[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"topic-GIS":3},{"name":4,"kind":5,"tokens":6,"total":7,"page":8,"page_size":9,"items":10},"GIS","tag",[4],67,1,100,[11,109,180,253,318,392,442,531,581,651,731,806,858,922,988,1039,1099,1165,1221,1288,1360,1420,1474,1525,1593,1640,1694,1772,1858,1923,1978,2026,2091,2133,2182,2260,2330,2402,2458,2507,2550,2594,2653,2735,2807,2872,2929,3006,3070,3126,3185,3244,3280,3332,3384,3457,3524,3590,3655,3700,3768,3845,3898,3965,4042,4092,4160],{"id":12,"title":13,"url":14,"summary":15,"summary_zh":16,"content":17,"source_name":18,"source_url":14,"published_at":19,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":23,"score_detail":24,"sources":31,"tags":33,"primary_topic":38,"secondary_topics":44,"classification":45,"search_phrases":86,"slug":89,"view_count":90,"doi":91,"paper":92,"created_at":108},5572,"Potential erosion risk assessment of Kanak stream basin (Sivas, Sarkisla) with the ICONA model","https:\u002F\u002Fdoi.org\u002F10.51753\u002Fflsrt.1828829","The rapid development of technology following the Industrial Revolution has increased human domination over nature. Erosion, which plays a critical role in the process of natural shaping of the earth, can accelerate over time because of improper utilization of the natural environment by humans. The main objective of this study is to determine the erosion susceptibility of the Kanak Creek Basin, one of the sub-basins in the upper reaches of the Kizilirmak River, using the ICONA model, whose main parameters are slope, lithology, land use and vegetation cover, and Geographic Information Systems (GIS) and Remote Sensing techniques, and to list the measures that can be taken against erosion. According to the results of the ICONA model potential erosion level map, 48% of the study area has low erosion susceptibility. These areas largely correspond to the vicinity of Sama Mountain, which has volcanic rocks resistant to erosion, and the base of Sarkisla Plain where the slope is very low. The plain floor is largely covered with agricultural lands. The expansion of irrigated agriculture in this region is one of the main measures that can be taken against erosion. Erosion susceptibility increases around Turna Mountain on the northern border of the basin and Cal Mountain in the south due to both the increase in slope and the lack of resistance of the rocks in the region to erosion, and corresponds to 30% of the study area. In 22% of the basin, susceptibility to erosion is at a medium level. Most of these areas consist of natural meadows and pastures. It is essential to take measures against overgrazing in these areas to prevent the complete loss of the already sparse vegetation cover. Planning land use in the basin in a sustainable manner, arranging fields and layers perpendicular to the slope, expanding irrigated agriculture, and preventing overgrazing are of vital importance in terms of combating soil erosion.","工业革命以来技术的迅猛发展增强了人类对自然的支配能力。侵蚀在地球自然塑造过程中起着关键作用，而人类对自然环境的不当利用会加速侵蚀进程。本研究的主要目标是利用ICONA模型（其主要参数为坡度、岩性、土地利用和植被覆盖）以及地理信息系统（GIS）和遥感技术，确定克孜勒河上游子流域之一卡纳克溪流域的侵蚀敏感性，并列出可采取的侵蚀防治措施。根据ICONA模型潜在侵蚀等级图的结果，研究区48%的区域侵蚀敏感性较低。这些区域主要对应于具有抗侵蚀火山岩的萨马山附近以及坡度极低的萨尔基什拉平原底部。平原底部大部分为农业用地覆盖。在该地区扩大灌溉农业是防治侵蚀的主要措施之一。在流域北部边界的图尔纳山和南部的恰尔山周围，由于坡度增大以及该地区岩石抗侵蚀能力不足，侵蚀敏感性增加，占研究区面积的30%。流域22%的区域侵蚀敏感性为中等水平。这些区域大部分为天然草甸和牧场。在这些地区采取措施防止过度放牧至关重要，以避免本已稀疏的植被覆盖完全丧失。以可持续方式规划流域土地利用、沿垂直于坡向布置田块和土层、扩大灌溉农业以及防止过度放牧，对防治土壤侵蚀具有至关重要的意义。",null,"Frontiers in Life Sciences and Related Technologies","2026-10-21T00:00:00Z","论文",10,false,61,{"impact":25,"substance":26,"depth":27,"authority":28,"freshness":29,"relevant":8,"comment":30},8,18,14,12,9,"该研究以ICONA模型结合GIS与遥感评估土耳其小流域侵蚀风险，方法规范、结论具体，但属区域性案例，公共影响有限，可作为专业参考而非每日精选。",[32],{"name":18,"url":14},[34,35,36,4,37],"遥感","土地利用","土壤侵蚀","水土保持",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",[],{"status":46,"locked":22,"version":47,"method":48,"evidence":49},"classified","2026-10-22.2","rules",{"candidates":50,"agricultural_evidence":52},[51,58,65,73,80],{"code":39,"score":21,"supported":52,"title":53,"abstract":54,"tags":57},true,[],[55,4,56],"地理信息","geographic information",[4],{"code":59,"score":60,"supported":52,"title":61,"abstract":62,"tags":64},"I3",7,[],[34,63],"remote sensing",[34],{"code":66,"score":67,"supported":52,"title":68,"abstract":69,"tags":72},"H2",6,[],[70,71],"土壤","soil",[],{"code":74,"score":75,"supported":52,"title":76,"abstract":77,"tags":79},"H3",3,[],[78],"灌溉",[],{"code":81,"score":82,"supported":22,"title":83,"abstract":84,"tags":85},"H6",2,[],[],[35,37],[87,88],"ICONA 模型 侵蚀风险","Kanak 流域 侵蚀","ICONA模型侵蚀风险-5572",0,"10.51753\u002Fflsrt.1828829",{"doi":91,"openalex_id":93,"authors":94,"venue":18,"cited_by_count":90,"oa_url":17,"card":100,"direction":106,"ingested_from":107},"W7223117733",[95,97],{"name":96,"orcid":17},"MERİÇ KURT",{"name":98,"orcid":99},"Celal ŞENOL","https:\u002F\u002Forcid.org\u002F0000-0003-0857-866X",{"tldr":101,"method":102,"finding":103,"direction":104,"opportunity":105},"用ICONA模型评估土耳其Kanak流域潜在侵蚀风险并列出防治措施。","ICONA模型结合GIS与遥感，输入坡度、岩性、土地利用与植被覆盖。","48%区域低侵蚀风险，30%高敏感，22%中等，主因坡度与岩性。","农业绿色发展与碳","可将ICONA与遥感时序数据结合，动态监测流域侵蚀并评估农业管理措施效果。","农业遥感与作物表型","openalex","2026-10-22T11:20:39.475037Z",{"id":110,"title":111,"url":112,"summary":113,"summary_zh":114,"content":17,"source_name":115,"source_url":112,"published_at":116,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":117,"score_detail":118,"sources":122,"tags":124,"primary_topic":128,"secondary_topics":132,"classification":133,"search_phrases":159,"slug":162,"view_count":90,"doi":163,"paper":164,"created_at":179},5495,"Artificial Neural Network-Based Prediction and Mapping of Elephant Corridors in West Bengal Using Geospatial and Environmental Variables","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23496876","The fragmentation of forest habitats and increasing anthropogenic pressures have significantly altered elephant movementpatternsinWestBengal,India,resultinginanescalatinghuman-elephantconflict.Accurateidentification and mapping of elephant corridors are essential for landscape-level conservation planning and mitigation.Traditional corridor mapping methods, including expert-based delineation and least-cost path analyses, oftenstruggle to capture the complex and nonlinear relationships between environmental variables influencing elephant movement. This study proposes an Artificial Neural Network (ANN)-based framework to predict potential elephant corridors across West Bengal using remotely sensed and geographic information system (GIS) datasets. The predictor variables included forest cover, normalized difference vegetation index (NDVI), elevation, slope,proximity to water sources, distance from roads, railways, settlements, agricultural land, and historical elephant occurrence records. The ANN model was trained using known elephant movement locations and validated using independent datasets. The predicted suitable surface was integrated into a GIS environment to identify probable movement corridors and prioritize areas for conservation. The proposed approach demonstrates the ability of machine learning to improve corridor prediction compared with conventional GIS-based techniques and provides a decision support tool for forest managers and policymakers.","森林栖息地的破碎化和日益增加的人为压力显著改变了印度西孟加拉邦大象的活动模式，导致人象冲突不断加剧。准确识别和绘制大象廊道对于景观层面的保护规划和冲突缓解至关重要。传统的廊道制图方法，包括基于专家的 delineation（边界划定）和最小成本路径分析，往往难以捕捉影响大象活动的环境变量之间复杂的非线性关系。本研究提出了一种基于人工神经网络（Artificial Neural Network, ANN）的框架，利用遥感数据和地理信息系统（Geographic Information System, GIS）数据集预测西孟加拉邦潜在的大象廊道。预测变量包括森林覆盖、归一化植被指数（Normalized Difference Vegetation Index, NDVI）、海拔、坡度、距水源的邻近度、距道路、铁路、居民点、农田的距离以及历史大象出现记录。ANN模型利用已知的大象活动位置进行训练，并使用独立数据集进行验证。将预测得到的适宜性表面整合到GIS环境中，以识别可能的迁移廊道并确定保护优先区域。所提出的方法展示了机器学习相较于传统基于GIS的技术在改进廊道预测方面的能力，并为森林管理者和政策制定者提供了决策支持工具。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-20T00:00:00Z",70,{"impact":28,"substance":119,"depth":120,"authority":28,"freshness":29,"relevant":8,"comment":121},20,17,"该研究用人工神经网络结合遥感与GIS预测大象迁徙走廊，方法新颖、数据扎实，对生态保护与乡村人兽冲突治理有参考价值，但属区域性研究，公共影响有限。",[123],{"name":115,"url":112},[125,34,4,126,127],"农业人工智能","野生动物保护","人兽冲突",{"code":43,"slug":129,"name":130,"path":131,"parent_code":17},"digital-agriculture","数字农业与前沿技术","\u002Ftopic\u002Fdigital-agriculture",[],{"status":134,"locked":22,"version":47,"method":48,"evidence":135},"partial",{"candidates":136,"agricultural_evidence":52,"reason":158},[137,145,149,154],{"code":138,"score":21,"supported":52,"title":139,"abstract":140,"tags":144},"I2",[],[141,142,143],"机器学习","machine learning","decision support",[125],{"code":39,"score":21,"supported":52,"title":146,"abstract":147,"tags":148},[],[55,4,56],[4],{"code":59,"score":150,"supported":52,"title":151,"abstract":152,"tags":153},4,[],[34],[34],{"code":81,"score":8,"supported":22,"title":155,"abstract":156,"tags":157},[],[],[126],"一级领域明确，二级方向需要细分",[160,161],"西孟加拉邦 大象走廊","人工神经网络 大象走廊","西孟加拉邦大象走廊-5495","10.5281\u002Fzenodo.23496876",{"doi":163,"openalex_id":165,"authors":166,"venue":115,"cited_by_count":90,"oa_url":112,"card":173,"direction":178,"ingested_from":107},"W7222999966",[167,169,171],{"name":168,"orcid":17},"Bhutia Dechen Doma",{"name":170,"orcid":17},"Swarup Das",{"name":172,"orcid":17},"Mandal Rakesh Kumar",{"tldr":174,"method":175,"finding":176,"direction":106,"opportunity":177},"用人工神经网络结合遥感与GIS变量预测并制图西孟加拉邦大象迁徙廊道。","ANN模型，输入遥感与GIS环境变量及历史象群出现记录，GIS集成制图。","ANN能刻画环境变量非线性关系，廊道预测优于传统GIS方法，可作决策支持工具。","可将ANN廊道预测与人类活动、农田冲突热点耦合，探索农业景观中野生动物通道与作物保护的协同规划。","农业人工智能与决策模型","2026-10-21T23:30:43.936453Z",{"id":181,"title":182,"url":183,"summary":184,"summary_zh":185,"content":17,"source_name":186,"source_url":183,"published_at":187,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":188,"score_detail":189,"sources":193,"tags":195,"primary_topic":199,"secondary_topics":200,"classification":201,"search_phrases":236,"slug":239,"view_count":90,"doi":240,"paper":241,"created_at":252},5403,"RS-GIS Based Dss (Decision Support System) for Land evaluation and Land resource management – (case study Amol District)","https:\u002F\u002Fdoi.org\u002F10.71500\u002Fthesis.2026.519222","Creating a proper planting pattern according to land talent identification, cannot be achieved without considering socioeconomic conditions and detailed holistic. This issue is considered by development of rice which is one of the main world’s most important agricultural products in rural areas and ensures their food security. In the country rice is considered as a strategic plant. This is among sustainable resources of area and attention to its development and expanding its cultivation causes farmers’ confidence and ensures economic stability of the region. On the other hand, crop insurance is same for all land, because statistical information on agricultural lands are most obtained through traditional methods based on the opinion of experts and individuals and collect this information always accompanied with error. Accordingly annually huge costs are paid for insured loss of agricultural lands Thus land evaluation, identification and resolution of land based on its capabilities by taking the capacity of the soil and environmental risks into account is essential for land management. This study presents a spatial decision support system (SDSS) to land evaluation and identification of suitable areas for rice cultivation in the studied area. After gathering data and field studies, various layers of criteria affecting decisions were created in GIS environment. Development of multi-criteria decision-making techniques (MCDM) is done using Analytical Hierarchy Process AHP, fuzzy logic and artificial neural networks. The comparison and integration of models (model compilation and standardization of fuzzy AHP, FAHP, fuzzy standardization and FAHP) was also carried out. To review and matching between fitness maps obtained from different models and the observed value of kappa coefficient was calculated. Neural network model with kappa coefficient 0.65 has highest fitness coefficient among land suitability class and the harvest amount and this due to the performance value in determining the classes is predictable in this model. After that, Fuzzy standardization compilation models and FAHP and Fuzzy standardization and AHP with Kappa coefficient of 0.54 and 0.51 respectively showed highest agreement between the land suitability classes and performance. The majority of lands located on non-prone class have high slope and if cultivation increase risk of soil erosion. Investigating area under rice plantation (paddy fields) with very prone and prone lands in different styles showed that almost the majority of this area is currently devoted to rice cultivation. Although neural network model showed higher accuracy than other models, but this assessment model requires data on rice yield and collecting performance rate required accuracy, cost and much time and sometimes land management and environmental hazards affects it.","根据土地适宜性识别来制定合理的种植模式，离不开对社会经济条件和详细整体性因素的考量。水稻作为世界最重要的农产品之一，其发展在农村地区受到重视，并保障了当地的粮食安全。在我国，水稻被视为战略作物。水稻是区域可持续资源之一，关注其发展并扩大种植面积能够增强农民信心，保障区域经济稳定。另一方面，作物保险对所有土地采取统一标准，因为农业用地的统计信息大多基于专家和个人意见通过传统方法获取，且此类信息的采集始终伴随着误差。因此，每年为农业用地保险损失支付巨额费用。有鉴于此，土地评价、识别及基于土地能力的土地问题解决，必须将土壤容量和环境风险纳入考量，这对土地管理至关重要。本研究提出了一种空间决策支持系统（SDSS），用于研究区域的土地评价和水稻适宜种植区识别。在收集数据和实地调研之后，于GIS环境中创建了影响决策的各准则图层。多准则决策技术（MCDM）的开发采用了层次分析法（AHP）、模糊逻辑和人工神经网络。同时进行了模型的比较与集成（模型编制与模糊AHP标准化、FAHP、模糊标准化与FAHP）。为审查和匹配不同模型获得的适宜性图件，计算了观测值与kappa系数。神经网络模型的kappa系数为0.65，在土地适宜性等级与产量之间具有最高的拟合系数，这归因于该模型在确定等级方面的性能值具有可预测性。其后，模糊标准化编制模型与FAHP、模糊标准化与AHP的kappa系数分别为0.54和0.51，在土地适宜性等级与产量之间表现出最高的一致性。位于非适宜等级的大多数土地具有高坡度，若扩大种植将增加土壤侵蚀风险。对不同适宜性等级下水稻种植区（稻田）的调查……","Test","2026-10-19T00:00:00Z",50,{"impact":25,"substance":190,"depth":191,"authority":75,"freshness":25,"relevant":8,"comment":192},16,15,"案例研究有一定方法参考价值，但来源不明、地域局限，不足以进入每日精选。",[194],{"name":186,"url":183},[196,34,4,197,198],"决策支持系统","水稻种植","土地评价",{"code":43,"slug":129,"name":130,"path":131,"parent_code":17},[],{"status":134,"locked":22,"version":47,"method":48,"evidence":202},{"candidates":203,"agricultural_evidence":52,"reason":158},[204,208,212,221,228,232],{"code":138,"score":28,"supported":52,"title":205,"abstract":206,"tags":207},[143],[143],[196],{"code":39,"score":28,"supported":52,"title":209,"abstract":210,"tags":211},[4],[4],[4],{"code":213,"score":21,"supported":52,"title":214,"abstract":215,"tags":220},"A1",[],[216,217,218,219],"水稻","稻田","rice","paddy",[197],{"code":222,"score":67,"supported":52,"title":223,"abstract":224,"tags":227},"A8",[],[225,226],"粮食安全","food security",[],{"code":66,"score":67,"supported":52,"title":229,"abstract":230,"tags":231},[],[70,71],[],{"code":59,"score":8,"supported":22,"title":233,"abstract":234,"tags":235},[],[],[34],[237,238],"Amol District 水稻 土地适宜性","RS-GIS 决策支持系统 土地评价","AmolDistrict水稻土地适宜性-5403","10.71500\u002Fthesis.2026.519222",{"doi":240,"openalex_id":242,"authors":243,"venue":186,"cited_by_count":90,"oa_url":183,"card":247,"direction":178,"ingested_from":107},"W7222963628",[244],{"name":245,"orcid":246},"Zeinab Maddahi","https:\u002F\u002Forcid.org\u002F0000-0002-2824-2736",{"tldr":248,"method":249,"finding":250,"direction":106,"opportunity":251},"构建基于RS-GIS的空间决策支持系统，评估伊朗Amol地区水稻种植适宜性。","GIS叠加多准则决策、AHP、模糊逻辑与人工神经网络，用Kappa系数验证。","神经网络模型Kappa系数0.65最高，土地适宜性与产量吻合最好。","可将该SDSS与实时遥感、作物保险定损结合，发展动态土地适宜性监测。","2026-10-20T23:30:40.596410Z",{"id":254,"title":255,"url":256,"summary":257,"summary_zh":258,"content":17,"source_name":259,"source_url":256,"published_at":187,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":90,"score_detail":260,"sources":262,"tags":264,"primary_topic":17,"secondary_topics":267,"classification":268,"search_phrases":285,"slug":288,"view_count":90,"doi":289,"paper":290,"created_at":317},5379,"GIS-based multi-criteria spatial decision support for equitable public toilet planning: mapping accessibility deficits, site suitability and priority intervention zones in Addis Ababa, Ethiopia","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44213-026-00088-5","Abstract Rapid urbanization frequently outpaces sanitation infrastructure, leaving vulnerable residents without essential services. This study develops and applies a GIS-based spatial decision-support framework combining multi-criteria decision analysis (MCDA), the Analytical Hierarchy Process (AHP), and network-based accessibility analysis to assess location suitability and prioritize public toilet development in Addis Ababa, Ethiopia. Eight spatial criteria, population density, proximity to public activity nodes, road connectivity, distance from existing facilities, land use\u002Fland cover, slope, soil characteristics, and proximity to rivers were standardized on a 1–5 suitability scale. A field inventory of 339 georeferenced facilities, constraint masking, network service-area analysis, and sensitivity analysis produced three principal findings. First, accessibility is severely deficient: only 25.07% of residents (822,514 of 3,280,422) live within the normative 500 m walking distance to public toilets; 74.93% lies beyond it. Second, provision is maldistributed: the highest-density population class records a provision ratio of 0.90 against 1.39 in the second-highest, with Addis Ketema and Yeka each serving ~ 13,400 residents per facility. Third, expert weights are internally consistent (CR = 0.0152), with demand and accessibility criteria receiving 79.2% of total weight. Suitability mapping classified 20.46% of the city (87.97 km²) as high\u002Fvery-high suitability. Overlaying suitability with service deficits and building-footprint constraints delineated a priority development envelope of 25.43 km² (5.91% of the city). Robustness testing across alternative weights and thresholds demonstrated stable spatial priorities (Jaccard similarity 0.60–0.97; AUC = 0.864). This framework provides municipal planners a transparent, reproducible basis for prioritizing sanitation investment, whilst acknowledging that tenure screening, community engagement, disability-responsive design, and environmental compliance remain essential.","摘要 快速城市化往往超出环境卫生基础设施的承载能力，致使弱势居民无法获得基本服务。本研究开发并应用了一个基于GIS的空间决策支持框架，该框架结合多准则决策分析（MCDA）、层次分析法（AHP）和基于网络的可达性分析，以评估埃塞俄比亚亚的斯亚贝巴公共厕所选址适宜性并确定建设优先序。八个空间准则——人口密度、公共活动节点邻近度、道路连通性、与现有设施的距离、土地利用\u002F土地覆盖、坡度、土壤特征及河流邻近度——被标准化为1–5级适宜性量表。通过对339处地理参照设施进行实地清查、约束掩膜、网络服务区分析和敏感性分析，得出三项主要发现。第一，可达性严重不足：仅25.07%的居民（3,280,422人中的822,514人）居住在距公共厕所规范规定的500米步行距离范围内；74.93%的居民超出该范围。第二，设施配置分布不均：人口密度最高等级的服务比率为0.90，而次高等级为1.39，Addis Ketema和Yeka每处设施各服务约13,400名居民。第三，专家权重具有内部一致性（CR = 0.0152），需求与可达性准则合计占总权重的79.2%。适宜性制图将全市20.46%的区域（87.97 km²）划为高\u002F极高适宜性。将适宜性与服务缺口及建筑轮廓约束叠加，划定出25.43 km²（占全市5.91%）的优先开发范围。跨替代权重与阈值的稳健性检验表明空间优先序稳定（Jaccard相似度0.60–0.97；AUC = 0.864）。该框架为市政规划者确定环境卫生投资优先序提供了透明、可复现的依据，同时承认土地权属筛查、社区参与、残障友好设计及环境合规仍不可或缺。","City and Built Environment",{"impact":90,"substance":90,"depth":90,"authority":90,"freshness":90,"relevant":90,"comment":261},"该研究聚焦埃塞俄比亚城市公共厕所规划，与三农、农业信息化、智慧农业等主题无关，不建议进入每日精选。",[263],{"name":259,"url":256},[4,265,266],"公共卫生设施","城市基础设施",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":270},"needs_review",{"candidates":271,"agricultural_evidence":22,"reason":284},[272,276,280],{"code":39,"score":28,"supported":52,"title":273,"abstract":274,"tags":275},[4],[4],[4],{"code":138,"score":25,"supported":52,"title":277,"abstract":278,"tags":279},[143],[],[],{"code":66,"score":67,"supported":52,"title":281,"abstract":282,"tags":283},[],[70,71],[],"农业相关性需要复核",[286,287],"亚的斯亚贝巴 公共厕所 GIS","公共卫生设施 城市基础设施 GIS","亚的斯亚贝巴公共厕所GIS-5379","10.1007\u002Fs44213-026-00088-5",{"doi":289,"openalex_id":291,"authors":292,"venue":259,"cited_by_count":90,"oa_url":309,"card":310,"direction":316,"ingested_from":107},"W7222967252",[293,295,297,300,303,306],{"name":294,"orcid":17},"Esubalew Mulugeta Engda",{"name":296,"orcid":17},"Mesfin Herchema",{"name":298,"orcid":299},"Ziyen Achamyeleh Mekonnen","https:\u002F\u002Forcid.org\u002F0009-0009-0913-1692",{"name":301,"orcid":302},"Kanenus Fufa Dararo","https:\u002F\u002Forcid.org\u002F0009-0007-5747-1558",{"name":304,"orcid":305},"Firdissa Sadeta Tiye","https:\u002F\u002Forcid.org\u002F0000-0002-9233-1741",{"name":307,"orcid":308},"Muralitharan Jothimani","https:\u002F\u002Forcid.org\u002F0000-0002-3766-0665","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44213-026-00088-5.pdf",{"tldr":311,"method":312,"finding":313,"direction":314,"opportunity":315},"用GIS多准则空间决策支持评估亚的斯亚贝巴公厕可达性缺口并划定优先建设区。","MCDA、AHP、网络可达性分析，结合339个设施实地清单与敏感性分析。","仅25.07%居民在500米步行范围内可达公厕，供给分布不均，高适宜区占20.46%。","数字乡村与农业信息化","可将该空间决策框架迁移至乡村卫生设施或农业服务设施布局优化，结合人口动态数据提升公平性。","智慧农业 \u002F 农业物联网","2026-10-20T23:30:08.538058Z",{"id":319,"title":320,"url":321,"summary":322,"summary_zh":323,"content":17,"source_name":324,"source_url":321,"published_at":325,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":326,"score_detail":327,"sources":329,"tags":331,"primary_topic":335,"secondary_topics":336,"classification":341,"search_phrases":368,"slug":371,"view_count":90,"doi":372,"paper":373,"created_at":391},5321,"GIS and remote sensing based multicriteria analysis for identifying potential agricultural land: A case study on Savar Upazila, Bangladesh","https:\u002F\u002Fdoi.org\u002F10.3329\u002Fbrds.v26i1.94265","Despite of gradually decreasing its contribution to gross domestic product (GDP), agriculture, however, is the backbone of the Bangladeshi economy. Farming is the primary mean of rural livelihoods in Bangladesh but agricultural land is slowly declining day by day. Although, at present, Bangladesh is self-sufficient in terms of producing food, especially rice and some other major agricultural products, it is predicted that, in near future, the country is going to face immense challenges due to climate related threats. The research aims to identify the potential lands for suitable farming in Savar Upazila (sub-district) under Dhaka district applying a geographic information system (GIS) and remote sensing (RS) based multicriteria analysis. Relevant biophysical characteristics of soil, terrain, and landuse and land cover (LULC) were considered. Soil and evelvation data was collected from Soil Resource Development Institute (SRDI)and Shuttle Radar Topography Mission (SRTM), respectively, whereas satellite images were collected from Landsat-8. The maximum likelihood supervised classification technique was used for LULC classification, and the multicriteria evaluation (MCE) and analytical hierarchy process (AHP) approach was employed to identify suitable areas for farming. The research finds the LULC classes are agricultural land, built-up area, fallow land, vegetation cover, waterbodies, and wetland are 12.42%, 31.01%, 25.69%, 25.98%, 4.81%, and 0.09%, respectively. This research also finds that agricultural land suitability was classified as highly suitable, moderately suitable, marginally suitable, and not suitable are 24.28%, 29.53%, 24.66%, and 21.53%, respectively. In contrast, the current agricultural land usage accounts for just 12.42% of the total land area in this research area. The Kappa accuracy has been measured at a value of 0.88 and an overall accuracy value of 0.90 which indicates that the LULC classification is done almost perfectly. This study offered information at the local level that farmers may utilize to decide on cropping patterns and appropriateness. Bangladesh Rural Development Studies, 26(1), 2023 (13-26)","尽管农业在国内生产总值（GDP）中的贡献逐渐下降，但它仍是孟加拉国经济的支柱。农耕是孟加拉国农村生计的主要方式，但农业用地正日益减少。虽然目前孟加拉国在粮食生产方面，尤其是稻米和其他一些主要农产品方面已实现自给自足，但据预测，在不久的将来，该国将因气候相关威胁而面临巨大挑战。本研究旨在运用地理信息系统（GIS）和遥感（RS）基础上的多准则分析，确定达卡县萨瓦尔乡（分区）适宜耕作的土地潜力。研究考虑了土壤、地形以及土地利用与土地覆盖（LULC）等相关生物物理特征。土壤数据来自土壤资源开发研究所（SRDI），高程数据来自航天飞机雷达地形测绘任务（SRTM），卫星影像则来自Landsat-8。土地利用与土地覆盖分类采用最大似然监督分类技术，适宜耕作区的识别则运用多准则评价（MCE）和层次分析法（AHP）。研究发现，土地利用与土地覆盖类别中，农业用地、建成区、休耕地、植被覆盖、水体及湿地分别占12.42%、31.01%、25.69%、25.98%、4.81%和0.09%。研究还发现，农业用地适宜性分为高度适宜、中度适宜、勉强适宜和不适宜，分别占24.28%、29.53%、24.66%和21.53%。相比之下，当前农业用地仅占本研究区土地总面积的12.42%。Kappa精度值为0.88，总体精度值为0.90，表明土地利用与土地覆盖分类近乎完美。本研究提供了地方层面的信息，可供农民在决定种植模式和适宜性时参考。《孟加拉国农村发展研究》，第26卷第1期，2023年（第13-26页）","OpenAlex","2026-10-18T00:00:00Z",60,{"impact":25,"substance":26,"depth":191,"authority":21,"freshness":29,"relevant":8,"comment":328},"方法规范、数据可靠的区域农用地适宜性案例研究，但属孟加拉地方尺度，对国内三农信息化仅有方法借鉴价值，不宜进入每日精选。",[330],{"name":324,"url":321},[34,4,332,333,334],"农用地适宜性","土地覆被","孟加拉农业",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[337],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":46,"locked":22,"version":47,"method":48,"evidence":342},{"candidates":343,"agricultural_evidence":52},[344,348,352,357,364],{"code":39,"score":26,"supported":52,"title":345,"abstract":346,"tags":347},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":349,"abstract":350,"tags":351},[63],[34,63],[34],{"code":213,"score":67,"supported":52,"title":353,"abstract":354,"tags":356},[],[355,218],"稻米",[],{"code":358,"score":67,"supported":52,"title":359,"abstract":360,"tags":363},"G",[],[361,362],"农村发展","rural development",[],{"code":66,"score":67,"supported":52,"title":365,"abstract":366,"tags":367},[],[70,71],[],[369,370],"Savar Upazila 农用地适宜性","Landsat-8 土地覆被分类","SavarUpazila农用地适宜性-5321","10.3329\u002Fbrds.v26i1.94265",{"doi":372,"openalex_id":374,"authors":375,"venue":385,"cited_by_count":90,"oa_url":321,"card":386,"direction":106,"ingested_from":107},"W7222895468",[376,378,380,382],{"name":377,"orcid":17},"Raju Ahmed",{"name":379,"orcid":17},"Shaikh Mehdee Mohammad",{"name":381,"orcid":17},"Ummul Momanin Coalee",{"name":383,"orcid":384},"Khandakar Hasan Mahmud","https:\u002F\u002Forcid.org\u002F0000-0003-1222-0791","The Bangladesh Rural Development Studies",{"tldr":387,"method":388,"finding":389,"direction":106,"opportunity":390},"用GIS与遥感多准则分析评估孟加拉Savar地区潜在农业用地适宜性。","Landsat-8监督分类提取土地利用，结合土壤、地形数据用AHP与MCE做适宜","仅12.42%为农地，高、中、边缘、不适宜分别占24.28%、29.53%、24.66%、21.53","可引入时序遥感与气候情景，动态评估适宜性变化并耦合作物种植决策支持。","2026-10-19T23:30:22.906704Z",{"id":393,"title":394,"url":395,"summary":396,"summary_zh":397,"content":17,"source_name":398,"source_url":395,"published_at":399,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":90,"score_detail":400,"sources":402,"tags":404,"primary_topic":17,"secondary_topics":405,"classification":406,"search_phrases":421,"slug":424,"view_count":90,"doi":425,"paper":426,"created_at":441},5187,"Determination of Erosion Potential of Rioni River Basin Using GIS and RUSLE Model","https:\u002F\u002Fdoi.org\u002F10.47191\u002Fetj\u002Fv11i10.07","This study focuses on determining the soil erosion potential within the Rioni River basin using the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) technologies. A 90-meter resolution Digital Elevation Model (DEM) from the Shuttle Radar Topographic Mission (SRTM) was utilized to delineate the basin boundaries and hydrological network. The RUSLE model, an empirical approach, was applied to estimate the long-term average annual soil loss. Individual RUSLE factors were computed using specific methodologies: the rainfall-runoff factor (R) was derived from a linear empirical relationship based on average atmospheric precipitation (1989-2021); the soil erodibility factor (K) was calculated using the Sharpley–Williams equation, yielding a value of 0.0184 for the prevalent soil type; the topographic factor (LS) was determined using a RUSLE-adapted approach; the cover-management factor (C) was calculated using the Durigon equation from NDVI values; and the support practice factor (P) was assigned based on slope and cultivation practices. Results indicate that the R-factor ranges from 313.65 to 473.89 MJ×mm\u002F(ha×hours), with an average of 391.02 MJ×mm\u002F(ha×hours). The maximum LS-factor reached 7137.810. The C-factor values (0.104 to 0.769) suggest a significant risk of water erosion across the basin. Overall, the study concludes that riverbed erosion predominantly occurs in the Rioni River basin, primarily influenced by flow velocity and slope.","本研究聚焦于利用修正通用土壤流失方程（RUSLE）与地理信息系统（GIS）技术，确定里奥尼河流域的土壤侵蚀潜力。研究采用航天飞机雷达地形测绘任务（SRTM）提供的90米分辨率数字高程模型（DEM）来划定流域边界与水文网络。RUSLE模型作为一种经验方法，被用于估算长期年均土壤流失量。各RUSLE因子采用特定方法计算：降雨-径流因子（R）基于1989—2021年平均大气降水量，通过线性经验关系推导得出；土壤可蚀性因子（K）采用Sharpley–Williams方程计算，针对主要土壤类型所得值为0.0184；地形因子（LS）采用RUSLE适配方法确定；覆盖管理因子（C）利用NDVI值，通过Durigon方程计算；支持措施因子（P）则依据坡度与耕作方式赋值。结果表明，R因子范围为313.65至473.89 MJ×mm\u002F（ha×小时），平均值为391.02 MJ×mm\u002F（ha×小时）。LS因子最大值达到7137.810。C因子值（0.104至0.769）表明全流域存在显著的水蚀风险。总体而言，研究认为里奥尼河流域的侵蚀主要发生在河床，主要受流速与坡度影响。","Engineering and Technology Journal","2026-10-15T00:00:00Z",{"impact":90,"substance":90,"depth":90,"authority":90,"freshness":90,"relevant":90,"comment":401},"该研究以格鲁吉亚里奥尼河流域为对象，属于水土保持与遥感应用类论文，与三农、农业信息化、智慧农业等主题无直接关联，不建议进入每日精选。",[403],{"name":398,"url":395},[34,36,4],[],{"status":269,"locked":22,"version":47,"method":48,"evidence":407},{"candidates":408,"agricultural_evidence":22,"reason":284},[409,413,417],{"code":39,"score":191,"supported":52,"title":410,"abstract":411,"tags":412},[4],[55,4],[4],{"code":66,"score":67,"supported":52,"title":414,"abstract":415,"tags":416},[],[70,71],[],{"code":59,"score":8,"supported":22,"title":418,"abstract":419,"tags":420},[],[],[34],[422,423],"RUSLE GIS 土壤侵蚀","土壤侵蚀 遥感 GIS","RUSLEGIS土壤侵蚀-5187","10.47191\u002Fetj\u002Fv11i10.07",{"doi":425,"openalex_id":427,"authors":428,"venue":398,"cited_by_count":90,"oa_url":435,"card":436,"direction":314,"ingested_from":107},"W7222052256",[429,431,433],{"name":430,"orcid":17},"GIORGI CHITIASHVILI",{"name":432,"orcid":17},"IRMA INASHVILI",{"name":434,"orcid":17},"IRINA KLIMIASHVILI","https:\u002F\u002Fwww.everant.org\u002Findex.php\u002Fetj\u002Farticle\u002Fdownload\u002F2054\u002F2236",{"tldr":437,"method":438,"finding":439,"direction":106,"opportunity":440},"用GIS和RUSLE模型评估里奥尼河流域土壤侵蚀潜力。","RUSLE模型结合SRTM DEM、NDVI与降水数据计算各侵蚀因子。","流域以河床侵蚀为主，主要受流速和坡度影响，存在显著水蚀风险。","可引入高分辨率遥感与时序NDVI改进C因子，并耦合水文模型动态评估侵蚀。","2026-10-17T23:30:38.427888Z",{"id":443,"title":444,"url":445,"summary":446,"summary_zh":447,"content":17,"source_name":448,"source_url":449,"published_at":399,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":450,"score_detail":451,"sources":454,"tags":456,"primary_topic":461,"secondary_topics":462,"classification":463,"search_phrases":489,"slug":492,"view_count":90,"doi":493,"paper":494,"created_at":530},5183,"Zionist Entity Settlement Expansion and Agricultural Land Conversion in the West Bank, Palestine (2011–2026): A Multi-Temporal Remote Sensing Analysis","https:\u002F\u002Fdoi.org\u002F10.63318\u002Fwaujpasv4i2_60","أُجريت هذه الدراسة لتقييم التغيرات في أنماط الاستيطان التابعة للكيان الصهيوني في الضفة الغربية بفلسطين، وذلك خلال الفترة الممتدة من عام 2011 إلى عام 2026، مع التركيز بشكل خاص على التغيرات التي طرأت على الأراضي الزراعية. وقد وظّف البحث تقنيات الاستشعار عن بعد لتحليل البيانات وتقييم اتجاهات التوسع الاستيطاني في المنطقة المختارة؛ حيث استخدم الباحثون صور الأقمار الصناعية ونظم المعلومات الجغرافية لرصد نمو المستوطنات، وتحديد المناطق المطوّرة حديثاً، ودراسة التغيرات في الغطاء الأرضي. وهدفت الدراسة إلى تحليل المناطق المبنية، والأراضي الزراعية، والغطاء النباتي، والأراضي القاحلة، والموارد المائية، فضلاً عن تحديد بؤر التوسع الاستيطاني، والمقارنة بين التجمعات الاستيطانية المختارة، ورصد التغيرات في شبكة الطرق، ودراسة التحولات في استخدامات الأراضي داخل المنطقة. ولتحقيق أهداف الدراسة، اعتمد الباحثون على مزيج من المنهجيات التي تشمل تصنيف الصور، وكشف التغيرات، وتحليل التراكب، وتحليل البؤر الساخنة. وتمثّل الهدف الرئيسي للدراسة في إرساء أساس لفهم انتشار المستوطنات ورصد التغيرات المرتبطة بالزراعة والتجمعات السكانية المجاورة بشكل أفضل، وذلك بالاستعانة بتقنيات الاستشعار عن بعد ونظم المعلومات الجغرافية.","本研究旨在评估2011年至2026年期间巴勒斯坦约旦河西岸犹太复国主义实体定居模式的变化，特别关注农业用地的变化。研究采用遥感技术分析数据并评估所选地区定居点扩张的趋势；研究人员利用卫星图像和地理信息系统监测定居点的增长、确定新开发区域并研究地表覆盖变化。研究旨在分析建成区、农业用地、植被覆盖、干旱土地和水资源，并确定定居点扩张的热点区域，比较选定的定居点集群，监测道路网络的变化，以及研究区域内土地利用的转变。为实现研究目标，研究人员采用了多种方法相结合的方式，包括图像分类、变化检测、叠加分析和热点分析。研究的主要目标是为理解定居点的扩散以及更好地监测与农业和邻近居民点相关的变化奠定基础，借助遥感技术和地理信息系统实现这一目标。","Wadi Alshatti University Journal of Pure and Applied Sciences","https:\u002F\u002Fwaujpas.com\u002Findex.php\u002Fjournal\u002Farticle\u002Fview\u002F775",78,{"impact":26,"substance":452,"depth":26,"authority":28,"freshness":25,"relevant":8,"comment":453},22,"该研究利用多时相遥感与GIS定量分析2011–2026年西岸定居点扩张导致的农地转换，方法规范、数据跨度长，对农业土地变化监测有参考价值，但地域性强、政策关联度有限，可作国际农业遥感案例收录。",[455],{"name":448,"url":449},[457,458,4,459,460],"遥感监测","土地利用变化","农地非农化","巴勒斯坦农业",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},[],{"status":46,"locked":22,"version":47,"method":48,"evidence":464},{"candidates":465,"agricultural_evidence":52},[466,470,474,479,485],{"code":59,"score":28,"supported":52,"title":467,"abstract":468,"tags":469},[63],[34],[457],{"code":39,"score":150,"supported":52,"title":471,"abstract":472,"tags":473},[],[55],[4],{"code":74,"score":75,"supported":52,"title":475,"abstract":476,"tags":478},[],[477],"水资源",[],{"code":480,"score":75,"supported":52,"title":481,"abstract":482,"tags":484},"H7",[],[483],"干旱",[],{"code":81,"score":8,"supported":22,"title":486,"abstract":487,"tags":488},[],[],[458],[490,491],"West Bank 遥感 农地变化","巴勒斯坦 定居点 农地转换","WestBank遥感农地变化-5183","10.63318\u002Fwaujpasv4i2_60",{"doi":493,"openalex_id":495,"authors":496,"venue":448,"cited_by_count":90,"oa_url":449,"card":525,"direction":106,"ingested_from":107},"W7222438368",[497,499,501,503,506,508,510,512,514,516,519,520,521,523],{"name":498,"orcid":17},"أسامة الشلطامي",{"name":500,"orcid":17},"مصطفى بن حكومة",{"name":502,"orcid":17},"حمزة الماطوني",{"name":504,"orcid":505},"Ramzi SALEM","https:\u002F\u002Forcid.org\u002F0000-0003-1539-1596",{"name":507,"orcid":17},"Mansour Salem",{"name":509,"orcid":17},"هالة الخزندار",{"name":511,"orcid":17},"ياسر نصار",{"name":513,"orcid":17},"Osama Shaltami",{"name":515,"orcid":17},"Mustafa Ben Hkoma",{"name":517,"orcid":518},"HAMZA AL MATONI","https:\u002F\u002Forcid.org\u002F0000-0002-4748-065X",{"name":504,"orcid":505},{"name":507,"orcid":17},{"name":522,"orcid":17},"Hala El-Khozondar",{"name":524,"orcid":17},"Yasser Nassar",{"tldr":526,"method":527,"finding":528,"direction":106,"opportunity":529},"用多时相遥感分析2011–2026年约旦河西岸定居点扩张及农地转化。","多时相卫星影像与GIS，结合影像分类、变化检测、叠加和热点分析。","定居点扩张显著侵占农地与植被，道路网络扩展驱动土地利用转变。","可延伸至多时相遥感监测土地权属冲突区农地流失，结合高分影像与开放GIS做定量归因。","2026-10-17T23:30:32.831824Z",{"id":532,"title":533,"url":534,"summary":535,"summary_zh":536,"content":17,"source_name":537,"source_url":534,"published_at":538,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":90,"score_detail":539,"sources":541,"tags":543,"primary_topic":17,"secondary_topics":545,"classification":546,"search_phrases":557,"slug":560,"view_count":90,"doi":561,"paper":562,"created_at":580},5167,"Archaeological Prospectivity and Terrace Morphometry Using Open Geospatial Data: A Reproducible GIS–Machine‐Learning Workflow for the Cuyes River Valley, Ecuador","https:\u002F\u002Fdoi.org\u002F10.1002\u002Farp.70071","ABSTRACT This study develops and evaluates a reproducible archaeological prospectivity workflow for data‐scarce tropical landscapes by integrating restricted legacy archaeological documentation with openly accessible environmental geospatial datasets. The Cuyes River Valley in southern Ecuador, located on the eastern‐Andean foothills where montane environments descend toward the Upper Amazon basin, provides the test case. Archaeological reports produced in 2009–2010 were converted into a structured inventory of 78 terrace records from Espíritu Playa, San Miguel de Cuyes and Nueva Zaruma. Terrace morphometry was analysed using area, height, length–width ratio and elevation, whereas K ‐means clustering identified recurrent forms. A presence–background random forest model combined known terrace locations with Copernicus DEM‐derived elevation, slope and roughness and WorldClim temperature and precipitation covariates. Spatial cross‐validation yielded a mean ROC‐AUC of 0.753 and mean average precision of 0.604, indicating useful but spatially variable ranking performance. Annual precipitation, elevation and annual mean temperature were the strongest model predictors. The results distinguish higher, cooler and drier upper valley systems from a lower, warmer and wetter Nueva Zaruma context, whereas morphometric clustering separates moderate upper valley terraces, large construction units, lower valley compact terraces and small elongated features. Exact archaeological coordinates were withheld and public outputs spatially generalized. Beyond the case study, the workflow demonstrates how legacy archaeological records can be transformed into reproducible, ethically constrained prospectivity products for survey prioritization and heritage management where field data and high‐resolution remote sensing remain limited.","摘要 本研究开发并评估了一套可重复的考古前景性工作流程，适用于数据稀缺的热带景观，其方法是将有限的遗留考古文献与公开可获取的环境地理空间数据集相结合。位于厄瓜多尔南部的库耶斯河谷（Cuyes River Valley）地处东安第斯山麓，山地环境由此向亚马逊盆地上游过渡，为本研究提供了测试案例。2009—2010年产生的考古报告被转换为结构化清单，收录了来自埃斯皮里图普拉亚（Espíritu Playa）、圣米格尔德库耶斯（San Miguel de Cuyes）和新萨鲁马（Nueva Zaruma）的78处台地记录。台地形态计量采用面积、高度、长宽比和海拔进行分析，同时运用K均值聚类识别重复出现的形态类型。研究构建了存在—背景随机森林模型，将已知台地位置与哥白尼DEM衍生的海拔、坡度和粗糙度以及WorldClim温度和降水协变量相结合。空间交叉验证得出平均ROC-AUC为0.753，平均精度为0.604，表明模型具有实用但空间可变的分级排序性能。年降水量、海拔和年平均气温是最强的模型预测因子。结果将较高、较冷且较干燥的上游河谷系统与较低、较暖且较湿润的新萨鲁马环境区分开来，而形态计量聚类则区分了中等上游河谷台地、大型建筑单元、下游河谷紧凑台地和小型狭长地物。精确的考古坐标未予公开，公开成果经过空间概化处理。除案例研究外，该工作流程展示了如何将遗留考古记录转化为可重复、受伦理约束的前景性产品，用于在野外数据和高分辨率遥感仍然有限的地区开展调查优先级排序和遗产管理。","Archaeological Prospection","2026-10-16T00:00:00Z",{"impact":90,"substance":90,"depth":90,"authority":90,"freshness":90,"relevant":90,"comment":540},"该研究属于考古空间分析，与三农、农业信息化主题无关，不建议进入每日精选。",[542],{"name":537,"url":534},[34,4,544],"考古",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":547},{"candidates":548,"agricultural_evidence":22,"reason":284},[549,553],{"code":39,"score":29,"supported":52,"title":550,"abstract":551,"tags":552},[4],[],[4],{"code":59,"score":60,"supported":52,"title":554,"abstract":555,"tags":556},[],[34,63],[34],[558,559],"考古 遥感 GIS","考古 遥感","考古遥感GIS-5167","10.1002\u002Farp.70071",{"doi":561,"openalex_id":563,"authors":564,"venue":537,"cited_by_count":90,"oa_url":574,"card":575,"direction":106,"ingested_from":107},"W7222708956",[565,568,571],{"name":566,"orcid":567},"Julio Guerra","https:\u002F\u002Forcid.org\u002F0000-0001-5278-719X",{"name":569,"orcid":570},"Danny Israel Benavides Pérez","https:\u002F\u002Forcid.org\u002F0000-0001-8979-3796",{"name":572,"orcid":573},"Marcelo Muñoz","https:\u002F\u002Forcid.org\u002F0009-0008-3705-5167","https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002Fpdfdirect\u002F10.1002\u002Farp.70071",{"tldr":576,"method":577,"finding":578,"direction":106,"opportunity":579},"用开放地理数据与随机森林构建可复现的考古潜力预测流程，识别厄瓜多尔梯田形态与分布。","整合78条梯田记录、Copernicus DEM与WorldClim变量，用K-","年降水、海拔和年均温是主要预测因子，模型AUC为0.753，空间表现存在差异。","可将该可复现流程迁移到数据稀缺山区的梯田识别与遗产调查优先级排序。","2026-10-17T23:30:28.431013Z",{"id":582,"title":583,"url":584,"summary":585,"summary_zh":586,"content":17,"source_name":587,"source_url":584,"published_at":538,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":588,"score_detail":589,"sources":591,"tags":593,"primary_topic":596,"secondary_topics":597,"classification":598,"search_phrases":625,"slug":628,"view_count":90,"doi":629,"paper":630,"created_at":650},5166,"Application of the SCS–CN Method Integrated with GIS and Remote Sensing for Watershed Runoff Estimation: A Review","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fijecc\u002F2026\u002Fv16i105735","Accurate estimation of runoff is crucial for watershed planning, soil and water conservation, flood mitigation, and the management of ungauged watersheds. The Soil Conservation Service Curve Number (SCS-CN) method has been extensively used because of its minimal input requirements and its ability to model the spatial influence of land use, soil properties, and hydrologic soil groups. This review compiles applications of the GIS-based SCS-CN method reported for watersheds in semi-arid and monsoon-affected countries such as India, Saudi Arabia, Afghanistan, China, Iraq, and Ethiopia. The reviewed literature employed rainfall data, land-use\u002Fland-cover data, soil maps, hydrologic soil groups, digital elevation models, and watershed morphometry to calculate curve numbers and direct runoff. The reported CN values varied substantially, from about 40 under dry conditions to more than 90 under urban, rocky, agricultural, or poorly infiltrating conditions. Runoff estimates ranged from relatively low values in arid catchments to more than 1,300 mm per year in high-rainfall watersheds. Several studies reported high R2 correlations between observed and estimated runoff, typically ranging from 0.73 to 0.98. Important limitations identified in the review include the sensitivity of results to the choice of curve number, antecedent moisture condition, initial abstraction assumption, land-use classification, soil-group assignment, rainfall representation, and the lack of observed discharge data. The overall design of the SCS-CN method and its integration with RS and GIS offer a practical approach to assessing spatial runoff and prioritising watersheds, but the method requires local calibration, uncertainty analysis, and validation against observed rainfall–runoff data.","径流的准确估算对于流域规划、水土保持、洪水缓解以及无资料流域的管理至关重要。土壤保持服务曲线数（SCS-CN）方法因其输入需求少、能够模拟土地利用、土壤性质和水文土壤组的空间影响而被广泛使用。本综述汇编了基于GIS的SCS-CN方法在半干旱和受季风影响国家（如印度、沙特阿拉伯、阿富汗、中国、伊拉克和埃塞俄比亚）流域的应用报道。所综述的文献利用降雨数据、土地利用\u002F土地覆盖数据、土壤图、水文土壤组、数字高程模型和流域形态计量来计算曲线数和直接径流。报道的CN值差异很大，从干旱条件下的约40到城市、岩石、农业或入渗不良条件下的90以上不等。径流估算值从干旱集水区的相对较低值到高降雨流域的年径流量超过1300 mm不等。多项研究报告了观测径流与估算径流之间的高R²相关性，通常在0.73至0.98之间。本综述识别出的重要局限性包括：结果对曲线数选择、前期土壤湿润条件、初始损失假设、土地利用分类、土壤组赋值、降雨代表性以及缺乏实测流量数据的敏感性。SCS-CN方法的总体设计及其与遥感和GIS的集成，为评估空间径流和流域优先排序提供了一种实用方法，但该方法需要本地校准、不确定性分析，并依据实测降雨—径流数据进行验证。","International Journal of Environment and Climate Change",63,{"impact":25,"substance":26,"depth":190,"authority":28,"freshness":29,"relevant":8,"comment":590},"综述系统梳理了GIS与遥感集成的SCS-CN径流估算方法及其局限，对农业信息化中的流域水资源与水土保持管理有参考价值，但属方法综述、影响面有限，未达每日精选门槛。",[592],{"name":587,"url":584},[34,4,37,594,595],"流域管理","水文模型",{"code":43,"slug":129,"name":130,"path":131,"parent_code":17},[],{"status":134,"locked":22,"version":47,"method":48,"evidence":599},{"candidates":600,"agricultural_evidence":52,"reason":158},[601,605,609,613,617,621],{"code":59,"score":28,"supported":52,"title":602,"abstract":603,"tags":604},[63],[34],[34],{"code":39,"score":28,"supported":52,"title":606,"abstract":607,"tags":608},[4],[4],[4],{"code":66,"score":67,"supported":52,"title":610,"abstract":611,"tags":612},[],[70,71],[],{"code":81,"score":150,"supported":52,"title":614,"abstract":615,"tags":616},[],[37],[37],{"code":480,"score":75,"supported":52,"title":618,"abstract":619,"tags":620},[],[483],[],{"code":74,"score":8,"supported":22,"title":622,"abstract":623,"tags":624},[],[],[595],[626,627],"SCS-CN GIS 遥感 径流估算","水土保持 水文模型 流域管理 遥感","SCS-CNGIS遥感径流估算-5166","10.9734\u002Fijecc\u002F2026\u002Fv16i105735",{"doi":629,"openalex_id":631,"authors":632,"venue":587,"cited_by_count":90,"oa_url":584,"card":645,"direction":106,"ingested_from":107},"W7222632567",[633,635,637,639,641,643],{"name":634,"orcid":17},"Sudhir Lad",{"name":636,"orcid":17},"R. D. Bansod",{"name":638,"orcid":17},"Bhaupatil Gavit",{"name":640,"orcid":17},"Sachin Nandgude",{"name":642,"orcid":17},"Shailendra Gadge",{"name":644,"orcid":17},"Mahesh Patil",{"tldr":646,"method":647,"finding":648,"direction":106,"opportunity":649},"综述GIS与遥感集成的SCS-CN法在半干旱与季风区流域径流估算的应用。","汇总印度、中国等国文献，用降雨、土地利用、土壤图、DEM与流域形态计算CN和径流","CN约40至90以上，年径流差异大，R²多在0.73至0.98，但结果对CN与前期湿度等敏感。","可研究CN本地化校准与不确定性量化，并结合实测径流验证，提升无资料流域径流估算可靠性。","2026-10-17T23:30:28.373754Z",{"id":652,"title":653,"url":654,"summary":655,"summary_zh":656,"content":17,"source_name":657,"source_url":654,"published_at":399,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":658,"score_detail":659,"sources":662,"tags":664,"primary_topic":17,"secondary_topics":668,"classification":669,"search_phrases":696,"slug":699,"view_count":90,"doi":700,"paper":701,"created_at":730},5088,"Spatial Analysis of the Potential for Irrigation Development in the Ertis Water Management Basin Using Multi-Criteria Analysis and Remote Sensing","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fearth7050171","Sustainable expansion of irrigated agriculture requires the identification of areas with favorable biophysical conditions while also considering water-resource and infrastructure constraints. This study assessed the biophysical land suitability for potential irrigation development within the Ertis Water Management Basin (WMB), Kazakhstan, using an integrated remote sensing, geographic information system (GIS), and Analytic Hierarchy Process (AHP) framework. Four criteria—slope, normalized difference vegetation index (NDVI), land use\u002Fland cover (LULC), and soil texture—were standardized into five suitability classes and integrated using an AHP-based weighted overlay. The derived weights were 0.51 for slope, 0.26 for NDVI, 0.14 for LULC, and 0.09 for soil texture, with a consistency ratio of approximately 1%. The resulting assessment classified approximately 10% of the basin as highly suitable (S1), 43% as suitable (S2), 18% as moderately suitable (S3), 2% as marginally suitable (S4), and 27% as not suitable (NS), indicating that approximately 53% of the basin falls within the two highest suitability classes. Regional analysis showed that substantial shares of suitable land are concentrated in Pavlodar and Abay Regions, while suitable areas were identified across a wide range of distances from the river network. These findings indicate considerable biophysical potential for irrigation development across the Ertis WMB, with suitable areas occurring both near and farther from the river network. The resulting suitability map provides a spatial basis for identifying areas where more detailed assessments of water availability, irrigation infrastructure, and development feasibility can subsequently be undertaken.","灌溉农业的可持续扩展需要识别具有有利生物物理条件的区域，同时还需考虑水资源和基础设施约束。本研究采用遥感、地理信息系统（GIS）和层次分析法（AHP）集成框架，评估了哈萨克斯坦额尔齐斯水资源管理流域（WMB）内潜在灌溉开发的生物物理土地适宜性。将坡度、归一化植被指数（NDVI）、土地利用\u002F土地覆盖（LULC）和土壤质地四项指标标准化为五个适宜性等级，并利用基于AHP的加权叠加进行集成。所得权重为：坡度0.51、NDVI 0.26、LULC 0.14、土壤质地0.09，一致性比率约为1%。评估结果将流域约10%的区域划为高度适宜（S1），43%为适宜（S2），18%为中等适宜（S3），2%为勉强适宜（S4），27%为不适宜（NS），表明流域约53%的面积属于两个最高适宜性等级。区域分析显示，适宜土地中有相当比例集中在巴甫洛达尔州和阿拜州，同时在距河网不同距离范围内均识别出适宜区域。这些结果表明，额尔齐斯水资源管理流域内灌溉开发具有可观的生物物理潜力，适宜区域既分布于河网附近，也分布于距河网较远的地方。所生成的适宜性图为后续开展更详细的水资源可利用性、灌溉基础设施和开发可行性评估提供了空间依据。","Earth",71,{"impact":28,"substance":119,"depth":120,"authority":660,"freshness":29,"relevant":8,"comment":661},13,"基于遥感、GIS与AHP的灌溉潜力空间评估，方法规范、数据翔实，对农业水资源规划有参考价值，但属区域案例研究，公共影响有限。",[663],{"name":657,"url":654},[34,665,4,666,667],"水资源管理","土地适宜性","灌溉潜力",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":670},{"candidates":671,"agricultural_evidence":52,"reason":695},[672,677,682,686,690],{"code":74,"score":26,"supported":52,"title":673,"abstract":675,"tags":676},[674],"irrigation",[78,477,674],[665],{"code":39,"score":26,"supported":52,"title":678,"abstract":680,"tags":681},[679],"spatial analysis",[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":683,"abstract":684,"tags":685},[63],[34,63],[34],{"code":66,"score":67,"supported":52,"title":687,"abstract":688,"tags":689},[],[70,71],[],{"code":691,"score":8,"supported":22,"title":692,"abstract":693,"tags":694},"H1",[],[],[666],"多个产业证据相当，需要确认主归属",[697,698],"Ertis 流域 灌溉潜力","哈萨克斯坦 灌溉 遥感","Ertis流域灌溉潜力-5088","10.3390\u002Fearth7050171",{"doi":700,"openalex_id":702,"authors":703,"venue":657,"cited_by_count":90,"oa_url":654,"card":725,"direction":106,"ingested_from":107},"W7222066993",[704,707,710,713,716,719,722],{"name":705,"orcid":706},"Nurgul Aitekeyeva","https:\u002F\u002Forcid.org\u002F0000-0003-3619-7362",{"name":708,"orcid":709},"Asset Yegizbayeva","https:\u002F\u002Forcid.org\u002F0000-0003-2114-8365",{"name":711,"orcid":712},"Nurlan Bekmukhamedov","https:\u002F\u002Forcid.org\u002F0000-0002-3157-7705",{"name":714,"orcid":715},"Kristina Konstantinova","https:\u002F\u002Forcid.org\u002F0009-0004-0212-5656",{"name":717,"orcid":718},"Kudaibergen Kyrgyzbay","https:\u002F\u002Forcid.org\u002F0000-0002-4279-6436",{"name":720,"orcid":721},"Nurdaulet B. Zhumabay","https:\u002F\u002Forcid.org\u002F0009-0004-2476-6526",{"name":723,"orcid":724},"Nurlan Balgabayev","https:\u002F\u002Forcid.org\u002F0000-0001-8127-7981",{"tldr":726,"method":727,"finding":728,"direction":106,"opportunity":729},"用遥感、GIS与AHP评估哈萨克斯坦额尔齐斯流域灌溉开发的土地适宜性。","遥感、GIS与AHP加权叠加，采用坡度、NDVI、土地利用和土壤质地四因子。","约53%流域属高或较高适宜等级，集中在巴甫洛达尔与阿拜地区。","可结合水资源可用性与灌溉基础设施约束，开展适宜区开发可行性的多尺度综合评估。","2026-10-16T23:30:26.892701Z",{"id":732,"title":733,"url":734,"summary":735,"summary_zh":736,"content":17,"source_name":737,"source_url":734,"published_at":738,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":7,"score_detail":739,"sources":742,"tags":744,"primary_topic":17,"secondary_topics":747,"classification":748,"search_phrases":772,"slug":775,"view_count":82,"doi":776,"paper":777,"created_at":805},4902,"Delineation of groundwater potential zones in Chalan Beel (inland wetland) for sustainable ecosystem in Lower Atrai River Basin NW Bangladesh","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44288-026-00768-z","Groundwater plays a critical role in sustaining the ecological integrity and water security of the Chalan Beel, the largest inland wetland (5097 km2) in the Lower Atrai River Basin of northwestern Bangladesh. This study delineates groundwater potential zones (GWPZs) using an integrated Geographic Information System (GIS), Remote Sensing (RS), and Analytical Hierarchy Process (AHP) approach. Seventeen hydrogeological, topographic, climatic, and environmental thematic layers, including rainfall, soil type, soil permeability, groundwater level, aquifer depth, land use\u002Fland cover, geomorphology, drainage density, NDVI, and NDWI, were analyzed to evaluate groundwater recharge and storage potential. The AHP results indicate that rainfall (20%), soil type (16%), and soil permeability (13%) are the most influential factors controlling groundwater occurrence and recharge. The generated GWPZ map classified the study area into three categories: very high (65 km2, 1%), medium (3933 km2, 77%), and low (1099 km2, 22%) potential zones. Temporal NDVI analysis (1990–2024) revealed substantial changes in vegetation and moisture conditions, with the moderate NDVI class increasing from 45 to 67%, indicating improved vegetation cover and its strong association with groundwater recharge potential. The identified high- and moderate-potential zones provide important information for groundwater development, irrigation planning, and ecosystem conservation. The study offers a scientific basis for sustainable groundwater-dependent ecosystem (SGDE) management and supports informed decision-making for water-resource planning under increasing climatic variability and anthropogenic pressures in northwestern Bangladesh.","地下水在维持孟加拉国西北部阿特拉伊河下游流域最大内陆湿地——查兰比尔湿地（5097平方公里）的生态完整性和水安全方面发挥着关键作用。本研究采用地理信息系统（GIS）、遥感（RS）和层次分析法（AHP）相结合的综合方法，圈定地下水潜力区（GWPZs）。通过分析十七个水文地质、地形、气候和环境专题图层，包括降雨量、土壤类型、土壤渗透性、地下水位、含水层深度、土地利用\u002F土地覆盖、地貌、河网密度、归一化植被指数（NDVI）和归一化水体指数（NDWI），评估地下水补给和储存潜力。层次分析法结果表明，降雨量（20%）、土壤类型（16%）和土壤渗透性（13%）是控制地下水赋存和补给的最主要因素。生成的地下水潜力区图将研究区划分为三类：极高潜力区（65平方公里，1%）、中等潜力区（3933平方公里，77%）和低潜力区（1099平方公里，22%）。时序NDVI分析（1990—2024年）揭示了植被和湿度条件的显著变化，中等NDVI等级从45%增至67%，表明植被覆盖改善及其与地下水补给潜力的密切关联。所识别的高潜力和中等潜力区为地下水开发、灌溉规划和生态系统保护提供了重要信息。本研究为可持续地下水依赖型生态系统（SGDE）管理提供了科学依据，并为孟加拉国西北部在气候变率加剧和人为压力增大背景下的水资源规划提供了知情决策支持。","Discover Geoscience","2026-10-12T00:00:00Z",{"impact":25,"substance":740,"depth":120,"authority":660,"freshness":25,"relevant":8,"comment":741},21,"该研究运用GIS、遥感和AHP方法评估孟加拉国湿地地下水潜力，方法新颖、数据详实，对农业水资源管理和生态保护有参考价值，但地域性较强，影响范围有限。",[743],{"name":737,"url":734},[665,457,4,745,746],"地下水潜力","湿地生态",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":749},{"candidates":750,"agricultural_evidence":22,"reason":284},[751,756,760,764,768],{"code":74,"score":752,"supported":52,"title":753,"abstract":754,"tags":755},11,[],[78,477,674],[745,665],{"code":39,"score":21,"supported":52,"title":757,"abstract":758,"tags":759},[],[55,4,56],[4],{"code":59,"score":60,"supported":52,"title":761,"abstract":762,"tags":763},[],[34,63],[457],{"code":66,"score":67,"supported":52,"title":765,"abstract":766,"tags":767},[],[70,71],[],{"code":81,"score":8,"supported":22,"title":769,"abstract":770,"tags":771},[],[],[746],[773,774],"Chalan Beel 湿地 地下水","孟加拉国 地下水潜力 遥感","ChalanBeel湿地地下水-4902","10.1007\u002Fs44288-026-00768-z",{"doi":776,"openalex_id":778,"authors":779,"venue":737,"cited_by_count":90,"oa_url":799,"card":800,"direction":106,"ingested_from":107},"W7221572372",[780,782,785,788,791,793,795,797],{"name":781,"orcid":17},"Wahedul Alam",{"name":783,"orcid":784},"Iftekharul Islam","https:\u002F\u002Forcid.org\u002F0000-0002-8025-5729",{"name":786,"orcid":787},"Chowdhury Sarwar Jahan","https:\u002F\u002Forcid.org\u002F0009-0008-1316-4684",{"name":789,"orcid":790},"Md. Nahid Hassan","https:\u002F\u002Forcid.org\u002F0009-0000-9210-383X",{"name":792,"orcid":17},"Mostofa Kamal",{"name":794,"orcid":17},"Fayed Islam Tishad",{"name":796,"orcid":17},"Quamrul Hasan Mazumder",{"name":798,"orcid":17},"Md. Golam Mostafa","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44288-026-00768-z.pdf",{"tldr":801,"method":802,"finding":803,"direction":106,"opportunity":804},"用GIS、遥感和AHP划分孟加拉Chalan Beel湿地地下水潜力区，支持可持续生态系统管理。","集成GIS、RS与AHP，分析17个水文地质、地形、气候和环境图层。","降雨、土壤类型和渗透性最关键；高潜力区仅1%，中潜力区占77%。","可结合时序遥感与机器学习提升GWPZ动态制图精度，并耦合灌溉与生态需水决策。","2026-10-14T23:30:30.477606Z",{"id":807,"title":808,"url":809,"summary":810,"summary_zh":811,"content":17,"source_name":812,"source_url":809,"published_at":738,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":117,"score_detail":813,"sources":815,"tags":817,"primary_topic":17,"secondary_topics":820,"classification":821,"search_phrases":837,"slug":840,"view_count":90,"doi":841,"paper":842,"created_at":857},4899,"Groundwater potential zoning in the Grande River Basin: A semi-arid region of Northeast Brazil","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10040-026-03188-y","Abstract Seasonal water scarcity in western Bahia, Brazil, has led to increased dependence on groundwater resources; however, basin-scale hydrogeological measurements remain insufficient for preliminary assessments. This study presents a geographic information system-based groundwater potential map for the Grande River Hydrographic Basin (GRHB), where groundwater potential is defined as a relative index reflecting conditions favorable for recharge and subsurface storage, rather than a direct measure of aquifer productivity. Ten hydrogeological and terrain proxy layers, derived from existing datasets and remote sensing, were standardized and integrated using an analytic hierarchy process weighting scheme and a weighted linear combination. The resulting index was classified into five groundwater potential categories. The very high- and high-potential classes account for 48.08 and 25.41% of the basin, respectively, while the moderate class accounts for 19.90%, and the low- and very low-potential classes together comprise 6.59%. Spatial association with available well locations was evaluated using receiver operating characteristic analysis and the area under the curve, which yielded a value of 0.821, indicating that wells are more frequently located in areas with higher index values. Additionally, a groundwater abstraction-pressure proxy, derived from wells with reported daily abstraction volumes, was used to identify potential stress areas where high favorability coincides with concentrated abstraction activities. These outputs serve as a first-order screening tool to guide field verification, monitoring, and targeted data acquisition across the basin.","摘要 巴西巴伊亚州西部的季节性缺水导致对地下水资源的依赖日益增加；然而，流域尺度的水文地质测量仍不足以支持初步评估。本研究提出了大河流域水文流域（GRHB）基于地理信息系统的地下水潜力图，其中地下水潜力被定义为一个相对指数，反映有利于补给和地下储存的条件，而非含水层生产能力的直接度量。从现有数据集和遥感数据中提取的十个水文地质和地形代理图层，采用层次分析法加权方案和加权线性组合进行了标准化和集成。所得指数被划分为五个地下水潜力类别。极高和高潜力类别分别占流域的48.08%和25.41%，中等类别占19.90%，低和极低潜力类别合计占6.59%。利用受试者工作特征分析和曲线下面积评估了与现有井位的空间关联性，所得值为0.821，表明水井更频繁地分布于指数值较高的区域。此外，利用从报告日开采量的水井中得出的地下水开采压力代理指标，识别了高适宜性与开采活动集中相重合的潜在压力区域。这些成果可作为初步筛选工具，用于指导全流域的实地验证、监测和针对性数据采集。","Hydrogeology Journal",{"impact":25,"substance":452,"depth":26,"authority":27,"freshness":25,"relevant":8,"comment":814},"方法扎实、结论可靠的水文地质论文，但属巴西区域研究，与国内三农信息化关联较弱，公共价值有限。",[816],{"name":812,"url":809},[34,665,4,818,819],"地下水","巴西农业",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":822},{"candidates":823,"agricultural_evidence":22,"reason":284},[824,828,832],{"code":59,"score":60,"supported":52,"title":825,"abstract":826,"tags":827},[],[34,63],[34],{"code":39,"score":60,"supported":52,"title":829,"abstract":830,"tags":831},[],[55,56],[4],{"code":74,"score":833,"supported":52,"title":834,"abstract":835,"tags":836},5,[],[477],[818,665],[838,839],"巴西 Bahia 地下水潜力","水资源管理 巴西农业 地下水 遥感","巴西Bahia地下水潜力-4899","10.1007\u002Fs10040-026-03188-y",{"doi":841,"openalex_id":843,"authors":844,"venue":812,"cited_by_count":90,"oa_url":851,"card":852,"direction":106,"ingested_from":107},"W7221527317",[845,848],{"name":846,"orcid":847},"Thyago Anthony Soares Lima","https:\u002F\u002Forcid.org\u002F0000-0002-4607-2953",{"name":849,"orcid":850},"Paulo de Tarso Amorim Castro","https:\u002F\u002Forcid.org\u002F0000-0002-7667-0161","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs10040-026-03188-y.pdf",{"tldr":853,"method":854,"finding":855,"direction":106,"opportunity":856},"基于GIS与AHP为巴西Grande河流域绘制地下水潜力分区图，并识别开采压力区。","GIS多图层叠加、AHP加权线性组合、ROC\u002FAUC验证，使用遥感与现有井数据。","高与极高潜力区占流域73.49%，AUC达0.821，井位与高潜力区空间吻合。","可结合遥感蒸散发与作物需水，将地下水潜力图与灌溉用水动态耦合，评估农业开采可持续性。","2026-10-14T23:30:28.775390Z",{"id":859,"title":860,"url":861,"summary":862,"summary_zh":863,"content":17,"source_name":864,"source_url":861,"published_at":865,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":866,"score_detail":867,"sources":869,"tags":871,"primary_topic":17,"secondary_topics":875,"classification":876,"search_phrases":898,"slug":901,"view_count":8,"doi":902,"paper":903,"created_at":921},4895,"Advancing Micro-Ecotone Mapping Using UAV Photogrammetry and GIS","https:\u002F\u002Fdoi.org\u002F10.64229\u002Fzkxf5z57","Ecotones are transitional boundaries between ecosystems and essential to regulating biodiversity and ecological processes. Although ecotones are often wider transition zones like aquatic-terrestrial boundaries, they can happen at fine spatial scales (micro-ecotones) and occur over only a few meters or even centimeters. In the past, ecotones have been examined using one-dimensional transects or coarsely resolved remote sensing data for analysis. However, such methods have been too coarse to detect the fine-scale spatial heterogeneity of micro-ecotones. This work develops a geospatial framework to map fine-scale aquatic-terrestrial micro-ecotones at Jahangirnagar University, Bangladesh, utilizing high-resolution unmanned aerial vehicle (UAV) photogrammetry integrated with geographic information systems. High-resolution RGB imagery was obtained using a DJI Mavic Pro and at a height of 200 ft, producing a 3 cm vertical accuracy. Object-based image classification was applied in ArcGIS Pro using support vector machine classifiers, spectral indices, textural measures, and structural features derived from digital elevation model and canopy models to delineate micro-ecotones. The accuracy assessment confirmed that a high degree of accuracy (96.20%, Kappa coefficient- 0.9584) exists between the orthomosaic and classified image. The data analysis revealed a specific spatial pattern in micro-ecotone distribution, with a significant decrease in micro-ecotone density with increasing elevation. In addition, Spearman correlation analyses clearly revealed a strong negative relationship (–0.971) between elevation and micro-ecotone occurrence, confirming that micro-relief features and water proximity are key factors that regulate micro-ecotone occurrence. The combination of UAV imagery, OBIC, and field verification can be used for micro-ecotone configuration and vegetation distribution.","生态交错带是生态系统之间的过渡边界，对调节生物多样性和生态过程至关重要。尽管生态交错带通常是较宽的过渡区域，如水陆交界带，但它们也可以出现在精细的空间尺度上（微观生态交错带），仅跨越几米甚至几厘米。过去，生态交错带通常采用一维样带或粗分辨率遥感数据进行研究分析。然而，这些方法过于粗糙，难以探测微观生态交错带的精细空间异质性。本研究开发了一个地理空间框架，利用高分辨率无人机（UAV）摄影测量技术并结合地理信息系统，对孟加拉国贾汉吉尔纳加尔大学的水陆微观生态交错带进行精细尺度制图。使用DJI Mavic Pro在200英尺高度获取高分辨率RGB影像，垂直精度达到3厘米。在ArcGIS Pro中应用基于对象的图像分类方法，采用支持向量机分类器，结合光谱指数、纹理特征以及由数字高程模型和冠层模型衍生的结构特征来 delineate 微观生态交错带。精度评估证实，正射影像与分类图像之间具有高度一致性（总体精度96.20%，Kappa系数0.9584）。数据分析揭示了微观生态交错带分布的特定空间格局，即微观生态交错带密度随海拔升高而显著降低。此外，Spearman相关分析清晰地揭示了海拔与微观生态交错带出现之间存在强负相关关系（–0.971），证实微地形特征和水体邻近性是调控微观生态交错带出现的关键因素。无人机影像、基于对象的图像分类与野外验证相结合的方法可用于微观生态交错带构型与植被分布研究。","Journal of Environmental Ecology","2026-10-13T00:00:00Z",72,{"impact":28,"substance":740,"depth":120,"authority":660,"freshness":29,"relevant":8,"comment":868},"该研究提出无人机摄影测量与GIS结合的微生态交错带精细制图框架，方法新颖、精度高，对农业生态监测有参考价值，但属国际案例、影响范围有限。",[870],{"name":864,"url":861},[872,34,873,4,874],"智慧农业","无人机遥感","生态制图",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":877},{"candidates":878,"agricultural_evidence":22,"reason":284},[879,883,887,893],{"code":39,"score":191,"supported":52,"title":880,"abstract":881,"tags":882},[4],[55,56],[4],{"code":59,"score":25,"supported":52,"title":884,"abstract":885,"tags":886},[],[34,63],[873,34],{"code":81,"score":67,"supported":52,"title":888,"abstract":889,"tags":892},[],[890,891],"生物多样性","biodiversity",[],{"code":894,"score":8,"supported":22,"title":895,"abstract":896,"tags":897},"I1",[],[],[872],[899,900],"无人机遥感 智慧农业 生态制图 遥感","无人机遥感 智慧农业","无人机遥感智慧农业生态制图遥感-4895","10.64229\u002Fzkxf5z57",{"doi":902,"openalex_id":904,"authors":905,"venue":864,"cited_by_count":90,"oa_url":915,"card":916,"direction":106,"ingested_from":107},"W7221666940",[906,908,910,912,914],{"name":907,"orcid":17},"Bibi Hafsa",{"name":909,"orcid":17},"Sifatul Hoque Siam",{"name":911,"orcid":17},"Mahib Reza",{"name":913,"orcid":17},"Ripa Akter",{"name":383,"orcid":384},"https:\u002F\u002Fjee.cultechpub.com\u002Findex.php\u002Fjee\u002Farticle\u002Fdownload\u002F60\u002F21",{"tldr":917,"method":918,"finding":919,"direction":106,"opportunity":920},"用无人机摄影测量与GIS绘制高精度水陆微型生态过渡带分布图。","DJI Mavic Pro 200英尺RGB影像，面向对象分类+SVM，结合DE","分类精度96.20%，微型生态过渡带密度随海拔升高显著下降，与海拔呈强负相关（-0.971）。","可将该高分辨率微型生态过渡带制图框架迁移至农田-水体交错带，研究其与作物长势及生物多样性的关系。","2026-10-14T23:30:26.895895Z",{"id":923,"title":924,"url":925,"summary":926,"summary_zh":927,"content":17,"source_name":928,"source_url":925,"published_at":929,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":7,"score_detail":930,"sources":932,"tags":934,"primary_topic":936,"secondary_topics":937,"classification":943,"search_phrases":967,"slug":970,"view_count":90,"doi":971,"paper":972,"created_at":987},4753,"Mapping groundwater potential zones using GIS, remote sensing and analytical hierarchy process (AHP) in Pader and Kitgum Districts, Uganda","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs43621-026-04943-7","Groundwater is a crucial source of freshwater in semi-arid regions, particularly in water-stressed areas, such as northern Uganda, where the surface water is scarce and unreliable precipitation patterns changes. This province lacks sufficient clean water for human consumption and only 20% of the water for agriculture extracted from the ground due to inaccessibility and insufficient information regarding the groundwater. With regard to these difficulties in water that are faced by the local communities, it has not been yet studied the distribution of groundwater in Kitgum and Pader districts. Therefore, the result of this research contributes preliminary groundwater investigation for contacting this indispensable source of water. The study employed a geospatial approach integrated with multi-criteria analysis to identify groundwater potential zones in Kitgum and Pader districts of Acholi subregion. The Utilization of Geographic Information Systems (GIS), remote sensing, and the Analytic Hierarchy Process (AHP) and six thematic layers; rainfall, drainage density, slope, soil type, geology, and land use\u002Fland cover were selected based on their hydrogeological influence and the accessibility of the data. After standardizing, and assigning normalized weights,a weighted overlay analysis in ArcGIS Pro version 3.1.0 was used to synthesize these layers into a comprehensive groundwater potential zonation map. The result categorized the study area into five zones; very low, low, medium, high, and very high potential. The analysis revealed that Kitgum District is predominantly characterized by very low to low groundwater potential zones of 67.24% when it is combined both, constrained by factors such as higher drainage density, and steeper slopes. Conversely, Pader District showed favorable conditions, with 85.5% of its area classified as high to very high groundwater potential, attributed to gentle slopes, and higher rainfall, that enhance infiltration capacity. Validation against yield data from 18 existing boreholes demonstrated a 75.0% alignment between the model and actual well performance, confirming the model’s reliability at acceptable result. This study demonstrated the effectiveness of GIS-based and AHP as a cost-effective tool for preliminary groundwater exploration in data-scarce environments. The resulting groundwater potential map provides a vital scientific foundation for sustainable water resource management, enabling targeted borehole siting, informed aquifer development, and resilience-building strategies to enhance water security for communities and livelihoods in the Acholi sub-region.","地下水是半干旱地区重要的淡水来源，尤其是在乌干达北部等水资源紧张地区，那里地表水稀缺且降水模式变化不可靠。该地区缺乏足够的清洁饮用水供人类消费，由于地下水难以获取且信息不足，仅有20%的农业用水来自地下开采。鉴于当地社区面临这些水资源困难，基特古姆和帕德尔地区的地下水分布尚未得到研究。因此，本研究结果为接触这一不可或缺的水源提供了初步的地下水调查。本研究采用地理空间方法与多准则分析相结合，识别阿乔利次区域基特古姆和帕德尔地区的地下水潜力区。利用地理信息系统（GIS）、遥感技术和层次分析法（AHP），基于其水文地质影响和数据可获取性，选取了六个主题图层：降雨量、河网密度、坡度、土壤类型、地质和土地利用\u002F土地覆盖。经过标准化和归一化权重赋值后，使用ArcGIS Pro 3.1.0版本中的加权叠加分析将这些图层综合成一张全面的地下水潜力分区图。结果将研究区划分为五个区域：极低、低、中等、高和极高潜力。分析表明，基特古姆区主要以极低至低地下水潜力区为主，两者合计占67.24%，受较高河网密度和较陡坡度等因素制约。相反，帕德尔区表现出有利条件，其85.5%的面积被归类为高至极高地下水潜力，这归因于平缓的坡度和较高的降雨量，增强了入渗能力。利用18口现有钻孔的出水量数据进行验证，模型与实际井表现之间的一致率达到75.0%，证实了模型在可接受结果范围内的可靠性。本研究证明了基于GIS和AHP的方法作为数据稀缺环境中初步地下水勘探的成本效益工具的有效性。所生成的地下水潜力图为可持续水资源管理提供了重要的科学基础，有助于有针对性地选址钻孔，为知情决策提供依据。","Discover Sustainability","2026-10-10T00:00:00Z",{"impact":25,"substance":119,"depth":120,"authority":660,"freshness":29,"relevant":8,"comment":931},"基于GIS、遥感与AHP的乌干达北部地下水潜力制图研究，方法成熟、验证可靠，对缺水地区农业水资源规划有参考价值，但属区域性初步研究，公共影响有限。",[933],{"name":928,"url":925},[34,665,4,745,935],"乌干达农业",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[938,939],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"code":74,"slug":674,"name":940,"path":941,"parent_code":942},"水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",{"status":46,"locked":22,"version":47,"method":48,"evidence":944},{"candidates":945,"agricultural_evidence":52},[946,950,954,959,963],{"code":39,"score":26,"supported":52,"title":947,"abstract":948,"tags":949},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":951,"abstract":952,"tags":953},[63],[34,63],[34],{"code":74,"score":25,"supported":52,"title":955,"abstract":956,"tags":958},[],[477,957],"water resource",[745,665],{"code":66,"score":67,"supported":52,"title":960,"abstract":961,"tags":962},[],[70,71],[],{"code":480,"score":75,"supported":52,"title":964,"abstract":965,"tags":966},[],[483],[],[968,969],"乌干达 Kitgum Pader 地下水","GIS AHP 地下水潜力","乌干达KitgumPader地下水-4753","10.1007\u002Fs43621-026-04943-7",{"doi":971,"openalex_id":973,"authors":974,"venue":928,"cited_by_count":90,"oa_url":925,"card":982,"direction":106,"ingested_from":107},"W7221339030",[975,978,980],{"name":976,"orcid":977},"Ahmed Abdirizak Dirie","https:\u002F\u002Forcid.org\u002F0009-0002-8109-0724",{"name":979,"orcid":17},"Abdulkadir Ahmed Mohamed",{"name":981,"orcid":17},"Ambiga Kannapiran",{"tldr":983,"method":984,"finding":985,"direction":106,"opportunity":986},"用GIS、遥感和AHP制图评估乌干达两区地下水潜力并验证。","GIS与遥感结合AHP，加权叠加6个主题图层，用18口井数据验证。","Kitgum区67.24%为低潜力，Pader区85.5%为高潜力，模型与井数据吻合75%。","可将该地下水潜力制图方法迁移到其他数据稀缺区，并结合农业灌溉需求优化井位。","2026-10-12T23:30:24.761508Z",{"id":989,"title":990,"url":991,"summary":992,"summary_zh":993,"content":17,"source_name":994,"source_url":991,"published_at":929,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":90,"score_detail":995,"sources":997,"tags":999,"primary_topic":17,"secondary_topics":1003,"classification":1004,"search_phrases":1020,"slug":1023,"view_count":8,"doi":1024,"paper":1025,"created_at":1038},4751,"A DISASTER RISK PREPAREDNESS MANAGEMENT PLAN FOR MARKETS IN MUBI TOWN, ADAMAWA STATE, NIGERIA","https:\u002F\u002Fdoi.org\u002F10.70382\u002Fhijiras.v013i2.088","The study evaluates disaster risk preparedness in major commercial markets within Mubi Town, Adamawa State, Nigeria, with a view to identifying hazard hotspots, structural deficiencies, and formulating a proactive, GIS-based disaster risk management plan. Major markets in developing urban centres face recurrent catastrophes, notably destructive fire outbreaks, exacerbated by high stall densities, combustible building materials, infrastructural deficits, and reactive emergency administration. Data for the study were obtained through both primary and secondary sources, comprising Global Positioning System (GPS) field coordinates of market boundaries, stall footprints, water sources, transformers, and hazardous activity points, paired with high-resolution georeferenced satellite imagery, physical lane width measurements, structured questionnaires administered to 384 market stakeholders, and document review of historical fire records. The data collected were subjected to descriptive statistical analysis and advanced spatial analysis within an ArcGIS Pro environment, utilizing Buffer Analysis, Network Analysis, and Multi-Criteria Decision Analysis (MCDA) via Weighted Overlay. The empirical findings indicate that 74.2% of market stalls are constructed from highly combustible temporary materials (timber, thatch, and corrugated iron sheets), while 68.5% of internal circulation lanes measure less than 2.0 metres in width, severely impeding fire appliance navigability. Critical firefighting infrastructure is virtually non-existent; the entire metropolitan area lacks functional municipal fire hydrants and relies on a severely under-resourced fire station with only one functional water tender. Spatial buffer analysis revealed that 63.8% of commercial stalls are situated within high-hazard impact zones (\u003C20 m) of unregulated fuel and liquefied petroleum gas (LPG) vendors. Furthermore, composite multi-criteria risk mapping established that 58.4% of the aggregate market acreage falls within the \"High\" and \"Extreme\" vulnerability classes. Stakeholder evaluation of institutional coordination yielded a grand mean score of 1.74 on a 4-point scale, demonstrating severe institutional fragmentation among local government authorities, emergency agencies, and market associations. The study recommends the official integration of market management committees into municipal disaster risk governance, the immediate installation of dedicated pressurized fire hydrants, statutory enforcement of a minimum 3.5-metre emergency lane clearance, strict spatial zoning of hazardous commodity vendors, and the institutionalization of a GIS-based spatial decision support tool for proactive disaster mitigation.","本研究评估了尼日利亚阿达马瓦州穆比镇主要商业市场的灾害风险防范情况，旨在识别灾害热点、结构性缺陷，并制定基于地理信息系统（GIS）的前瞻性灾害风险管理方案。发展中城市中心的主要市场面临反复发生的灾难，尤其是破坏性火灾，其加剧因素包括摊位密度高、建筑材料可燃、基础设施不足以及应急管理被动。研究数据通过一手和二手来源获取，包括市场边界、摊位占地、水源、变压器和危险活动点的全球定位系统（GPS）实地坐标，并结合高分辨率地理参照卫星影像、物理通道宽度测量、对384名市场利益相关者进行的结构化问卷调查，以及历史火灾记录的文件审查。所收集数据在ArcGIS Pro环境中进行了描述性统计分析和高级空间分析，运用了缓冲区分析、网络分析和通过加权叠加实现的多准则决策分析（MCDA）。实证结果表明，74.2%的市场摊位由高度可燃的临时材料（木材、茅草和波纹铁皮）建造，而68.5%的内部流通通道宽度不足2.0米，严重阻碍了消防车辆通行。关键消防基础设施几乎不存在；整个都市区缺乏功能正常的市政消防栓，仅依赖一个资源严重不足、只有一辆可用水罐车的消防站。空间缓冲区分析显示，63.8%的商业摊位位于无监管燃料和液化石油气（LPG）销售商的高危影响区（\u003C20米）内。此外，综合多准则风险制图确定，市场总面积的58.4%属于“高”和“极高”脆弱性等级。利益相关者对机构协调的评价在4分制量表上总平均得分为1.74，表明地方政府当局、应急机构和市场协会之间存在严重的机构碎片化。研究建议将市场管理委员会正式纳入市政灾害风险治理体系，立即安装专用加压消防栓，并依法强制执行","International Journal of Innovation Research and Advanced Studies",{"impact":90,"substance":90,"depth":90,"authority":90,"freshness":90,"relevant":90,"comment":996},"研究尼日利亚市场火灾风险与GIS防灾规划，属城市应急管理范畴，与三农、农业信息化主题无关，不建议进入每日精选。",[998],{"name":994,"url":991},[1000,1001,4,1002],"防灾减灾","应急管理","市场安全",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1005},{"candidates":1006,"agricultural_evidence":22,"reason":284},[1007,1012,1016],{"code":39,"score":21,"supported":52,"title":1008,"abstract":1009,"tags":1011},[],[55,1010,4,679],"空间分析",[4],{"code":138,"score":75,"supported":52,"title":1013,"abstract":1014,"tags":1015},[],[143],[],{"code":480,"score":8,"supported":22,"title":1017,"abstract":1018,"tags":1019},[],[],[1000],[1021,1022],"Mubi 市场 火灾风险","尼日利亚 市场 GIS 防灾","Mubi市场火灾风险-4751","10.70382\u002Fhijiras.v013i2.088",{"doi":1024,"openalex_id":1026,"authors":1027,"venue":994,"cited_by_count":90,"oa_url":1032,"card":1033,"direction":106,"ingested_from":107},"W7221329767",[1028,1030],{"name":1029,"orcid":17},"Yakubu Usman Mohammed",{"name":1031,"orcid":17},"NUWARI ATI BATHON","https:\u002F\u002Fharvardpublications.com\u002Fhijiras\u002Farticle\u002Fdownload\u002F777\u002F716",{"tldr":1034,"method":1035,"finding":1036,"direction":314,"opportunity":1037},"评估尼日利亚穆比镇市场火灾风险，用GIS制定防灾准备管理规划。","GPS测绘、卫星影像、384份问卷与ArcGIS空间分析（缓冲、网络、加权叠加M","74.2%摊位为易燃材料，68.5%通道不足2米，58.4%市场面积属高至极高脆弱等级。","可将该GIS-MCDA框架移植到农产品批发市场与乡村集市，结合物联网传感实现火灾实时预警。","2026-10-12T23:30:24.642855Z",{"id":1040,"title":1041,"url":1042,"summary":1043,"summary_zh":1044,"content":17,"source_name":1045,"source_url":1042,"published_at":1046,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":117,"score_detail":1047,"sources":1049,"tags":1051,"primary_topic":1054,"secondary_topics":1055,"classification":1056,"search_phrases":1071,"slug":1074,"view_count":82,"doi":1075,"paper":1076,"created_at":1098},4596,"Spatio-temporal analysis of land use\u002Fland cover (LULC) changes using GIS techniques in Upper Bhavani River Basin, Nilgiri Hills, India","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44274-026-00915-w","The study investigates the land use and land cover (LULC) changes in Upper Bhavani River basin of the Western Ghats over the past four decades (1989–2019) using remote sensing (RS) and geographic information system (GIS) techniques. It also explores the correlation between LULC changes and population growth during this period. The study highlights the importance of mapping and monitoring LULC changes in developing better management strategies for the sustainable development of natural resources. The iterative self-organising data analysis technique was used for unsupervised classification to create LULC maps of the riverbasin.The study identified and categorised seven LULC categories, namely water bodies, deciduous forest, evergreen forest, agriculture, plantation, barren land, and settlement. The results of the study showed a complex series of modifications in the LULC in the study basin over the past forty years due to policy changes and conventional agroforestry systems. The study revealed a decrease in agriculture, evergreen forest, and deciduous forest by − 6.88%, − 31.42%, and − 9.88%, respectively, while water bodies, plantations, barren land, and settlement area increased by 7.06%, 17.64%, 13.29%, and 10.23%, respectively. The findings of the study provide insights into specific changes in LULC and help predict which land uses will be impacted in the future. The overall accuracy of the classification was0.73.Overall, this study emphasised the importance of monitoring and mapping LULC changes using RS and GIS techniques to develop better management strategies for the sustainable development of natural resources. The findings of the study were useful for policymakers, land-use planners, and conservationists in developing effective strategies to maintain the ecological balance of the Western Ghats.","本研究利用遥感（RS）和地理信息系统（GIS）技术，探讨了过去四十年（1989—2019年）西高止山脉上巴瓦尼河流域的土地利用与土地覆盖（LULC）变化，并分析了该时期LULC变化与人口增长之间的相关性。研究强调了制图和监测LULC变化对于制定自然资源可持续发展管理策略的重要性。采用迭代自组织数据分析技术进行非监督分类，以生成该流域的LULC图。研究识别并划分了七类LULC，分别为水体、落叶林、常绿林、农业、种植园、裸地和居民点。研究结果表明，受政策变化和传统农林业系统的影响，过去四十年研究流域的LULC经历了一系列复杂的改变。研究揭示，农业、常绿林和落叶林分别减少了−6.88%、−31.42%和−9.88%，而水体、种植园、裸地和居民点面积分别增加了7.06%、17.64%、13.29%和10.23%。研究结果揭示了LULC的具体变化，有助于预测未来哪些土地利用类型将受到影响。分类总体精度为0.73。总体而言，本研究强调了利用RS和GIS技术监测和制图LULC变化对于制定自然资源可持续发展管理策略的重要性。研究结果有助于政策制定者、土地利用规划者和保护主义者制定有效策略，以维持西高止山脉的生态平衡。","Discover Environment","2026-10-08T00:00:00Z",{"impact":28,"substance":119,"depth":120,"authority":660,"freshness":25,"relevant":8,"comment":1048},"基于遥感与GIS的四十年土地利用变化实证研究，数据翔实、结论可靠，对流域生态管理与土地规划有参考价值，但属区域案例研究，公共影响层级有限。",[1050],{"name":1045,"url":1042},[457,35,4,1052,1053],"流域治理","西高止山",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[],{"status":46,"locked":22,"version":47,"method":48,"evidence":1057},{"candidates":1058,"agricultural_evidence":52},[1059,1063,1067],{"code":39,"score":26,"supported":52,"title":1060,"abstract":1061,"tags":1062},[4],[55,4,56],[4],{"code":59,"score":60,"supported":52,"title":1064,"abstract":1065,"tags":1066},[],[34,63],[457],{"code":81,"score":8,"supported":22,"title":1068,"abstract":1069,"tags":1070},[],[],[35],[1072,1073],"土地利用 流域治理 西高止山 遥感监测","土地利用 流域治理","土地利用流域治理西高止山遥感监测-4596","10.1007\u002Fs44274-026-00915-w",{"doi":1075,"openalex_id":1077,"authors":1078,"venue":1045,"cited_by_count":90,"oa_url":1092,"card":1093,"direction":106,"ingested_from":107},"W7221028855",[1079,1081,1084,1086,1088,1090],{"name":1080,"orcid":17},"Sapna Kinattinkara",{"name":1082,"orcid":1083},"Thangavelu Arumugam","https:\u002F\u002Forcid.org\u002F0000-0002-2984-283X",{"name":1085,"orcid":17},"Karpagamani Vellingiri",{"name":1087,"orcid":17},"Manoj Kumar Patley",{"name":1089,"orcid":17},"Manimaran Arumugam",{"name":1091,"orcid":17},"Nigatu Wondrade","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44274-026-00915-w.pdf",{"tldr":1094,"method":1095,"finding":1096,"direction":106,"opportunity":1097},"用遥感与GIS分析印度上巴瓦尼河流域1989-2019年土地利用变化及其与人口增长的关系。","遥感与GIS、ISODATA非监督分类，划分七类LULC，总体精度0.73。","农业、常绿林和落叶林分别减少6.88%、31.42%、9.88%，水体、种植园、裸地和居民地增加。","可结合高精度分类与人口、政策数据，构建LULC变化驱动力模型并预测未来情景。","2026-10-10T23:30:30.955766Z",{"id":1100,"title":1101,"url":1102,"summary":1103,"summary_zh":1104,"content":17,"source_name":1105,"source_url":1102,"published_at":1046,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":1106,"score_detail":1107,"sources":1109,"tags":1111,"primary_topic":17,"secondary_topics":1115,"classification":1116,"search_phrases":1143,"slug":1146,"view_count":90,"doi":1147,"paper":1148,"created_at":1164},4592,"Desertification Assessment in the Hodna Basin, Algeria using Desertification Degree Index and Geospatial Techniques","https:\u002F\u002Fdoi.org\u002F10.56093\u002Faaz.v65i3.177561","This study assesses desertification in the Hodna Basin, Algeria, using remote sensing and Geographic Information Systems (GIS) through the development of a Desertification Degree Index (DDI) based on feature-space analysis. Landsat 9 imagery was used to derive four spectral indices: the Normalized Difference Vegetation Index (NDVI), surface albedo, the Modified Soil-Adjusted Vegetation Index (MSAVI), and the Topsoil Grain Size Index (TGSI). Five feature-space combinations were evaluated, with the Albedo-NDVI and TGSI-NDVI models exhibiting the strongest statistically significant negative correlations. These two models were subsequently used for DDI generation and comparison. The Albedo-NDVI model achieved the highest performance, with an Overall Accuracy of 91.9% and a Kappa coefficient of 0.89, substantially outperforming the TGSI-NDVI model. The resulting desertification map indicates that approximately 65% of the Hodna Basin is affected by high to severe desertification, particularly in the central and southern regions, where prolonged aridity and intensive human activities have accelerated land degradation. In contrast, the northern part of the basin exhibits relatively low desertification levels owing to denser vegetation cover and more favorable environmental conditions. These findings demonstrate the robustness of the Albedo-NDVI feature-space model for desertification assessment in arid and semi-arid environments and highlight the value of integrating spectral indices with statistical feature-space analysis. The proposed approach provides a reliable and objective framework for large-scale desertification mapping and offers valuable decision support for soil conservation, ecosystem restoration, and sustainable land management in vulnerable dryland regions.","本研究利用遥感与地理信息系统（GIS），通过构建基于特征空间的荒漠化程度指数（DDI），对阿尔及利亚霍德纳盆地的荒漠化进行了评估。研究采用Landsat 9影像提取了四个光谱指数：归一化差异植被指数（NDVI）、地表反照率、修正土壤调整植被指数（MSAVI）和表土粒度指数（TGSI）。对五种特征空间组合进行了评价，其中反照率-NDVI和TGSI-NDVI模型表现出最强的统计显著负相关。随后，这两个模型被用于DDI生成与比较。反照率-NDVI模型取得了最佳性能，总体精度为91.9%，Kappa系数为0.89，显著优于TGSI-NDVI模型。生成的荒漠化图表明，霍德纳盆地约65%的区域受到高度至严重荒漠化的影响，尤其是在中部和南部地区，长期的干旱和密集的人类活动加速了土地退化。相比之下，盆地北部由于植被覆盖较密、环境条件较为有利，荒漠化程度相对较低。这些发现证明了反照率-NDVI特征空间模型在干旱和半干旱环境荒漠化评估中的稳健性，并凸显了将光谱指数与统计特征空间分析相结合的价值。所提出的方法为大规模荒漠化制图提供了可靠且客观的框架，并为脆弱旱地地区的土壤保持、生态系统恢复和可持续土地管理提供了有价值的决策支持。","Annals of Arid Zone",73,{"impact":28,"substance":452,"depth":26,"authority":660,"freshness":25,"relevant":8,"comment":1108},"该研究提出基于Landsat 9与特征空间分析的荒漠化程度指数，方法新颖、精度高，对干旱区土地退化监测与农业可持续发展有参考价值，但属区域性案例研究，影响范围有限。",[1110],{"name":1105,"url":1102},[34,1112,4,1113,1114],"土地退化","植被指数","荒漠化监测",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1117},{"candidates":1118,"agricultural_evidence":22,"reason":284},[1119,1123,1127,1131,1135,1139],{"code":39,"score":21,"supported":52,"title":1120,"abstract":1121,"tags":1122},[],[55,1010,4,56],[4],{"code":59,"score":25,"supported":52,"title":1124,"abstract":1125,"tags":1126},[],[34,63],[1113,34],{"code":66,"score":67,"supported":52,"title":1128,"abstract":1129,"tags":1130},[],[70,71],[],{"code":480,"score":75,"supported":52,"title":1132,"abstract":1133,"tags":1134},[],[483],[],{"code":138,"score":75,"supported":52,"title":1136,"abstract":1137,"tags":1138},[],[143],[],{"code":691,"score":8,"supported":22,"title":1140,"abstract":1141,"tags":1142},[],[],[1112],[1144,1145],"Albedo-NDVI 荒漠化","荒漠化监测 土地退化 植被指数 遥感","Albedo-NDVI荒漠化-4592","10.56093\u002Faaz.v65i3.177561",{"doi":1147,"openalex_id":1149,"authors":1150,"venue":1105,"cited_by_count":90,"oa_url":1158,"card":1159,"direction":106,"ingested_from":107},"W7220932821",[1151,1153,1155],{"name":1152,"orcid":17},"Sami Mekentichi",{"name":1154,"orcid":17},"Salah Abdesselam",{"name":1156,"orcid":1157},"Razika Sahnouni","https:\u002F\u002Forcid.org\u002F0000-0003-4914-6804","http:\u002F\u002Fepubs.icar.org.in\u002Findex.php\u002FAAZ\u002Farticle\u002Fdownload\u002F177561\u002F68055",{"tldr":1160,"method":1161,"finding":1162,"direction":106,"opportunity":1163},"基于Landsat 9与特征空间分析构建荒漠化程度指数，评估阿尔及利亚Hodna盆地荒漠化。","Landsat 9影像提取NDVI、反照率、MSAVI、TGSI，用Albedo","Albedo-NDVI模型精度最高（总体精度91.9%，Kappa 0.89），约65%区域处于高至","可将Albedo-NDVI特征空间模型迁移至其他干旱区，并结合时序影像与人类活动因子做驱动力归因。","2026-10-10T23:30:29.517004Z",{"id":1166,"title":1167,"url":1168,"summary":1169,"summary_zh":1170,"content":17,"source_name":1171,"source_url":1168,"published_at":1172,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":866,"score_detail":1173,"sources":1175,"tags":1177,"primary_topic":1181,"secondary_topics":1182,"classification":1183,"search_phrases":1194,"slug":1197,"view_count":8,"doi":1198,"paper":1199,"created_at":1220},4586,"Advanced Assessment of the Agro-Silvo-Pastoral Coherence in Transboundary Transitional Water Regions","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15101916","Transitional waters play a vital role in the ecological health and sustainability of coastal areas. According to European Union legislation, transitional waters are coastal water bodies influenced by freshwater flows but are partly saline due to their proximity to the sea. This study focuses on agricultural and forestry regions adjacent to transboundary transitional waters—i.e., areas where two or more countries share an estuary, tidal inlet, delta, or lagoon and have a contiguous border in their territorial waters. The objective of the study is to determine the patterns of riparian agroforestry around the transboundary transitional waters in Europe and the dependence of the sustainability of these agro-silvo-pastoral systems under stress on the overall cross-border coherence of the countries sharing these waters. The innovative methodology uses GIS and geostatistical interpretation to quantitatively interpret multi-layered spatial data from remote sensing and other sources. The article’s main finding is that in the direct catchment areas of 12 transboundary transitional waters in three European bioregions—the Baltic Sea, the Adriatic and Black Seas, and the Northeast Atlantic—the Dissimilarity Index values vary from 1.5% to 8.2% in different agroforestry systems.","过渡水域对沿海地区的生态健康与可持续性具有至关重要的作用。根据欧盟立法，过渡水域是受淡水径流影响但因靠近海洋而具有一定盐度的沿海水体。本研究聚焦于毗邻跨界过渡水域的农业与林业区域，即两个或多个国家共享同一河口、潮汐入口、三角洲或潟湖，且其领海边界相连的区域。本研究旨在确定欧洲跨界过渡水域周边河岸农林复合系统的格局，以及这些处于压力下的农林牧系统可持续性对共享这些水域的国家之间整体跨境协调性的依赖程度。该创新性方法采用地理信息系统（GIS）和地统计解译技术，对来自遥感及其他来源的多层空间数据进行定量解译。本文的主要发现是：在欧洲三个生物区——波罗的海、亚得里亚海与黑海以及东北大西洋——的12处跨界过渡水域的直接集水区内，不同农林复合系统的相异指数值在1.5%至8.2%之间变化。","Land","2026-10-09T00:00:00Z",{"impact":28,"substance":740,"depth":120,"authority":660,"freshness":29,"relevant":8,"comment":1174},"方法新颖、数据扎实的欧洲跨境滨海农林牧系统遥感评估论文，对农业空间信息化有参考价值，但属区域案例研究，公共影响有限。",[1176],{"name":1171,"url":1168},[457,1178,1179,4,1180],"跨境流域","农林牧复合系统","滨海湿地",{"code":43,"slug":129,"name":130,"path":131,"parent_code":17},[],{"status":134,"locked":22,"version":47,"method":48,"evidence":1184},{"candidates":1185,"agricultural_evidence":52,"reason":158},[1186,1190],{"code":59,"score":60,"supported":52,"title":1187,"abstract":1188,"tags":1189},[],[34,63],[457],{"code":39,"score":60,"supported":52,"title":1191,"abstract":1192,"tags":1193},[],[55,4],[4],[1195,1196],"欧洲 跨境过渡水域 农林复合","GIS 遥感 农林牧系统 一致性","欧洲跨境过渡水域农林复合-4586","10.3390\u002Fland15101916",{"doi":1198,"openalex_id":1200,"authors":1201,"venue":1171,"cited_by_count":90,"oa_url":1168,"card":1215,"direction":106,"ingested_from":107},"W7221179136",[1202,1204,1206,1209,1212],{"name":1203,"orcid":17},"Aistė Jurkienė",{"name":1205,"orcid":17},"Egidijus Jurkus",{"name":1207,"orcid":1208},"Ramūnas Povilanskas","https:\u002F\u002Forcid.org\u002F0000-0003-0895-3917",{"name":1210,"orcid":1211},"Eduardas Spiriajevas","https:\u002F\u002Forcid.org\u002F0000-0002-4684-5979",{"name":1213,"orcid":1214},"Arvydas Urbis","https:\u002F\u002Forcid.org\u002F0000-0002-9641-9214",{"tldr":1216,"method":1217,"finding":1218,"direction":106,"opportunity":1219},"用GIS与地统计量化欧洲12处跨境过渡水域周边农林牧系统的一致性差异。","GIS与地统计解读遥感等多源多层空间数据，计算相异指数。","三大生物区12处水域集水区农林系统相异指数为1.5%至8.2%。","可拓展跨境流域农林牧系统一致性对生态可持续性的驱动机制与动态监测研究。","2026-10-10T23:30:27.974100Z",{"id":1222,"title":1223,"url":1224,"summary":1225,"summary_zh":1226,"content":17,"source_name":1227,"source_url":1224,"published_at":1172,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":1228,"score_detail":1229,"sources":1231,"tags":1233,"primary_topic":1236,"secondary_topics":1237,"classification":1238,"search_phrases":1257,"slug":1260,"view_count":8,"doi":1261,"paper":1262,"created_at":1287},4585,"Integrated multi-criteria decision analysis and bivariate statistical modeling for landslide susceptibility zonation in the northwestern Ethiopian highlands","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44475-026-00073-w","Landslides represent a critical geo-environmental hazard in the Ethiopian highlands, specifically within the Telemt, Janamora, and Beyeda districts, where they frequently result in fatalities and the destruction of vital infrastructure and agricultural land. This study integrated Geographic Information Systems (GIS) and remote sensing data to perform landslide susceptibility mapping (LSM) using two distinct modeling approaches: the Frequency Ratio (FR) and the Analytical Hierarchy Process (AHP). A total of 140 data points (98 for training (70%) and 42 for testing (30%)) were considered for modeling and validation. Eleven geo-environmental conditioning factors: Slope, rainfall, lithology, density of lineaments, curvature, aspect, normalized difference vegetation index, land use\u002Fland cover, distance to drainage, drainage density, and soil were analyzed to evaluate their influence on landslide occurrence. According to the AHP model, 13.69% and 26.91% of the study area were classified as very high and high susceptibility zones, respectively. In comparison, the FR model identified 12.09% as very high and 23.78% as high susceptibility zones. Both models underscored that steep slopes, porphyritic basalt unit, high lineament density, proximity to drainage systems, and concave terrain curvature are the primary drivers of slope instability. Conversely, gentle slopes, sandstone unit, and dense vegetation cover were strongly associated with low-susceptibility regions. Model performance was validated using the Receiver Operating Characteristic (ROC) curve, yielding an Area Under the Curve (AUC) value of 0.812 for the AHP model and 0.793 for the FR model, alongside a prediction rate AUC value of 77.4% (0.774) for the AHP model and 70.4% for the FR model, confirming the predictive reliability of both methods. These results provide essential geospatial intelligence for policy-makers and stakeholders to guide disaster risk management, sustainable land-use planning, and targeted rehabilitation efforts in the region.","滑坡是埃塞俄比亚高地，特别是Telemt、Janamora和Beyeda地区面临的严重地质环境灾害，频繁造成人员伤亡以及重要基础设施和农田的破坏。本研究综合地理信息系统（GIS）和遥感数据，采用频率比（FR）和层次分析法（AHP）两种不同的建模方法进行滑坡易发性制图（LSM）。建模与验证共考虑了140个数据点（98个用于训练（70%），42个用于测试（30%））。分析了十一个地质环境条件因子：坡度、降雨量、岩性、线理密度、曲率、坡向、归一化植被指数、土地利用\u002F土地覆被、距水系距离、水系密度和土壤，以评估它们对滑坡发生的影响。根据AHP模型，研究区分别有13.69%和26.91%的区域被划分为极高和高易发区。相比之下，FR模型将12.09%的区域划为极高易发区，23.78%划为高易发区。两种模型均强调，陡坡、斑状玄武岩单元、高线理密度、邻近水系以及凹形地形曲率是斜坡失稳的主要驱动因素。相反，缓坡、砂岩单元和茂密植被覆盖与低易发区密切相关。采用受试者工作特征（ROC）曲线对模型性能进行验证，AHP模型的曲线下面积（AUC）值为0.812，FR模型为0.793，同时AHP模型的预测率AUC值为77.4%（0.774），FR模型为70.4%，证实了两种方法的预测可靠性。这些结果为政策制定者和利益相关者提供了重要的地理空间情报，可指导该地区的灾害风险管理、可持续土地利用规划和有针对性的修复工作。","Discover Hazards",64,{"impact":25,"substance":119,"depth":190,"authority":28,"freshness":25,"relevant":8,"comment":1230},"GIS与遥感结合的滑坡易发性制图研究，方法规范、数据扎实，对农业灾害风险管理和土地规划有参考价值，但属区域性案例，公共影响有限。",[1232],{"name":1227,"url":1224},[34,35,4,1234,1235],"灾害风险","滑坡易发性",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[],{"status":46,"locked":22,"version":47,"method":48,"evidence":1239},{"candidates":1240,"agricultural_evidence":52},[1241,1245,1249,1253],{"code":39,"score":21,"supported":52,"title":1242,"abstract":1243,"tags":1244},[],[55,4,56],[4],{"code":59,"score":60,"supported":52,"title":1246,"abstract":1247,"tags":1248},[],[34,63],[34],{"code":66,"score":67,"supported":52,"title":1250,"abstract":1251,"tags":1252},[],[70,71],[],{"code":81,"score":8,"supported":22,"title":1254,"abstract":1255,"tags":1256},[],[],[35],[1258,1259],"埃塞俄比亚高原 滑坡易发性","GIS 遥感 滑坡风险制图","埃塞俄比亚高原滑坡易发性-4585","10.1007\u002Fs44475-026-00073-w",{"doi":1261,"openalex_id":1263,"authors":1264,"venue":1227,"cited_by_count":90,"oa_url":1224,"card":1282,"direction":106,"ingested_from":107},"W7221122595",[1265,1268,1270,1272,1274,1276,1278,1280],{"name":1266,"orcid":1267},"Engdaw Gulbet Tebege","https:\u002F\u002Forcid.org\u002F0009-0008-4252-1249",{"name":1269,"orcid":17},"Belete Getahun",{"name":1271,"orcid":17},"Yohannes Dessalegn Girma",{"name":1273,"orcid":17},"Yibeltal Awoke Temeche",{"name":1275,"orcid":17},"Worku Birhan Fenklew",{"name":1277,"orcid":17},"Ayalnesh Mihrete Tagele",{"name":1279,"orcid":17},"Gashaw Tesfaw Chekole",{"name":1281,"orcid":17},"Muluken Mintesinot",{"tldr":1283,"method":1284,"finding":1285,"direction":106,"opportunity":1286},"用GIS与遥感结合FR和AHP模型，对埃塞俄比亚高原滑坡易发性进行分区制图与验证。","GIS与遥感数据，11个孕灾因子，频率比与层次分析法，ROC曲线验证。","AHP精度略高（AUC 0.812），陡坡、玄武岩、高线密度与近水系为主要致灾因子。","可将滑坡易发性与农田地块、作物分布叠加，评估农业用地风险并支撑山区土地整治决策。","2026-10-10T23:30:27.880607Z",{"id":1289,"title":1290,"url":1291,"summary":1292,"summary_zh":1293,"content":17,"source_name":115,"source_url":1291,"published_at":1046,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":23,"score_detail":1294,"sources":1296,"tags":1298,"primary_topic":1302,"secondary_topics":1307,"classification":1309,"search_phrases":1344,"slug":1347,"view_count":8,"doi":1348,"paper":1349,"created_at":1359},4501,"THE IMPACT OF AGRICULTURAL LANDSCAPE USE AROUND KOKAND CITY ON FOOD SECURITY","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23244244","This thesis examines the impact of agricultural landscape use around Kokand City on food security based on a geographical approach. The study area encompasses agricultural territories directly adjacent to Kokand City and functionally connected to the city’s food supply. Landscape, territorial-comparative, statistical, and ecological-geographical analysis methods were used in the study. Based on official statistical data, it is shown that agricultural, forestry, and fishery products are produced within Kokand City itself. During January–September 2024, the volume of products from these sectors in the city amounted to 264.8 billion UZS, including 2.7 thousand tons of vegetables, 4.9 thousand tons of fruits, 7.4 thousand tons of milk, and 2.1 thousand tons of meat. At the same time, intensive irrigated farming, soil salinization, the efficiency of water resource use, and urbanization processes were assessed as key factors affecting the sustainability of agricultural landscapes. The study substantiates the need to monitor peri-urban agro-landscapes using GIS and remote sensing, improve irrigation efficiency, and control the transformation of productive agricultural land to strengthen food security.","本论文基于地理学方法，考察了浩罕市周边农业景观利用对粮食安全的影响。研究区域涵盖与浩罕市直接相邻且在功能上与城市粮食供应相联系的农业地域。研究中采用了景观分析、地域比较、统计及生态地理分析方法。基于官方统计数据，研究表明浩罕市自身范围内生产了农业、林业和渔业产品。2024年1月至9月期间，该市这些部门的产品总量达2648亿苏姆，其中包括2700吨蔬菜、4900吨水果、7400吨牛奶和2100吨肉类。同时，集约化灌溉农业、土壤盐渍化、水资源利用效率及城市化进程被评估为影响农业景观可持续性的关键因素。研究论证了利用地理信息系统（GIS）和遥感技术监测城郊农业景观、提高灌溉效率以及控制生产性农业用地转变以加强粮食安全的必要性。",{"impact":25,"substance":26,"depth":27,"authority":28,"freshness":29,"relevant":8,"comment":1295},"基于GIS与遥感的城郊农业景观研究，数据具体但属地方性案例，方法可借鉴。",[1297],{"name":115,"url":1291},[225,457,4,1299,1300,1301],"灌溉效率","盐碱化","城郊农业",{"code":222,"slug":1303,"name":1304,"path":1305,"parent_code":1306},"yield-food-security","单产提升与粮食安全","\u002Ftopic\u002Ffield-crops\u002Fyield-food-security","A",[1308],{"code":74,"slug":674,"name":940,"path":941,"parent_code":942},{"status":46,"locked":22,"version":47,"method":48,"evidence":1310},{"candidates":1311,"agricultural_evidence":52},[1312,1316,1320,1324,1328,1332,1338],{"code":222,"score":191,"supported":52,"title":1313,"abstract":1314,"tags":1315},[226],[225,226],[225],{"code":74,"score":29,"supported":52,"title":1317,"abstract":1318,"tags":1319},[],[78,477,674,957],[],{"code":59,"score":60,"supported":52,"title":1321,"abstract":1322,"tags":1323},[],[34,63],[457],{"code":39,"score":60,"supported":52,"title":1325,"abstract":1326,"tags":1327},[],[55,4],[4],{"code":66,"score":67,"supported":52,"title":1329,"abstract":1330,"tags":1331},[],[70,71],[],{"code":1333,"score":75,"supported":52,"title":1334,"abstract":1335,"tags":1337},"B1",[],[1336],"蔬菜",[],{"code":1339,"score":75,"supported":52,"title":1340,"abstract":1341,"tags":1343},"D",[],[1342],"渔业",[],[1345,1346],"Kokand 农业景观 粮食安全","城郊农业 GIS 遥感","Kokand农业景观粮食安全-4501","10.5281\u002Fzenodo.23244244",{"doi":1348,"openalex_id":1350,"authors":1351,"venue":115,"cited_by_count":90,"oa_url":1291,"card":1354,"direction":106,"ingested_from":107},"W7220903359",[1352],{"name":1353,"orcid":17},"Boratov Alijon",{"tldr":1355,"method":1356,"finding":1357,"direction":106,"opportunity":1358},"基于地理方法分析科坎德市周边农业景观利用对粮食安全的影响。","景观与生态地理分析、统计及GIS遥感监测建议。","灌溉、盐渍化、水资源效率与城市化是影响农业景观可持续性的关键因素。","可结合GIS与遥感构建城郊农业景观动态监测体系，评估灌溉效率与土地转化对粮食安全的影响。","2026-10-09T23:30:25.643757Z",{"id":1361,"title":1362,"url":1363,"summary":1364,"summary_zh":1365,"content":17,"source_name":1366,"source_url":1363,"published_at":1367,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":90,"score_detail":1368,"sources":1370,"tags":1372,"primary_topic":17,"secondary_topics":1375,"classification":1376,"search_phrases":1391,"slug":1394,"view_count":8,"doi":1395,"paper":1396,"created_at":1419},4361,"Flood susceptibility assessment using GIS and an analytical hierarchy process in Ilorin Metropolis, Kwara, Nigeria","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44327-026-00380-3","Flooding remains a major environmental challenge in Ilorin Metropolis, Kwara State, Nigeria. In this study, flood susceptibility across the metropolis was assessed using geographic information systems (GIS), remote sensing, and the analytical hierarchy process (AHP). ASTER Global Digital Elevation Model and Landsat 8 OLI\u002FTIRS imagery acquired in January 2024 were used to derive nine flood-conditioning factors: elevation, slope, drainage density, topographic wetness index, stream power index, distance from streams, distance from roads, land use\u002Fland cover (LULC), and normalized difference vegetation index. The factors were weighted using the AHP and integrated through weighted overlay in ArcGIS. The resulting flood susceptibility map classified 0.8% of the study area as very low susceptibility, 9.3% as low, 47.1% as moderate, 30.8% as high, and 12.0% as very high. Thus, 42.8% of Ilorin Metropolis was classified as having high or very high flood susceptibility, particularly along the Asa River corridor and low-lying urban areas. Independent validation using 200 flood and non-flood reference points produced an overall accuracy of 96.5%, a sensitivity (recall) of 1.00, a specificity of 0.95, a precision of 0.895, and a Cohen’s kappa of 0.919. The results demonstrate the utility of the GIS-AHP framework for identifying flood-susceptible areas and supporting urban flood mitigation and land use planning in the Ilorin Metropolis.","洪水仍然是尼日利亚夸拉州伊洛林大都市面临的主要环境挑战。本研究利用地理信息系统（GIS）、遥感和层次分析法（AHP）评估了该大都市的洪水敏感性。研究使用ASTER全球数字高程模型和2024年1月获取的Landsat 8 OLI\u002FTIRS影像，提取了九个洪水致灾因子：高程、坡度、河网密度、地形湿度指数、河流功率指数、距河流距离、距道路距离、土地利用\u002F土地覆盖（LULC）以及归一化植被指数。采用层次分析法对这些因子进行赋权，并在ArcGIS中通过加权叠加进行集成。生成的洪水敏感性图将研究区0.8%的区域划分为极低敏感性，9.3%为低敏感性，47.1%为中等敏感性，30.8%为高敏感性，12.0%为极高敏感性。因此，伊洛林大都市42.8%的区域被归类为高或极高洪水敏感性，尤其是沿阿萨河走廊和低洼城市地区。利用200个洪水和非洪水参考点进行的独立验证得出总体精度为96.5%，灵敏度（召回率）为1.00，特异度为0.95，精确率为0.895，Cohen's kappa系数为0.919。结果表明，GIS-AHP框架可用于识别洪水易发区域，并为伊洛林大都市的城市洪水缓解和土地利用规划提供支持。","Discover Cities","2026-10-05T00:00:00Z",{"impact":90,"substance":90,"depth":90,"authority":90,"freshness":90,"relevant":90,"comment":1369},"该研究聚焦尼日利亚伊洛林城市洪水易发性评估，属城市防灾与GIS遥感应用，与三农、农业信息化、智慧农业等主题无直接关联，不建议进入每日精选。",[1371],{"name":1366,"url":1363},[34,4,1373,1374],"洪水风险","城市防洪",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1377},{"candidates":1378,"agricultural_evidence":22,"reason":284},[1379,1383,1387],{"code":39,"score":26,"supported":52,"title":1380,"abstract":1381,"tags":1382},[4],[55,4,56],[4],{"code":59,"score":60,"supported":52,"title":1384,"abstract":1385,"tags":1386},[],[34,63],[34],{"code":480,"score":8,"supported":22,"title":1388,"abstract":1389,"tags":1390},[],[],[1373],[1392,1393],"城市防洪 洪水风险 遥感 GIS","城市防洪 洪水风险","城市防洪洪水风险遥感GIS-4361","10.1007\u002Fs44327-026-00380-3",{"doi":1395,"openalex_id":1397,"authors":1398,"venue":1366,"cited_by_count":90,"oa_url":1413,"card":1414,"direction":106,"ingested_from":107},"W7220433564",[1399,1401,1404,1407,1410],{"name":1400,"orcid":17},"Olaitan Isioye",{"name":1402,"orcid":1403},"Maimuna Mahmud Zailani","https:\u002F\u002Forcid.org\u002F0009-0003-0566-4842",{"name":1405,"orcid":1406},"Mudassir Hassan","https:\u002F\u002Forcid.org\u002F0009-0005-0257-298X",{"name":1408,"orcid":1409},"Ibrahim Faruk Gaya","https:\u002F\u002Forcid.org\u002F0000-0003-2644-1982",{"name":1411,"orcid":1412},"Muhammad Lawal Abubakar","https:\u002F\u002Forcid.org\u002F0000-0002-2797-3166","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44327-026-00380-3.pdf",{"tldr":1415,"method":1416,"finding":1417,"direction":106,"opportunity":1418},"用GIS、遥感和AHP评估尼日利亚伊洛林市洪水易发性并制图。","ASTER DEM与Landsat 8影像提取9个因子，AHP加权叠加，200点","42.8%区域高或极高易发，模型总体精度96.5%，Kappa为0.919。","可引入机器学习与实时降雨数据，提升洪水易发性动态预测精度。","2026-10-07T23:30:28.711328Z",{"id":1421,"title":1422,"url":1423,"summary":1424,"summary_zh":1425,"content":17,"source_name":1426,"source_url":1423,"published_at":1427,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":23,"score_detail":1428,"sources":1430,"tags":1432,"primary_topic":17,"secondary_topics":1433,"classification":1434,"search_phrases":1453,"slug":1456,"view_count":90,"doi":1457,"paper":1458,"created_at":1473},4316,"GIS-BASED ASSESSMENT OF SOIL EROSION RISK IN GUBI DAM WATERSHED, NORTHEASTERN NIGERIA, USING THE REVISED UNIVERSAL SOIL LOSS EQUATION (RUSLE)","https:\u002F\u002Fdoi.org\u002F10.70382\u002Fbejemcr.v13i4.040","Soil erosion within reservoir watersheds can degrade land resources and mobilise sediment through drainage networks, making spatial identification of erosion-prone areas important for watershed management. This study assessed the magnitude and spatial distribution of soil erosion in the Gubi Dam watershed, northeastern Nigeria, using the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) and remote-sensing techniques. A 30m Shuttle Radar Topography Mission (SRTM) digital elevation model was used for watershed delineation and terrain analysis, while rainfall records, FAO soil information and September 2021 Landsat 8 OLI imagery were used to derive rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover-management (C), and support-practice (P) factors. Vegetation protection was represented using a continuous NDVI-derived C-factor surface. The delineated watershed covered approximately 18,067.39 ha (180.67 km²). RUSLE estimated soil loss ranged from approximately 0 to 715.3 t ha⁻¹ yr⁻¹, with a watershed-wide mean of 5.590t ha⁻¹ yr⁻¹. The archived study-specific classification indicated that 98.6% of the watershed occurred within the two lower soil loss classes, whereas the three upper classes collectively occupied approximately 252.94 ha (1.4%). Elevated estimates were spatially concentrated, particularly in areas associated with steep terrain and major drainage pathways. The assessment provides a spatial screening basis for prioritising field investigation and soil conservation planning. The estimates represent potential sheet and rill soil loss rather than sediment delivery to Gubi Reservoir, and field validation is recommended.","水库流域内的土壤侵蚀会退化土地资源，并通过排水网络搬运泥沙，因此对易侵蚀区域进行空间识别对流域管理具有重要意义。本研究采用修订通用土壤流失方程（RUSLE），结合地理信息系统（GIS）和遥感技术，评估了尼日利亚东北部古比大坝流域土壤侵蚀的强度与空间分布。研究使用30 m航天飞机雷达地形测绘任务（SRTM）数字高程模型进行流域划分和地形分析，并利用降雨记录、FAO土壤信息和2021年9月Landsat 8 OLI影像提取降雨侵蚀力（R）、土壤可蚀性（K）、坡长与坡度（LS）、植被覆盖与管理（C）以及水土保持措施（P）因子。植被保护状况通过基于NDVI生成的连续C因子表面来表示。划分出的流域面积约为18 067.39 ha（180.67 km²）。RUSLE估算的土壤流失量约为0至715.3 t ha⁻¹ yr⁻¹，全流域平均值为5.590 t ha⁻¹ yr⁻¹。本研究采用的分类结果表明，流域内98.6%的区域属于两个较低土壤流失等级，而三个较高等级合计约占252.94 ha（1.4%）。高估算值在空间上较为集中，尤其出现在陡峭地形和主要排水通道相关区域。该评估为优先开展野外调查和水土保持规划提供了空间筛查依据。这些估算值代表潜在的片蚀和细沟土壤流失，而非输移至古比水库的泥沙量，建议进行野外验证。","Journal of Environmental Management and Construction Research","2026-10-04T00:00:00Z",{"impact":25,"substance":26,"depth":191,"authority":28,"freshness":25,"relevant":8,"comment":1429},"基于RUSLE与GIS\u002F遥感的流域土壤侵蚀定量评估，方法规范、数据具体，但属区域性案例研究，对国内三农信息化仅有方法借鉴价值。",[1431],{"name":1426,"url":1423},[457,36,4,37,1052],[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1435},{"candidates":1436,"agricultural_evidence":22,"reason":284},[1437,1441,1445,1449],{"code":39,"score":26,"supported":52,"title":1438,"abstract":1439,"tags":1440},[4],[55,4,56],[4],{"code":66,"score":27,"supported":52,"title":1442,"abstract":1443,"tags":1444},[71],[70,71],[],{"code":81,"score":150,"supported":52,"title":1446,"abstract":1447,"tags":1448},[],[37],[37],{"code":59,"score":150,"supported":52,"title":1450,"abstract":1451,"tags":1452},[],[34],[457],[1454,1455],"Gubi Dam 流域 RUSLE","尼日利亚 土壤侵蚀 GIS","GubiDam流域RUSLE-4316","10.70382\u002Fbejemcr.v13i4.040",{"doi":1457,"openalex_id":1459,"authors":1460,"venue":1426,"cited_by_count":90,"oa_url":1467,"card":1468,"direction":106,"ingested_from":107},"W7219911927",[1461,1463,1465],{"name":1462,"orcid":17},"AHMED BABAYO",{"name":1464,"orcid":17},"ABDULKADIR ABUBAKAR",{"name":1466,"orcid":17},"ZAKARI DANLADI","https:\u002F\u002Fberkeleypublications.com\u002Fbjemcr\u002Farticle\u002Fdownload\u002F895\u002F790",{"tldr":1469,"method":1470,"finding":1471,"direction":106,"opportunity":1472},"用RUSLE结合GIS和遥感评估尼日利亚Gubi水库流域土壤侵蚀风险并制图。","RUSLE模型、30m SRTM DEM、Landsat 8 OLI、NDVI与","流域年均土壤流失5.59 t\u002Fha\u002Fyr，高侵蚀区集中于陡坡和主排水路径，仅1.4%面积属高侵蚀等级","可结合泥沙输移比与实地验证，将潜在侵蚀估算转化为水库淤积风险与保护措施优先区研究。","2026-10-06T23:30:21.805554Z",{"id":1475,"title":1476,"url":1477,"summary":1478,"summary_zh":1479,"content":17,"source_name":1480,"source_url":1477,"published_at":1427,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":1481,"score_detail":1482,"sources":1484,"tags":1486,"primary_topic":17,"secondary_topics":1490,"classification":1491,"search_phrases":1506,"slug":1509,"view_count":90,"doi":1510,"paper":1511,"created_at":1524},4315,"أثرتغير الحرارة والامطار على التدهور البيئي في ناحية الكوير","https:\u002F\u002Fdoi.org\u002F10.66359\u002Fitqan.v2i1.034","يتناول البحث أثر التغيرات المناخية في تدهور الغطاء النباتي بناحية الكوير خلال المدة (1990–2023)، من خلال تحليل بيانات الحرارة والأمطار، واستخدام تقنيات الاستشعار عن بعد ونظم المعلومات الجغرافية (GIS) ومؤشر الغطاء النباتي (NDVI). أظهرت النتائج ارتفاعاً في درجات الحرارة مقابل انخفاض وتذبذب كميات الأمطار، مما أدى إلى تراجع كثافة الغطاء النباتي واتساع مساحات الغطاء الضعيف، خاصة في عامي 2000 و2023 بفعل الجفاف وارتفاع التبخر. كما أكدت الدراسة وجود علاقة واضحة بين التغيرات المناخية وتدهور الغطاء النباتي، مما يبرز أهمية تبني إدارة بيئية مستدامة للحفاظ على الموارد الطبيعية في المنطقة","本研究探讨了1990年至2023年期间气候变化对科韦尔地区植被退化的影响，通过分析气温和降水数据，并运用遥感技术、地理信息系统（GIS）和植被指数（NDVI）进行研究。结果表明，气温上升而降水量减少且波动，导致植被密度下降、稀疏植被面积扩大，尤其是在2000年和2023年，干旱和蒸发加剧了这一趋势。研究还证实气候变化与植被退化之间存在明显关系，凸显了采取可持续环境管理以保护该地区自然资源的重要性。","مجلة الاتقان للعلوم الإنسانية",57,{"impact":25,"substance":26,"depth":191,"authority":21,"freshness":67,"relevant":8,"comment":1483},"基于遥感与GIS的伊拉克区域植被退化实证研究，方法规范但属地方性案例，公共影响有限。",[1485],{"name":1480,"url":1477},[1487,1488,457,4,1489],"气候变化","NDVI","植被退化",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1492},{"candidates":1493,"agricultural_evidence":22,"reason":284},[1494,1498,1502],{"code":480,"score":60,"supported":52,"title":1495,"abstract":1496,"tags":1497},[],[1487,483],[1487],{"code":39,"score":60,"supported":52,"title":1499,"abstract":1500,"tags":1501},[],[55,4],[4],{"code":59,"score":67,"supported":52,"title":1503,"abstract":1504,"tags":1505},[],[34],[1488,1489,457],[1507,1508],"الكوير NDVI","تدهور الغطاء النباتي GIS","الكويرNDVI-4315","10.66359\u002Fitqan.v2i1.034",{"doi":1510,"openalex_id":1512,"authors":1513,"venue":1480,"cited_by_count":90,"oa_url":1518,"card":1519,"direction":106,"ingested_from":107},"W7219900093",[1514,1516],{"name":1515,"orcid":17},"معن جاسم محمد",{"name":1517,"orcid":17},"أ. م. د    خالد صطم عطية","https:\u002F\u002Falitqan.iraqiqsa.org\u002Findex.php\u002FAIJHS\u002Farticle\u002Fdownload\u002Fitqan-v2i1-034\u002F389",{"tldr":1520,"method":1521,"finding":1522,"direction":106,"opportunity":1523},"研究1990–2023年伊拉克Kوير地区气温降水变化对植被退化的影响。","用气温降水数据、遥感、GIS和NDVI分析植被覆盖变化。","气温升高、降水减少且波动导致植被密度下降、弱覆盖扩大，2000和2023年最严重。","可结合多源遥感与气候模型，量化干旱区植被退化驱动机制并预测未来趋势。","2026-10-06T23:30:21.747683Z",{"id":1526,"title":1527,"url":1528,"summary":1529,"summary_zh":1530,"content":17,"source_name":1531,"source_url":1528,"published_at":1367,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":1532,"score_detail":1533,"sources":1535,"tags":1537,"primary_topic":1541,"secondary_topics":1542,"classification":1543,"search_phrases":1569,"slug":1572,"view_count":8,"doi":1573,"paper":1574,"created_at":1592},4312,"Identification of Cultivable Wastelands in Meghalaya, India using Geospatial Technology for Agricultural Reclamation","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fjgeesi\u002F2026\u002Fv30i101131","Cultivable wastelands suitable for cultivation are a significant land resource that can be utilised to improve agricultural productivity and sustainable land management. The present study aimed to estimate the cultivable wastelands of Meghalaya using Remote Sensing and Geographic Information System (GIS) techniques and to assess the possibilities for reclaiming wastelands for agriculture. Multispectral satellite data from the LISS-IV sensor for the period 2025-2026 were processed to create a False Colour Composite (FCC), and Land Use\u002FLand Cover (LULC) classification was performed using visual image interpretation to distinguish the major cultivable wasteland categories: Dense Scrub Land, Sparse Scrub Land, Grasslands\u002FGrazing Lands, and Shifting Cultivation Area. About 340,673.36 ha, representing almost 15.2% of the total geographical area of Meghalaya, were identified as cultivable wastelands. Among the identified categories, Sparse Scrub Land occupied the largest area (206,595.18 ha), followed by Dense Scrub Land (99,488.89 ha), Shifting Cultivation Area (34,331.34 ha), and Grasslands\u002FGrazing Lands (257.94 ha). The distribution of these wastelands suggests considerable potential for reclamation through appropriate land restoration and sustainable management practices. The spatial database and thematic maps generated provide baseline information for land-use planning, resource management, and policy formulation aimed at enhancing agricultural productivity and the sustainable utilisation of wastelands in Meghalaya.","适宜耕作的 cultivable wasteland（可耕荒地）是一项重要的土地资源，可用于提高农业生产力和可持续土地管理。本研究旨在利用遥感（Remote Sensing）和地理信息系统（Geographic Information System, GIS）技术估算梅加拉亚邦的可耕荒地，并评估将荒地开垦用于农业的可能性。对2025—2026年LISS-IV传感器多光谱卫星数据进行处理，生成假彩色合成影像（False Colour Composite, FCC），并通过目视图像解译进行土地利用\u002F土地覆盖（Land Use\u002FLand Cover, LULC）分类，以区分主要可耕荒地类别：密灌丛地、疏灌丛地、草地\u002F放牧地以及轮垦区。约340,673.36公顷土地被识别为可耕荒地，占梅加拉亚邦总地理面积的近15.2%。在已识别类别中，疏灌丛地面积最大（206,595.18公顷），其次为密灌丛地（99,488.89公顷）、轮垦区（34,331.34公顷）和草地\u002F放牧地（257.94公顷）。这些荒地的分布表明，通过适当的土地恢复和可持续管理措施，具有相当大的开垦潜力。所生成的空间数据库和专题图件为土地利用规划、资源管理和政策制定提供了基础信息，旨在提高梅加拉亚邦的农业生产力和实现荒地的可持续利用。","Journal of Geography Environment and Earth Science International",69,{"impact":28,"substance":119,"depth":190,"authority":28,"freshness":29,"relevant":8,"comment":1534},"基于LISS-IV遥感与GIS的印度梅加拉亚邦可耕荒地清查，数据翔实、方法规范，对农业土地复垦与空间规划有参考价值，但属区域案例，公共影响有限。",[1536],{"name":1531,"url":1528},[1538,1539,457,4,1540],"可持续农业","耕地保护","土地整治",{"code":43,"slug":129,"name":130,"path":131,"parent_code":17},[],{"status":134,"locked":22,"version":47,"method":48,"evidence":1544},{"candidates":1545,"agricultural_evidence":52,"reason":158},[1546,1551,1555,1559,1564],{"code":59,"score":21,"supported":52,"title":1547,"abstract":1548,"tags":1550},[],[34,63,1549],"multispectral",[457],{"code":39,"score":21,"supported":52,"title":1552,"abstract":1553,"tags":1554},[],[55,4,56],[4],{"code":691,"score":82,"supported":22,"title":1556,"abstract":1557,"tags":1558},[],[],[1540,1539],{"code":1560,"score":8,"supported":22,"title":1561,"abstract":1562,"tags":1563},"G2",[],[],[1540],{"code":1565,"score":8,"supported":22,"title":1566,"abstract":1567,"tags":1568},"H8",[],[],[1538],[1570,1571],"Meghalaya 可耕荒地 遥感","LISS-IV 土地利用 分类","Meghalaya可耕荒地遥感-4312","10.9734\u002Fjgeesi\u002F2026\u002Fv30i101131",{"doi":1573,"openalex_id":1575,"authors":1576,"venue":1531,"cited_by_count":90,"oa_url":1528,"card":1587,"direction":106,"ingested_from":107},"W7220436664",[1577,1579,1582,1584],{"name":1578,"orcid":17},"Ronak Meena",{"name":1580,"orcid":1581},"Chandan Goswami","https:\u002F\u002Forcid.org\u002F0000-0002-9487-5080",{"name":1583,"orcid":17},"C. P. Suresh",{"name":1585,"orcid":1586},"Akmaul Hoque","https:\u002F\u002Forcid.org\u002F0009-0002-4475-566X",{"tldr":1588,"method":1589,"finding":1590,"direction":106,"opportunity":1591},"利用遥感与GIS识别印度梅加拉亚邦可耕荒地并评估其农业复垦潜力。","LISS-IV多光谱影像、假彩色合成与目视解译的土地利用分类。","识别出约34万公顷可耕荒地，占全邦15.2%，以稀疏灌木地为主。","可结合机器学习自动分类与土壤、气候数据，构建荒地复垦适宜性评价模型。","2026-10-06T23:30:20.340575Z",{"id":1594,"title":1595,"url":1596,"summary":1597,"summary_zh":17,"content":17,"source_name":1598,"source_url":1596,"published_at":1367,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":588,"score_detail":1599,"sources":1601,"tags":1603,"primary_topic":17,"secondary_topics":1606,"classification":1607,"search_phrases":1626,"slug":1629,"view_count":82,"doi":1630,"paper":1631,"created_at":1639},4308,"GIS, Remote Sensing and Machine Learning Applications for Forest Fire Mapping, Susceptibility Assessment and Risk Analysis: A Systematic Review","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11233692\u002Fv1","GIS, Remote Sensing and Machine Learning Applications for Forest Fire Mapping, Susceptibility Assessment and Risk Analysis: A Systematic Review。Research Square","Research Square",{"impact":28,"substance":26,"depth":190,"authority":25,"freshness":29,"relevant":8,"comment":1600},"系统综述梳理遥感与机器学习在森林火灾制图与风险评估中的应用，对林业信息化与防灾有参考价值，但属综述类论文、来源为预印本平台，权威性一般。",[1602],{"name":1598,"url":1596},[141,34,4,1604,1605],"森林防火","风险评估",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1608},{"candidates":1609,"agricultural_evidence":22,"reason":284},[1610,1614,1618,1622],{"code":138,"score":28,"supported":52,"title":1611,"abstract":1612,"tags":1613},[142],[142],[141],{"code":59,"score":28,"supported":52,"title":1615,"abstract":1616,"tags":1617},[63],[63],[34],{"code":39,"score":28,"supported":52,"title":1619,"abstract":1620,"tags":1621},[4],[4],[4],{"code":480,"score":8,"supported":22,"title":1623,"abstract":1624,"tags":1625},[],[],[1604],[1627,1628],"森林火灾 遥感 机器学习","GIS 森林火险 评估","森林火灾遥感机器学习-4308","10.21203\u002Frs.3.rs-11233692\u002Fv1",{"doi":1630,"openalex_id":1632,"authors":1633,"venue":1598,"cited_by_count":90,"oa_url":1638,"card":17,"direction":106,"ingested_from":107},"W7220368159",[1634,1636],{"name":1635,"orcid":17},"Lucius Malalu",{"name":1637,"orcid":17},"Henry Chinthuli","https:\u002F\u002Fwww.researchsquare.com\u002Farticle\u002Frs-11233692\u002Flatest.pdf","2026-10-06T23:30:19.935677Z",{"id":1641,"title":1642,"url":1643,"summary":1644,"summary_zh":1645,"content":17,"source_name":115,"source_url":1643,"published_at":1646,"category":20,"cover_url":17,"hotness":1647,"is_selected":22,"score":1648,"score_detail":1649,"sources":1651,"tags":1655,"primary_topic":1657,"secondary_topics":1658,"classification":1659,"search_phrases":1678,"slug":1681,"view_count":90,"doi":1682,"paper":1683,"created_at":1693},4305,"A Comparative Geographical Analysis of Land Use Patterns in Akrani and Nandurbar Tehsils of Nandurbar District","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23155213","Abstract \"A Comparative Geographical Analysis of Land Use Patterns in Akrani and Nandurbar Tehsils in Nandurbar District,\" aims to analyze and contrast the features and spatial distribution of different land-use categories in the two tehsils. An key measure of how human activity and the physical environment interact is land use. Major land-use categories include agricultural land, forest land, fallow land, barren and uncultivable land, grazing land, built-up land, and water bodies are the focus of the study. Akrani Tehsil is distinguished by hilly and rugged terrain, a substantial amount of forest cover, and primarily rain-fed agriculture, whereas Nandurbar Tehsil has relatively favorable terrain, agricultural conditions, irrigation facilities, and a higher concentration of settlements and other non-agricultural activities. In addition to geographical methods like GIS and remote sensing when appropriate, the study makes use of secondary data from government reports, Census publications, statistical records, maps, and other pertinent sources. In order to determine the regional variances, similarities, and differences in land-use patterns, as well as to investigate the impact of socioeconomic and physical factors on land usage, a comparative study is conducted. By improving knowledge of regional differences in land use, the study is expected to support sustainable resource management, land-use planning, and balanced regional development in the Nandurbar District.","《阿克兰尼与南杜尔巴尔塔卢卡土地利用模式的比较地理分析——以楠杜尔巴尔县为例》旨在分析和对比这两个塔卢卡不同土地利用类别的特征与空间分布。土地利用是衡量人类活动与自然环境相互作用的重要指标。研究重点关注的主要土地利用类别包括农业用地、林地、休耕地、荒地和不可耕种地、放牧地、建设用地及水体。阿克兰尼塔卢卡以丘陵崎岖地形、大面积森林覆盖和以雨养农业为主为特征，而南杜尔巴尔塔卢卡则拥有相对有利的地形、农业条件、灌溉设施，以及更集中的居民点和其他非农业活动。本研究在适当情况下运用地理信息系统（GIS）和遥感等地理学方法，同时利用来自政府报告、人口普查出版物、统计记录、地图及其他相关来源的二手数据。为确定土地利用模式的区域差异、相似性与不同之处，并探究社会经济和自然因素对土地利用的影响，本研究进行了比较分析。通过增进对土地利用区域差异的认识，该研究有望为楠杜尔巴尔县的可持续资源管理、土地利用规划和区域均衡发展提供支持。","2026-10-31T00:00:00Z",25,45,{"impact":67,"substance":27,"depth":660,"authority":28,"freshness":90,"relevant":8,"comment":1650},"印度地方性土地利用对比研究，方法常规、无全国性价值，且发布日期晚于今日，时效性为零，不建议进入每日精选。",[1652,1653],{"name":115,"url":1643},{"name":115,"url":1654},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23155212",[457,35,1656,4],"区域发展",{"code":43,"slug":129,"name":130,"path":131,"parent_code":17},[],{"status":134,"locked":22,"version":47,"method":48,"evidence":1660},{"candidates":1661,"agricultural_evidence":52,"reason":158},[1662,1666,1670,1674],{"code":59,"score":60,"supported":52,"title":1663,"abstract":1664,"tags":1665},[],[34,63],[457],{"code":39,"score":60,"supported":52,"title":1667,"abstract":1668,"tags":1669},[],[55,4],[4],{"code":74,"score":67,"supported":52,"title":1671,"abstract":1672,"tags":1673},[],[78,674],[],{"code":81,"score":8,"supported":22,"title":1675,"abstract":1676,"tags":1677},[],[],[35],[1679,1680],"Nandurbar 土地利用 对比","Akrani Nandurbar 遥感","Nandurbar土地利用对比-4305","10.5281\u002Fzenodo.23155213",{"doi":1682,"openalex_id":1684,"authors":1685,"venue":115,"cited_by_count":90,"oa_url":1643,"card":1688,"direction":106,"ingested_from":107},"W7220403169",[1686],{"name":1687,"orcid":17},"Amol Rameshwarrao Bhuyar",{"tldr":1689,"method":1690,"finding":1691,"direction":106,"opportunity":1692},"对比分析印度Nandurbar县Akrani与Nandurbar两个乡的土地利用格局差异。","基于政府报告、普查等二手数据，结合GIS与遥感进行对比地理分析。","Akrani以林地、雨养农业为主，Nandurbar地形与灌溉条件更优、建设用地更集中。","可引入多时相遥感影像与农户调查，量化地形—灌溉差异对土地利用变化的驱动机制。","2026-10-06T23:30:19.626838Z",{"id":1695,"title":1696,"url":1697,"summary":1698,"summary_zh":1699,"content":17,"source_name":115,"source_url":1697,"published_at":1367,"category":20,"cover_url":17,"hotness":1647,"is_selected":22,"score":866,"score_detail":1700,"sources":1702,"tags":1706,"primary_topic":1710,"secondary_topics":1711,"classification":1718,"search_phrases":1747,"slug":1750,"view_count":90,"doi":1751,"paper":1752,"created_at":1771},4294,"GIS- and Remote Sensing-Based Identification of Suitable Agricultural Waste Landfill Sites for Climate-Smart Agriculture in Ilorin, Nigeria","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23168428","Abstract Lack of a designated landfill for agricultural waste management (AWM) in Ilorin municipalities led to indiscriminate disposal of agricultural waste within the city and the only existing Sokoto-Ayekale general solid waste dumpsite, posing environmental and public health risks while undermining climate-smart agriculture (CSA). The study identifies suitable landfill sites for AWM by integrating Geographic Information System (GIS), Remote Sensing (RS), and Multi-Criteria Decision Analysis (MCDA) to locate environmentally and climate-resilient sites. Spatial data employed for the study include Shuttle Radar Topography Mission (SRTM), Landsat 9 imagery, Digital Elevation Model (DEM), road networks, waterbodies, built-up areas, soil quality, slope, and geology, which were processed in ArcGIS 10.3 to develop constraint thematic suitability maps. The Analytical Hierarchy Process (AHP) was employed to derive criterion weights, and the Weighted Linear Combination (WLC) was used to generate the map. AHP consistency ratio (CR) was used to validate the model’s consistency (CR=0.016), which falls within the acceptable CR \u003C0.1. The AHP weighted results were 0.41, 0.2, 0.14, 0.10, 0.08, and 0.07 for waterbodies, built-up area, slope, soil quality, geology, and road network, respectively. Maps were created for each criterion, reclassified, and integrated using the weighted linear combination method to generate an overall AWM suitability map. The study identified four potential locations for AWM. Approximately 507.23 km² are unsuitable, 1204.21 km² are marginally suitable, 4899.28 km² are moderately suitable, and 2021.7 km² are highly suitable for AWM landfill development. The findings present a scientifically based decision-support framework to guide policymakers, environmental agencies, and urban planners in developing sustainable AWM strategies that minimize environmental risk while advancing climate-smart agriculture. Keywords: Agricultural waste, Climate-smart agriculture, Landfill, Suitability, Sustainability","摘要 伊洛林各市镇缺乏用于农业废弃物管理（AWM）的指定填埋场，导致农业废弃物在城市内部及唯一现有的索科托-阿耶卡莱一般固体废弃物倾倒场被随意处置，既构成环境和公共健康风险，也削弱了气候智慧型农业（CSA）。本研究通过整合地理信息系统（GIS）、遥感（RS）和多准则决策分析（MCDA），识别适用于AWM的填埋场选址，以确定具有环境韧性和气候韧性的场址。研究采用的空间数据包括航天飞机雷达地形测绘任务（SRTM）数据、Landsat 9影像、数字高程模型（DEM）、道路网络、水体、建成区、土壤质量、坡度和地质，并在ArcGIS 10.3中进行处理以生成约束性专题适宜性图。采用层次分析法（AHP）推导准则权重，并运用加权线性组合（WLC）生成地图。使用AHP一致性比率（CR）验证模型的一致性（CR=0.016），该值处于可接受的CR\u003C0.1范围内。AHP加权结果分别为：水体0.41、建成区0.2、坡度0.14、土壤质量0.10、地质0.08、道路网络0.07。针对每个准则生成地图，经重分类后采用加权线性组合方法进行整合，生成总体AWM适宜性图。研究确定了四个潜在的AWM选址。约507.23 km²不适宜，1204.21 km²勉强适宜，4899.28 km²中等适宜，2021.7 km²高度适宜建设AWM填埋场。研究结果为政策制定者、环境机构和城市规划者提供了基于科学的决策支持框架，以指导制定可持续的AWM策略，在降低环境风险的同时推进气候智慧型农业。关键词：农业废弃物，气候智慧型农业，填埋场，适宜性，可持续性",{"impact":28,"substance":740,"depth":120,"authority":660,"freshness":29,"relevant":8,"comment":1701},"GIS与遥感结合MCDA为农业废弃物填埋选址提供决策框架，方法规范、数据翔实，但属区域性案例研究，公共影响有限。",[1703,1704],{"name":115,"url":1697},{"name":115,"url":1705},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23168429",[34,1707,1708,4,1709],"农业废弃物","气候智慧农业","选址评估",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[1712,1717],{"code":1713,"slug":1714,"name":1715,"path":1716,"parent_code":942},"H5","waste","面源污染与废弃物利用","\u002Ftopic\u002Fenvironment\u002Fwaste",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":1719},{"candidates":1720,"agricultural_evidence":52},[1721,1725,1730,1734,1739,1743],{"code":39,"score":26,"supported":52,"title":1722,"abstract":1723,"tags":1724},[4],[55,4,56],[4],{"code":1713,"score":191,"supported":52,"title":1726,"abstract":1728,"tags":1729},[1727],"agricultural waste",[1707,1727],[1707],{"code":59,"score":191,"supported":52,"title":1731,"abstract":1732,"tags":1733},[63],[34,63],[34],{"code":894,"score":752,"supported":52,"title":1735,"abstract":1737,"tags":1738},[1736],"smart agriculture",[1736],[],{"code":66,"score":67,"supported":52,"title":1740,"abstract":1741,"tags":1742},[],[70,71],[],{"code":480,"score":8,"supported":22,"title":1744,"abstract":1745,"tags":1746},[],[],[1708],[1748,1749],"Ilorin 农业废弃物 填埋场 选址","GIS 遥感 农业废弃物 填埋场","Ilorin农业废弃物填埋场选址-4294","10.5281\u002Fzenodo.23168428",{"doi":1751,"openalex_id":1753,"authors":1754,"venue":115,"cited_by_count":90,"oa_url":1697,"card":1766,"direction":316,"ingested_from":107},"W7220389353",[1755,1757,1759,1761,1764],{"name":1756,"orcid":17},"Saheed Mohammed Ishaq",{"name":1758,"orcid":17},"Alamin Adedeji Adenekan",{"name":1760,"orcid":17},"Ibrahim Dauda",{"name":1762,"orcid":1763},"Afeez Oladeji Amoo","https:\u002F\u002Forcid.org\u002F0000-0002-0412-9333",{"name":1765,"orcid":17},"Nureni Babatunde Amoo",{"tldr":1767,"method":1768,"finding":1769,"direction":104,"opportunity":1770},"用GIS、遥感和多准则决策为尼日利亚Ilorin筛选农业废弃物填埋场适宜选址。","GIS\u002FRS结合AHP与加权线性组合，基于DEM、Landsat 9等空间数据。","识别出4处潜在选址，约2021.7 km²高度适宜，模型一致性良好。","可将该选址框架与温室气体排放、运输成本及气候情景耦合，拓展到其他区域。","2026-10-06T23:30:07.715522Z",{"id":1773,"title":1774,"url":1775,"summary":1776,"summary_zh":1777,"content":17,"source_name":1778,"source_url":1775,"published_at":1779,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":117,"score_detail":1780,"sources":1782,"tags":1784,"primary_topic":17,"secondary_topics":1788,"classification":1789,"search_phrases":1817,"slug":1820,"view_count":90,"doi":1821,"paper":1822,"created_at":1857},4232,"Integrated machine learning and AHP-based framework for spatial delineation of rainwater harvesting potential","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-72943-8","Groundwater scarcity and its declining situation in the semi-arid area of Jaipur district, Rajasthan make it imperative to adopt scientific solutions to locate suitable rainwater harvesting sites. This study combines Geographic Information Systems (GIS), Analytical Hierarchy Process (AHP) and machine learning (ML) algorithms for delineating the RWH suitability zones. Eleven biophysical and anthropogenic factors, namely elevation (280–647 m), slope (0–35°), topographic wetness index (TWI), drainage density, soil profile, land use\u002Fland cover (LULC), rainfall (350–700 mm yr⁻ 1 ), hillshade, aspect, lineament density, and proximity to roads, were standardized and incorporated into a spatial database. A georeferenced inventory of 150 locations was divided into training (70%; n = 105) and testing (30%; n = 45) datasets and analyzed using XGBoost, Support Vector Machine (SVM), Gradient Boosting Machine (GBM), CatBoost, and AHP models. Among the evaluated algorithms, XGBoost exhibited the highest predictive performance with a ROC-AUC of 0.78, followed by SVM (0.76), AHP (0.73), CatBoost (0.69), and GBM (0.68). The XGBoost model identified 38.1% (3902.6 km 2 ) of the study area as highly suitable to very highly suitable for RWH implementation, whereas 34.6% (3533.7 km 2 ) and 27.3% (2783.7 km 2 ) were classified as moderate and low-to-very low suitability classes, respectively. Variable importance analysis revealed that rainfall (15.7%), drainage density (15.6%), elevation (11.5%), and TWI (8.8%) were the dominant controls on RWH suitability. The AHP framework showed acceptable consistency (CR \u003C 0.10) and model validation showed an overall accuracy of 88% and a Kappa coefficient of 0.64. The integrated framework successfully identified priority recharge areas in the southeastern lowlands and offers a scalable decision support tool for sustainable groundwater management and water resource planning that is resilient to climate change in semi-arid areas.","拉贾斯坦邦斋浦尔地区半干旱区的地下水稀缺及其持续下降的态势，使得采用科学方法确定适宜的雨水收集地点势在必行。本研究结合地理信息系统（Geographic Information Systems, GIS）、层次分析法（Analytical Hierarchy Process, AHP）和机器学习（Machine Learning, ML）算法，划定雨水收集适宜性分区。研究将11项生物物理和人为因素，即高程（280–647 m）、坡度（0–35°）、地形湿度指数（Topographic Wetness Index, TWI）、河网密度、土壤剖面、土地利用\u002F土地覆被（Land Use\u002FLand Cover, LULC）、降雨量（350–700 mm yr⁻¹）、山体阴影、坡向、线理密度和道路邻近度，进行标准化处理并纳入空间数据库。将150个地理参考位置清单划分为训练集（70%；n = 105）和测试集（30%；n = 45），并采用XGBoost、支持向量机（Support Vector Machine, SVM）、梯度提升机（Gradient Boosting Machine, GBM）、CatBoost和AHP模型进行分析。在评估的算法中，XGBoost表现出最高的预测性能，ROC-AUC为0.78，其次是SVM（0.76）、AHP（0.73）、CatBoost（0.69）和GBM（0.68）。XGBoost模型识别出研究区38.1%（3902.6 km²）的区域为雨水收集高度适宜至极高适宜区，而34.6%（3533.7 km²）和27.3%（2783.7 km²）分别被归类为中度适宜和低至极低适宜等级。变量重要性分析表明，降雨量（15.7%）、河网密度（15.6%）、高程（11.5%）和TWI（8.8%）是雨水收集适宜性的主导控制因素。AHP框架显示出可接受的一致性（CR \u003C 0.10），模型验证显示总体精度为88%，Kappa系数为0.64。该集成框架成功识别了东南部低地的优先补给区，并为半干旱地区可持续地下水管理和应对气候变化的淡水资源规划提供了一种可扩展的决策支持工具。","Scientific Reports","2026-10-03T00:00:00Z",{"impact":25,"substance":452,"depth":120,"authority":27,"freshness":29,"relevant":8,"comment":1781},"方法扎实、结论可复用的半干旱区雨水收集选址研究，但属区域案例，公共影响有限。",[1783],{"name":1778,"url":1775},[1785,141,4,1786,1787],"农业遥感","雨水收集","地下水管理",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1790},{"candidates":1791,"agricultural_evidence":22,"reason":284},[1792,1796,1800,1805,1809,1813],{"code":138,"score":26,"supported":52,"title":1793,"abstract":1794,"tags":1795},[142],[141,142,143],[141],{"code":39,"score":21,"supported":52,"title":1797,"abstract":1798,"tags":1799},[],[55,4,56],[4],{"code":480,"score":29,"supported":52,"title":1801,"abstract":1802,"tags":1804},[],[1487,483,1803],"climate change",[],{"code":66,"score":67,"supported":52,"title":1806,"abstract":1807,"tags":1808},[],[70,71],[],{"code":74,"score":67,"supported":52,"title":1810,"abstract":1811,"tags":1812},[],[477,957],[],{"code":59,"score":8,"supported":22,"title":1814,"abstract":1815,"tags":1816},[],[],[1785],[1818,1819],"Jaipur 雨水收集 选址","XGBoost AHP 地下水补给","Jaipur雨水收集选址-4232","10.1038\u002Fs41598-026-72943-8",{"doi":1821,"openalex_id":1823,"authors":1824,"venue":1778,"cited_by_count":90,"oa_url":1851,"card":1852,"direction":106,"ingested_from":107},"W7218709806",[1825,1828,1830,1833,1835,1837,1839,1841,1843,1845,1848],{"name":1826,"orcid":1827},"Agradeep Mohanta","https:\u002F\u002Forcid.org\u002F0000-0002-9369-3445",{"name":1829,"orcid":17},"Ameet Yadav",{"name":1831,"orcid":1832},"Dharmendra Singh","https:\u002F\u002Forcid.org\u002F0000-0001-8528-8637",{"name":1834,"orcid":17},"Sultan Singh",{"name":1836,"orcid":17},"Shuchi Mishra",{"name":1838,"orcid":17},"Kanwarpreet Singh",{"name":1840,"orcid":17},"Abhishek Sharma",{"name":1842,"orcid":17},"Amenjor Senagah",{"name":1844,"orcid":17},"Aditya Kumar Tiwary",{"name":1846,"orcid":1847},"Chandni Thakur","https:\u002F\u002Forcid.org\u002F0000-0001-8976-2738",{"name":1849,"orcid":1850},"Mohamed A. Mattar","https:\u002F\u002Forcid.org\u002F0000-0002-7506-3036","https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-72943-8_reference.pdf",{"tldr":1853,"method":1854,"finding":1855,"direction":106,"opportunity":1856},"结合GIS、AHP与多种机器学习算法，划分印度斋浦尔半干旱区雨水收集适宜性分区。","11个生物物理与人为因子，150个样本，XGBoost、SVM、GBM、CatB","XGBoost表现最佳（AUC=0.78），38.1%区域高度适宜，降雨与排水密度为主导因子。","可将该集成框架迁移至其他半干旱农业区，并结合遥感时序数据动态更新适宜性。","2026-10-05T23:30:25.173949Z",{"id":1859,"title":1860,"url":1861,"summary":1862,"summary_zh":1863,"content":17,"source_name":115,"source_url":1861,"published_at":1864,"category":20,"cover_url":17,"hotness":1647,"is_selected":22,"score":1865,"score_detail":1866,"sources":1868,"tags":1872,"primary_topic":17,"secondary_topics":1875,"classification":1876,"search_phrases":1907,"slug":1910,"view_count":82,"doi":1911,"paper":1912,"created_at":1922},4169,"Spatial Patterns and Dynamics of Agricultural Land Use: A Geographical Analysis","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23117515","This study examines the spatial patterns and dynamics of agricultural land use through a geographical perspective, emphasizing the relationship between land use, land cover, and socio-economic as well as environmental factors. The research integrates spatial analysis methods, remote sensing, and GIS techniques to understand the distribution, transformation, and management of agricultural landscapes across different regions. It highlights how factors such as market forces, technological advancements, policy interventions, and environmental constraints influence land-use decisions and transitions. The study also explores agricultural typologies, landscape ecosystems, and regional variations in land-use practices, supported by global case studies including Europe, North America, East Asia, Sub-Saharan Africa, and South America. Furthermore, it discusses the impacts of agricultural land use on biodiversity, soil, water resources, and climate systems, emphasizing sustainability challenges and ecosystem services. The findings underline the importance of integrated land-use planning, governance reforms, and adaptive strategies to promote sustainable agricultural development in the face of climate change and increasing global demand for food.","本研究从地理学视角考察农业土地利用的空间格局与动态变化，重点关注土地利用、土地覆盖与社会经济及环境因素之间的关系。研究综合运用空间分析方法、遥感与GIS技术，理解不同区域农业景观的分布、转型与管理。研究强调市场力量、技术进步、政策干预和环境约束等因素如何影响土地利用决策与转变。研究还探讨了农业类型学、景观生态系统以及土地利用实践的区域差异，并辅以欧洲、北美、东亚、撒哈拉以南非洲和南美洲的全球案例研究。此外，研究讨论了农业土地利用对生物多样性、土壤、水资源和气候系统的影响，强调可持续性挑战与生态系统服务。研究结论强调，面对气候变化和全球粮食需求不断增长，综合土地利用规划、治理改革和适应性策略对于促进农业可持续发展具有重要意义。","2026-11-30T00:00:00Z",49,{"impact":25,"substance":27,"depth":191,"authority":28,"freshness":90,"relevant":8,"comment":1867},"综述性论文，方法整合遥感与GIS，但缺乏新数据与具体案例，且发布日期在未来，时效性不足，不建议进入每日精选。",[1869,1870],{"name":115,"url":1861},{"name":115,"url":1871},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23117514",[1538,34,4,1873,1874],"生态系统服务","农业土地利用",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1877},{"candidates":1878,"agricultural_evidence":52,"reason":695},[1879,1883,1887,1891,1895,1899,1903],{"code":81,"score":21,"supported":52,"title":1880,"abstract":1881,"tags":1882},[],[890,1873,891],[1873],{"code":39,"score":21,"supported":52,"title":1884,"abstract":1885,"tags":1886},[],[1010,4,679],[4],{"code":59,"score":60,"supported":52,"title":1888,"abstract":1889,"tags":1890},[],[34,63],[34],{"code":66,"score":67,"supported":52,"title":1892,"abstract":1893,"tags":1894},[],[70,71],[],{"code":480,"score":67,"supported":52,"title":1896,"abstract":1897,"tags":1898},[],[1487,1803],[],{"code":74,"score":75,"supported":52,"title":1900,"abstract":1901,"tags":1902},[],[477],[],{"code":1565,"score":8,"supported":22,"title":1904,"abstract":1905,"tags":1906},[],[],[1538],[1908,1909],"农业土地利用 空间格局 遥感","农业土地利用 生态系统服务 可持续农业 遥感","农业土地利用空间格局遥感-4169","10.5281\u002Fzenodo.23117515",{"doi":1911,"openalex_id":1913,"authors":1914,"venue":115,"cited_by_count":90,"oa_url":1861,"card":1917,"direction":106,"ingested_from":107},"W7218853570",[1915],{"name":1916,"orcid":17},"Anjali Harshavardhan Thorat",{"tldr":1918,"method":1919,"finding":1920,"direction":106,"opportunity":1921},"从地理视角分析全球农业土地利用的空间格局与动态变化。","整合空间分析、遥感和GIS技术，结合多区域案例研究。","市场、技术、政策和环境共同驱动土地利用转变，需综合规划与适应性治理。","可结合多源遥感与机器学习，量化政策与市场对土地利用变化的非线性驱动机制。","2026-10-04T23:30:24.369006Z",{"id":1924,"title":1925,"url":1926,"summary":1927,"summary_zh":1928,"content":17,"source_name":1929,"source_url":1926,"published_at":1930,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":1931,"score_detail":1932,"sources":1934,"tags":1936,"primary_topic":1938,"secondary_topics":1939,"classification":1941,"search_phrases":1961,"slug":1964,"view_count":82,"doi":1965,"paper":1966,"created_at":1977},4102,"Application of GIS and Remote Sensing Techniques in Geospatial Mapping of Gully Statuses of an Alfisols in Yola South Local Government Area, Adamawa State","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fwjimt.v10.no1.2026.pg155.165","This research work saddled to study the application of GIS and Remote Sensing (RS) Techniques in geospatial mapping of gully erosion statuses of an Alfisols in Yola South LGA. Bole farmland was selected where expansion and development of gully was geospatially mapped out for the period of 20 years (2004-2024) at interval of five (5) years using GIS and RS techniques. The results reveal a concerning trend of increasing gully erosion, with significant growth in affected areas over the years. The highest percentage of increase occurred at 2014-2019 with about 58,069.00 m2 (65.5 %) and in 2019-2024was increased with 14,154.00 m2 (15.97 %). The total area affected in the area within the study period was 88,627.00 m2 caused by heavy rainfall and deforestation. Therefore, there are needs for effective land management practices, policy interventions, and community engagement to mitigate the effects of gully erosion.","本研究旨在探讨GIS与遥感（RS）技术在约拉南部地方政府区淋溶土冲沟侵蚀状况地理空间制图中的应用。选取博莱农田为研究区，利用GIS与遥感技术，以5年为间隔，对2004—2024年共20年间冲沟的扩展与发育进行了地理空间制图。结果表明，冲沟侵蚀呈令人担忧的加剧趋势，受影响面积逐年显著增长。增幅最大的时段为2014—2019年，约增加58 069.00 m²（65.5%）；2019—2024年增加14 154.00 m²（15.97%）。研究期内该区域受影响总面积为88 627.00 m²，主要由强降雨和森林砍伐所致。因此，需要采取有效的土地管理措施、政策干预和社区参与，以减轻冲沟侵蚀的影响。","WORLD JOURNAL OF INNOVATION AND MODERN TECHNOLOGY","2026-09-30T00:00:00Z",54,{"impact":25,"substance":26,"depth":27,"authority":67,"freshness":25,"relevant":8,"comment":1933},"基于GIS与遥感的20年沟蚀动态监测，数据具体、结论明确，但属区域案例研究，公共影响有限。",[1935],{"name":1929,"url":1926},[1937,34,36,4,37],"数字乡村",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},[1940],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":1942},{"candidates":1943,"agricultural_evidence":52},[1944,1948,1952,1956],{"code":59,"score":191,"supported":52,"title":1945,"abstract":1946,"tags":1947},[63],[34,63],[34],{"code":39,"score":28,"supported":52,"title":1949,"abstract":1950,"tags":1951},[4],[4],[4],{"code":81,"score":8,"supported":22,"title":1953,"abstract":1954,"tags":1955},[],[],[37],{"code":1957,"score":8,"supported":22,"title":1958,"abstract":1959,"tags":1960},"I6",[],[],[1937],[1962,1963],"Yola South 沟蚀 遥感","Alfisols 沟蚀 GIS 制图","YolaSouth沟蚀遥感-4102","10.56201\u002Fwjimt.v10.no1.2026.pg155.165",{"doi":1965,"openalex_id":1967,"authors":1968,"venue":1929,"cited_by_count":90,"oa_url":1971,"card":1972,"direction":106,"ingested_from":107},"W7214920253",[1969],{"name":1970,"orcid":17},"Mohammed Pakra Umar","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FWJIMT\u002FVOL. 10 NO. 1 2026\u002FAPPLICATION OF GIS AND REMOTE 156-165.pdf",{"tldr":1973,"method":1974,"finding":1975,"direction":106,"opportunity":1976},"用GIS和遥感技术对尼日利亚Yola South地区20年沟蚀动态进行空间制图与监测。","基于GIS与遥感影像，按5年间隔提取2004-2024年沟蚀范围并计算面积变化。","沟蚀面积持续扩大，2014-2019年增幅最大达65.5%，20年累计影响88,627平方米。","可结合多源高分辨率遥感与机器学习，构建沟蚀风险预警模型并评估保护性耕作等治理措施效果。","2026-10-03T23:30:37.949646Z",{"id":1979,"title":1980,"url":1981,"summary":1982,"summary_zh":1983,"content":17,"source_name":1984,"source_url":1981,"published_at":1930,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":23,"score_detail":1985,"sources":1987,"tags":1989,"primary_topic":17,"secondary_topics":1992,"classification":1993,"search_phrases":2008,"slug":2011,"view_count":82,"doi":2012,"paper":2013,"created_at":2025},4099,"Flood Hazard Assessment Using Multi-Criteria Analysis and Remote Sensing Data in Dwiridj Basin, Maysan Governorate, Southeastern Iraq","https:\u002F\u002Fdoi.org\u002F10.46717\u002Figj.2026.59.2c.7","A Flood Hazard Assessment of the Dwiridj Basin area (approximately 3,537 km2 in the Maysan governorate of southernmost Iraq was done by the use of an expert-based, multicriteria, GIS-based approach that used Geographic Information Systems for spatial analysis. The five selected controlling criteria included Elevation, Slope, Mean Monthly Precipitation (2014-2024), Drainage Density, and the Topographic Wetness Index. All criteria were normalized by the application of fuzzy membership functions, and then all normalized criteria values were combined using a Gamma Fuzzy Overlay Operator within ArcGIS to create a Flood Hazard Index. An evaluation of the flood hazard index resulted in classification into four levels of flood hazard. Area statistics were generated by each level. The results indicated that 20% (707 km²) of the basin had little or no flood hazard potential; 45% (1592 km²) had low flood hazard potential; 25% (884 km²) had moderate flood hazard potential; and 10% (354 km²) had high flood hazard potential. The resulting map offers a practical foundation for prioritizing mitigation and preparedness within the basin.","对伊拉克最南部迈桑省Dwiridj流域（面积约3,537平方公里）进行了洪水灾害评估，采用基于专家知识的多准则GIS方法，利用地理信息系统进行空间分析。所选五个控制准则包括高程、坡度、月平均降水量（2014—2024年）、河网密度和地形湿度指数。所有准则均通过模糊隶属度函数进行归一化处理，然后利用ArcGIS中的Gamma模糊叠加算子将所有归一化准则值进行组合，生成洪水灾害指数。对洪水灾害指数的评价结果划分为四个洪水灾害等级，并统计了各等级的面积。结果表明，流域内20%（707平方公里）的区域洪水灾害潜力很小或没有；45%（1,592平方公里）的区域洪水灾害潜力低；25%（884平方公里）的区域洪水灾害潜力中等；10%（354平方公里）的区域洪水灾害潜力高。所生成的地图为流域内减灾和备灾工作的优先级排序提供了实用基础。","Iraqi Geological Journal",{"impact":25,"substance":26,"depth":191,"authority":28,"freshness":25,"relevant":8,"comment":1986},"基于GIS与遥感的多准则洪水风险评估，方法规范、数据详实，对农业防灾减灾有参考价值，但属区域性研究，公共影响有限。",[1988],{"name":1984,"url":1981},[34,1990,4,1991],"洪水风险评估","伊拉克农业",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":1994},{"candidates":1995,"agricultural_evidence":22,"reason":284},[1996,2000,2004],{"code":39,"score":21,"supported":52,"title":1997,"abstract":1998,"tags":1999},[],[55,1010,4,679,56],[4],{"code":59,"score":29,"supported":52,"title":2001,"abstract":2002,"tags":2003},[63],[],[34],{"code":480,"score":8,"supported":22,"title":2005,"abstract":2006,"tags":2007},[],[],[1990],[2009,2010],"Dwiridj Basin 洪水风险","Maysan 遥感 洪水评估","DwiridjBasin洪水风险-4099","10.46717\u002Figj.2026.59.2c.7",{"doi":2012,"openalex_id":2014,"authors":2015,"venue":1984,"cited_by_count":90,"oa_url":2019,"card":2020,"direction":106,"ingested_from":107},"W7214908176",[2016],{"name":2017,"orcid":2018},"Yasir Aldabbagh","https:\u002F\u002Forcid.org\u002F0009-0009-2772-7596","https:\u002F\u002Figj-iraq.org\u002Figj\u002Findex.php\u002Figj\u002Farticle\u002Fdownload\u002F3374\u002F2521",{"tldr":2021,"method":2022,"finding":2023,"direction":106,"opportunity":2024},"用多准则GIS与遥感数据评估伊拉克Dwiridj流域洪水风险并分级制图。","模糊隶属度归一化与Gamma模糊叠加，结合高程、坡度、降水等5因子。","流域10%面积高洪水风险，25%中等，45%低，20%极低或无风险。","可引入时序遥感与机器学习动态更新风险图，并耦合农业土地利用评估灾损。","2026-10-03T23:30:37.632997Z",{"id":2027,"title":2028,"url":2029,"summary":2030,"summary_zh":2031,"content":17,"source_name":2032,"source_url":2029,"published_at":1930,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":866,"score_detail":2033,"sources":2035,"tags":2037,"primary_topic":17,"secondary_topics":2040,"classification":2041,"search_phrases":2062,"slug":2065,"view_count":82,"doi":2066,"paper":2067,"created_at":2090},4098,"Monitoring Sustainable Rural Tourism Development in Post-Conflict Areas Using Remote Sensing and Geospatial Analysis","https:\u002F\u002Fdoi.org\u002F10.26493\u002F1854-6935.24.433-464","This study examines how rural tourism supports sustainable development, economic recovery, social stability, and cultural preservation in post-conflict regions, using Transcarpathia, Ukraine, as a case study for 2022–2024. It applies a mixed-methods approach combining satellite remote sensing, GIS-based spatial analysis, and socio-economic indicators to assess land-use change, infrastructure recovery, ecological stability, and socio-economic resilience. Unlike existing geospatial monitoring studies that focus on single dimensions (e.g. land cover or tourist flows) in stable environments. This research introduces a theoretically grounded, multi-dimensional framework that integrates environmental, infrastructural, socio-economic, and digital indicators into a unified composite sustainability index, enabling continuous monitoring where conventional field data collection is constrained. The findings indicate notable recovery and resilience: tourism-related infrastructure rebounded strongly, ecological indicators improved over time, and digital accessibility expanded substantially, supporting tourism development despite ongoing post-conflict challenges. The study offers a novel integrated geospatial framework for monitoring sustainable rural tourism transitions in data-constrained and crisis-affected territories.","本研究以乌克兰外喀尔巴阡（Transcarpathia）为案例，考察2022—2024年期间乡村旅游如何促进冲突后地区的可持续发展、经济复苏、社会稳定与文化保护。研究采用混合方法，结合卫星遥感、基于GIS的空间分析和社会经济指标，评估土地利用变化、基础设施恢复、生态稳定性及社会经济韧性。与现有聚焦于稳定环境中单一维度（如土地覆盖或游客流量）的地理空间监测研究不同，本研究提出了一个具有理论根基的多维框架，将环境、基础设施、社会经济和数字指标整合为统一的复合可持续性指数，从而在传统实地数据采集受限的情况下实现持续监测。研究结果表明了显著的恢复与韧性：旅游相关基础设施强劲反弹，生态指标随时间改善，数字可及性大幅扩展，在持续面临冲突后挑战的情况下支撑了旅游发展。本研究为在数据受限和受危机影响的地区监测可持续乡村旅游转型提供了一个新颖的综合地理空间框架。","Managing Global Transitions",{"impact":28,"substance":740,"depth":26,"authority":660,"freshness":25,"relevant":8,"comment":2034},"该研究提出融合遥感、GIS与社会经济指标的多维可持续性指数框架，方法新颖且对数据受限地区有参考价值，但案例局限于乌克兰局部区域，对国内三农信息化实践的直接影响力有限。",[2036],{"name":2032,"url":2029},[1937,2038,2039,457,4],"可持续发展","乡村旅游",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":2042},{"candidates":2043,"agricultural_evidence":52,"reason":695},[2044,2050,2054,2058],{"code":2045,"score":191,"supported":52,"title":2046,"abstract":2048,"tags":2049},"G4",[2047],"rural tourism",[2039,2047],[2039],{"code":59,"score":191,"supported":52,"title":2051,"abstract":2052,"tags":2053},[63],[34,63],[457],{"code":39,"score":21,"supported":52,"title":2055,"abstract":2056,"tags":2057},[],[1010,4,679],[4],{"code":1957,"score":8,"supported":22,"title":2059,"abstract":2060,"tags":2061},[],[],[1937],[2063,2064],"遥感 GIS 可持续乡村旅游","可持续发展 乡村旅游 数字乡村 遥感监测","遥感GIS可持续乡村旅游-4098","10.26493\u002F1854-6935.24.433-464",{"doi":2066,"openalex_id":2068,"authors":2069,"venue":2032,"cited_by_count":90,"oa_url":2084,"card":2085,"direction":106,"ingested_from":107},"W7214899546",[2070,2072,2074,2076,2079,2081],{"name":2071,"orcid":17},"Valeriia Shcherbak",{"name":2073,"orcid":17},"Oleksandr Dorokhov",{"name":2075,"orcid":17},"Viktoriia Riashchenko",{"name":2077,"orcid":2078},"Valentina Djakona","https:\u002F\u002Forcid.org\u002F0000-0002-9199-3559",{"name":2080,"orcid":17},"Oleksii Yermolenko",{"name":2082,"orcid":2083},"Maja Meško","https:\u002F\u002Forcid.org\u002F0000-0001-5615-9801","https:\u002F\u002Fojs.upr.si\u002Ffm\u002Farticle\u002Fview\u002F270\u002F115",{"tldr":2086,"method":2087,"finding":2088,"direction":106,"opportunity":2089},"用遥感与GIS构建多维可持续指数，监测乌克兰战后乡村旅游业恢复。","卫星遥感、GIS空间分析与社经指标，构建复合可持续指数。","旅游基础设施强劲反弹，生态改善，数字可及性扩大，支撑战后恢复。","可将该多维遥感框架迁移至数据受限的乡村农业旅游与生计恢复监测研究。","2026-10-03T23:30:37.512385Z",{"id":2092,"title":2093,"url":2094,"summary":2095,"summary_zh":17,"content":17,"source_name":2096,"source_url":2094,"published_at":2097,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":1481,"score_detail":2098,"sources":2100,"tags":2102,"primary_topic":17,"secondary_topics":2105,"classification":2106,"search_phrases":2121,"slug":2124,"view_count":8,"doi":2125,"paper":2126,"created_at":2132},4095,"Identification of priority areas using GIS and remote sensing for ecological restoration: contributions to the conservation of the Doradito Tucumano (Tucumán – Argentina)","https:\u002F\u002Fdoi.org\u002F10.19137\u002Fhuellas-2026-3015","Tucumano (Tucumán -Argentina)","Huellas","2026-10-01T00:00:00Z",{"impact":25,"substance":26,"depth":190,"authority":67,"freshness":29,"relevant":8,"comment":2099},"GIS与遥感用于生态修复优先区识别，方法有参考价值，但属区域鸟类保护研究，与农业信息化关联偏弱，公共影响有限。",[2101],{"name":2096,"url":2094},[34,2103,4,2104],"生态修复","生物多样性保护",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":2107},{"candidates":2108,"agricultural_evidence":22,"reason":284},[2109,2113,2117],{"code":59,"score":29,"supported":52,"title":2110,"abstract":2111,"tags":2112},[63],[],[34],{"code":39,"score":29,"supported":52,"title":2114,"abstract":2115,"tags":2116},[4],[],[4],{"code":81,"score":8,"supported":22,"title":2118,"abstract":2119,"tags":2120},[],[],[2103],[2122,2123],"阿根廷 Tucumán Doradito Tucumano","GIS 遥感 生态修复","阿根廷TucumánDoraditoTucumano-4095","10.19137\u002Fhuellas-2026-3015",{"doi":2125,"openalex_id":2127,"authors":2128,"venue":2096,"cited_by_count":90,"oa_url":2094,"card":17,"direction":106,"ingested_from":107},"W7216242382",[2129],{"name":2130,"orcid":2131},"Andrea Margarita Díaz","https:\u002F\u002Forcid.org\u002F0009-0000-0126-0400","2026-10-03T23:30:35.510515Z",{"id":2134,"title":2135,"url":2136,"summary":2137,"summary_zh":2138,"content":17,"source_name":2096,"source_url":2139,"published_at":2097,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2140,"score_detail":2141,"sources":2143,"tags":2145,"primary_topic":2147,"secondary_topics":2148,"classification":2152,"search_phrases":2167,"slug":2170,"view_count":82,"doi":2171,"paper":2172,"created_at":2181},4093,"Identificação de áreas prioritárias utilizando SIG e sensoriamento remoto para restauração ecológica: contribuições para a conservação do Doradito Tucumano (Tucumán – Argentina)","https:\u002F\u002Fdoi.org\u002F10.19137\u002F\u002Fhuellas-2026-3015","Landscape transformation driven by agricultural frontier expansion has intensified the fragmentation of habitats used by the Tucumán Doradito (Pseudocolopteryx dinelliana), a Near Threatened (NT) species, reducing ecological connectivity and the availability of suitable habitats in Tucumán Province, Argentina. This study aimed to identify priority areas for ecological restoration through the integration of Geographic Information Systems (GIS), remote sensing, and multicriteria analysis. Species occurrence records from GBIF, EcoRegistros, and the National Biodiversity Information System were combined with the IUCN potential distribution, Landsat 8\u002F9 imagery, the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI), and a Digital Elevation Model provided by the National Geographic Institute. Map algebra and suitability and exclusion criteria were applied to identify 50,481 ha of high-priority restoration areas, representing 2.2% of the provincial territory. The results indicate that the departments of Graneros, Leales and Simoca contain 55.9% of the priority area, constituting the main core for restoring landscape connectivity. The proposed methodology provides an objective framework to support territorial planning and prioritize ecological restoration actions aimed at strengthening the conservation of the Tucumán Doradito in highly transformed landscapes.","农业前沿扩张驱动的景观转变加剧了图库曼多拉迪托鸟（Pseudocolopteryx dinelliana）所利用生境的破碎化，该物种为近危（NT）物种，导致阿根廷图库曼省的生态连通性和适宜生境可用性降低。本研究旨在通过整合地理信息系统（GIS）、遥感和多准则分析，确定生态恢复的优先区域。将来自GBIF、EcoRegistros和国家生物多样性信息系统的物种分布记录与IUCN潜在分布区、Landsat 8\u002F9影像、归一化植被指数（NDVI）、归一化水体指数（NDWI）以及国家地理研究所提供的数字高程模型相结合。应用地图代数以及适宜性和排除标准，确定了50,481公顷的高优先级恢复区域，占全省面积的2.2%。结果表明，Graneros、Leales和Simoca等省辖区包含优先区域的55.9%，构成了恢复景观连通性的核心区域。所提出的方法为支持国土空间规划、优先开展旨在加强高度转变景观中图库曼多拉迪托鸟保护的生态恢复行动提供了客观框架。","https:\u002F\u002Fcerac.unlpam.edu.ar\u002Findex.php\u002Findex\u002Farticle\u002Fview\u002F9861",59,{"impact":25,"substance":119,"depth":120,"authority":67,"freshness":25,"relevant":8,"comment":2142},"阿根廷图库曼省利用GIS与遥感识别生态修复优先区的论文，方法可借鉴但属区域案例，公共价值有限。",[2144],{"name":2096,"url":2139},[34,2103,890,4,2146],"景观连通性",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[2149],{"code":81,"slug":891,"name":2150,"path":2151,"parent_code":942},"生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity",{"status":46,"locked":22,"version":47,"method":48,"evidence":2153},{"candidates":2154,"agricultural_evidence":52},[2155,2159,2163],{"code":39,"score":21,"supported":52,"title":2156,"abstract":2157,"tags":2158},[],[55,4,56],[4],{"code":81,"score":25,"supported":52,"title":2160,"abstract":2161,"tags":2162},[],[890,891],[2103,890],{"code":59,"score":60,"supported":52,"title":2164,"abstract":2165,"tags":2166},[],[34,63],[34],[2168,2169],"Tucumán Doradito 生态修复","Landsat NDVI 优先区识别","TucumánDoradito生态修复-4093","10.19137\u002F\u002Fhuellas-2026-3015",{"doi":2171,"openalex_id":2173,"authors":2174,"venue":2096,"cited_by_count":90,"oa_url":2139,"card":2176,"direction":106,"ingested_from":107},"W7216132579",[2175],{"name":2130,"orcid":2131},{"tldr":2177,"method":2178,"finding":2179,"direction":106,"opportunity":2180},"结合GIS、遥感和多准则分析，识别阿根廷图库曼省优先生态恢复区以保护近危鸟类。","使用GBIF等物种记录、Landsat影像、NDVI、NDWI和DEM进行地图代","识别出50,481公顷高优先级恢复区，占省域2.2%，集中在Graneros、Leales和Simo","可延伸至农业景观中多物种连通性保护规划，或结合时序遥感动态评估恢复成效。","2026-10-03T23:30:35.383506Z",{"id":2183,"title":2184,"url":2185,"summary":2186,"summary_zh":2187,"content":17,"source_name":657,"source_url":2185,"published_at":2188,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2189,"score_detail":2190,"sources":2192,"tags":2194,"primary_topic":2198,"secondary_topics":2199,"classification":2202,"search_phrases":2225,"slug":2228,"view_count":833,"doi":2229,"paper":2230,"created_at":2259},4085,"Seasonal Snow Water Resources and Spring Runoff Harvesting Potential in the North Kazakhstan Region: An Integrated Remote Sensing and GIS-Based Multi-Criteria Assessment","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fearth7050163","Seasonal snow is a critical water resource in Northern Kazakhstan, where spring snowmelt dominates surface runoff and agricultural water supply. However, traditional rainwater harvesting frameworks often neglect snow water equivalent (SWE), limiting their applicability in cold, snow-dominated steppe environments. This study develops an integrated remote sensing and GIS-based approach to identify potential sites for spring runoff harvesting. Using Sentinel-2 imagery, snow cover fraction (SCF) was derived and combined with a digital elevation model (DEM) to estimate snow depth through a quadratic regression model, validated against in situ data from 23 meteorological stations. Snow water equivalent was then calculated by incorporating field-measured snow density. Alongside SWE, six additional parameters—slope, drainage density, land use\u002Fland cover (LULC), and soil texture (sand, silt, clay)—were integrated within an Analytical Hierarchy Process (AHP) multi-criteria decision analysis. Results show that SWE, drainage density, and LULC collectively contributed 75% of the weight in site suitability, underscoring their dominant role in snowmelt-driven hydrology. The final suitability map indicates that 28.03% of the region falls into the “Very High” class, concentrated in central and northwestern districts. Developing just 30% of these potential zones could yield approximately 4.2 × 108 m3 of usable meltwater, supporting up to 105,000 ha under full irrigation or 280,000 ha under deficit irrigation. The study demonstrates that integrating high-resolution SWE with MCDA provides a scalable framework for enhancing agricultural resilience, mitigating floods, and strengthening water security in cold, semi-arid landscapes.","季节性积雪是哈萨克斯坦北部的重要水资源，春季融雪主导着地表径流和农业供水。然而，传统的雨水收集框架往往忽视雪水当量（SWE），限制了其在寒冷、以积雪为主的草原环境中的适用性。本研究开发了一种集成遥感和GIS的方法，用于识别春季径流收集的潜在场址。利用Sentinel-2影像提取积雪覆盖率（SCF），并结合数字高程模型（DEM）通过二次回归模型估算雪深，利用23个气象站的实地数据进行验证。随后，结合实地测量的雪密度计算雪水当量。除SWE外，还将坡度、河网密度、土地利用\u002F土地覆盖（LULC）以及土壤质地（砂、粉砂、黏土）等六个附加参数纳入层次分析法（AHP）多准则决策分析。结果表明，SWE、河网密度和LULC在场地适宜性评价中合计贡献了75%的权重，凸显了它们在融雪驱动水文中的主导作用。最终适宜性图显示，该区域28.03%的面积属于“极高”等级，集中在中部和西北部地区。仅开发这些潜在区域的30%，即可产生约4.2 × 10⁸ m³的可用融水，可支持多达105,000公顷的充分灌溉或280,000公顷的亏缺灌溉。本研究表明，将高分辨率SWE与多准则决策分析相结合，为增强农业韧性、减轻洪水和加强寒冷半干旱地区的水安全提供了一个可扩展的框架。","2026-10-02T00:00:00Z",77,{"impact":190,"substance":740,"depth":26,"authority":660,"freshness":29,"relevant":8,"comment":2191},"该研究将遥感与GIS多准则评估结合，量化了北哈萨克斯坦融雪水资源与灌溉潜力，方法新颖、数据扎实，对寒区农业水资源管理有参考价值，但地域性较强，属细分领域进展。",[2193],{"name":657,"url":2185},[2195,2196,34,4,2197],"农业水资源","哈萨克斯坦","融雪灌溉",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},[2200,2201],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"code":74,"slug":674,"name":940,"path":941,"parent_code":942},{"status":46,"locked":22,"version":47,"method":48,"evidence":2203},{"candidates":2204,"agricultural_evidence":52},[2205,2209,2213,2217,2221],{"code":59,"score":191,"supported":52,"title":2206,"abstract":2207,"tags":2208},[63],[34,63],[34],{"code":39,"score":28,"supported":52,"title":2210,"abstract":2211,"tags":2212},[4],[4],[4],{"code":74,"score":21,"supported":52,"title":2214,"abstract":2215,"tags":2216},[],[78,477,674,957],[2195],{"code":66,"score":67,"supported":52,"title":2218,"abstract":2219,"tags":2220},[],[70,71],[],{"code":480,"score":75,"supported":52,"title":2222,"abstract":2223,"tags":2224},[],[483],[],[2226,2227],"北哈萨克斯坦 融雪 灌溉潜力","Sentinel-2 雪水当量 遥感","北哈萨克斯坦融雪灌溉潜力-4085","10.3390\u002Fearth7050163",{"doi":2229,"openalex_id":2231,"authors":2232,"venue":657,"cited_by_count":90,"oa_url":2185,"card":2254,"direction":106,"ingested_from":107},"W7216430083",[2233,2236,2239,2241,2243,2245,2248,2251],{"name":2234,"orcid":2235},"Zhanassyl Teleubay","https:\u002F\u002Forcid.org\u002F0000-0003-4783-5489",{"name":2237,"orcid":2238},"Erkin Ussalinov","https:\u002F\u002Forcid.org\u002F0000-0003-1907-9532",{"name":2240,"orcid":17},"Laura Ryskulbekova",{"name":2242,"orcid":17},"Asset Arystanov",{"name":2244,"orcid":17},"Ibragim Seitassanov",{"name":2246,"orcid":2247},"Улжан Онласын","https:\u002F\u002Forcid.org\u002F0000-0001-5789-5464",{"name":2249,"orcid":2250},"Nuray Kutymova","https:\u002F\u002Forcid.org\u002F0009-0000-7214-1708",{"name":2252,"orcid":2253},"Farabi Yermekov","https:\u002F\u002Forcid.org\u002F0000-0002-0290-3866",{"tldr":2255,"method":2256,"finding":2257,"direction":106,"opportunity":2258},"结合遥感与GIS评估哈萨克斯坦北部季节性雪水资源及春季径流收集潜力。","Sentinel-2与DEM估算雪深和SWE，结合AHP多准则决策分析选址。","SWE、河网密度和土地利用贡献75%权重，28%区域为极高适宜区。","可将SWE驱动的选址框架推广至其他寒旱区，并耦合气候情景与灌溉效率优化。","2026-10-03T23:30:32.427699Z",{"id":2261,"title":2262,"url":2263,"summary":2264,"summary_zh":2265,"content":17,"source_name":2266,"source_url":2263,"published_at":2097,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2267,"score_detail":2268,"sources":2270,"tags":2272,"primary_topic":2274,"secondary_topics":2275,"classification":2277,"search_phrases":2305,"slug":2308,"view_count":150,"doi":2309,"paper":2310,"created_at":2329},4027,"Groundwater Potential Zonation of Unchehra Watershed, Central India using AHP, Remote Sensing, and GIS Techniques","https:\u002F\u002Fdoi.org\u002F10.17491\u002Fjgsi.2026.174637","ABSTRACT Groundwater is the primary source of domestic and agricultural water in the semi-arid regions of central India. Despite receiving moderate annual rainfall, Unchehra watershed experiences seasonal water shortages, especially during summer, highlighting the need for scientific assessment of groundwater resources. This study delineates groundwater potential zones (GWPZs) in the Unchehra watershed using an integrated Remote Sensing (RS), Geographic Information System (GIS), and Analytical Hierarchy Process (AHP) approach. Seven major factors influencing groundwater occurrence lineament density, geology, land use and land cover (LULC), drainage density, geomorphology, slope and soil type were considered in the analysis. Spatial thematic layers for these parameters were prepared from satellite imagery and Digital Elevation Model (DEM) data using ArcGIS. The relative importance of each factor and its classes was determined through AHP, providing a systematic weighting scheme for groundwater potential assessment. The weighted layers were integrated to generate a groundwater potential zonation map. The resulting map classified the watershed into five groundwater potential zones: very low, low, moderate, high, and very high. The analysis revealed that 7.88% of the watershed falls under very low potential, while significant portions of the area exhibit moderate (28.07%) to very high (22.61%) groundwater potential. To assess the reliability of the generated model, validation was carried out using 41 randomly selected dug wells and Receiver Operating Characteristic (ROC) curve analysis. The near-zero Consistency Ratio (CR) confirms the reliability of the AHP weighting scheme, while the Area Under the Curve (AUC) value of 0.763 indicates good predictive accuracy of the groundwater potential model. The identified high and very high groundwater potential zones are suitable for groundwater development and artificial recharge measures such as check dams, percolation tanks, and recharge wells. The integrated RS-GIS-AHP framework developed in this study provides a reliable decision-support tool for groundwater exploration, recharge planning, and sustainable groundwater management in Unchehra watershed and similar hydrogeological settings.","摘要 地下水是印度中部半干旱地区生活用水和农业用水的主要来源。尽管Unchehra流域年降水量适中，但仍面临季节性缺水问题，尤其是在夏季，这凸显了对地下水资源进行科学评估的必要性。本研究采用遥感（RS）、地理信息系统（GIS）和层次分析法（AHP）相结合的方法，对Unchehra流域的地下水潜力区（GWPZs）进行了划分。分析中考虑了影响地下水赋存的七个主要因素：线性构造密度、地质、土地利用与土地覆盖（LULC）、河网密度、地貌、坡度和土壤类型。利用ArcGIS从卫星影像和数字高程模型（DEM）数据中制备了这些参数的空间专题图层。通过AHP确定各因素及其类别的相对重要性，为地下水潜力评估提供了系统化的权重方案。将加权图层进行叠加整合，生成了地下水潜力分区图。所得图件将流域划分为五个地下水潜力区：极低、低、中等、高和极高。分析表明，流域面积的7.88%属于极低潜力区，而相当部分区域表现出中等（28.07%）至极高（22.61%）的地下水潜力。为评估所生成模型的可靠性，利用41口随机选取的民井和受试者工作特征（ROC）曲线分析进行了验证。接近零的一致性比率（CR）证实了AHP权重方案的可靠性，而曲线下面积（AUC）值为0.763表明地下水潜力模型具有良好的预测精度。所识别的高和极高地下水潜力区适宜进行地下水开发和人工补给措施，如拦水坝、渗滤池和回灌井。本研究开发的RS-GIS-AHP集成框架为Unchehra流域及类似水文地质条件下的地下水勘探、补给规划和可持续地下水管理提供了可靠的决策支持工具。","Journal of the Geological Society of India",66,{"impact":25,"substance":119,"depth":120,"authority":660,"freshness":25,"relevant":8,"comment":2269},"方法扎实、验证可靠的区域地下水潜力评估论文，对农业水资源管理有参考价值，但属印度区域研究，公共影响有限。",[2271],{"name":2266,"url":2263},[34,665,4,2273,745],"印度农业",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[2276],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":2278},{"candidates":2279,"agricultural_evidence":52},[2280,2284,2288,2292,2296,2300],{"code":39,"score":26,"supported":52,"title":2281,"abstract":2282,"tags":2283},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":2285,"abstract":2286,"tags":2287},[63],[34,63],[34],{"code":66,"score":67,"supported":52,"title":2289,"abstract":2290,"tags":2291},[],[70,71],[],{"code":74,"score":833,"supported":52,"title":2293,"abstract":2294,"tags":2295},[],[477],[745,665],{"code":480,"score":75,"supported":52,"title":2297,"abstract":2298,"tags":2299},[],[483],[],{"code":2301,"score":8,"supported":22,"title":2302,"abstract":2303,"tags":2304},"J3",[],[],[2273],[2306,2307],"地下水潜力 水资源管理 印度农业 遥感","地下水潜力 水资源管理","地下水潜力水资源管理印度农业遥感-4027","10.17491\u002Fjgsi.2026.174637",{"doi":2309,"openalex_id":2311,"authors":2312,"venue":2266,"cited_by_count":90,"oa_url":17,"card":2324,"direction":106,"ingested_from":107},"W7215068088",[2313,2315,2317,2319,2321],{"name":2314,"orcid":17},"Rabindra Nath Tiwari",{"name":2316,"orcid":17},"Brahmanand Sharma",{"name":2318,"orcid":17},"Sarvesh Kumar Patel",{"name":2320,"orcid":17},"Aditya Singh Baghel",{"name":2322,"orcid":2323},"Ashish Kumar Mishra","https:\u002F\u002Forcid.org\u002F0000-0002-9953-4576",{"tldr":2325,"method":2326,"finding":2327,"direction":106,"opportunity":2328},"用RS、GIS与AHP集成方法划分印度Unchehra流域地下水潜力区并验证精度。","基于遥感与DEM提取7个因子，AHP加权叠加，41口井与ROC验证。","流域分五级潜力区，高与极高潜力占22.61%，模型AUC达0.763，精度良好。","可将该框架与实时灌溉需水、作物布局耦合，支撑半干旱区精准补灌与地下水回补选址。","2026-10-02T23:30:24.566714Z",{"id":2331,"title":2332,"url":2333,"summary":2334,"summary_zh":2335,"content":17,"source_name":324,"source_url":2333,"published_at":1930,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":450,"score_detail":2336,"sources":2338,"tags":2340,"primary_topic":2343,"secondary_topics":2344,"classification":2347,"search_phrases":2385,"slug":2388,"view_count":8,"doi":2389,"paper":2390,"created_at":2401},3901,"Geospatial analysis of irrigation suitability in Nigeria using remote sensing and GIS","https:\u002F\u002Fdoi.org\u002F10.53030\u002Ftjags.1937471","This research offers a comprehensive geospatial evaluation of land suitability for irrigation across Nigeria. It leverages 2020 Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, processed within the Google Earth Engine (GEE) cloud-based computational environment. Given growing concerns about food security and climate variability, ascertaining areas amenable to irrigation is paramount for fostering sustainable agricultural development within Nigeria. This investigation integrated multi-temporal remote sensing observations, including the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and Normalized Difference Water Index - NDWI, to construct an Irrigation Suitability Index (ISI). These datasets underwent analysis at a 500-meter spatial resolution, encompassing the entirety of the nation. Weighted overlay analysis, performed within the GEE environment, generated a nationwide map delineating irrigation potential across five distinct categories: Very Low, Low, Moderate, High, and Very High suitability. The findings reveal suitability scores ranging from a minimum of 0.11 (very low) to a maximum of 1 (very high). Specifically, northern Nigerian states such as Sokoto, Kebbi, Yobe, and Borno demonstrated high to very high suitability. In contrast, southern states, including Lagos, Rivers, Cross River, and Delta, were characterized by very low suitability. The study underscores significant geographical disparities, particularly in arid northern regions which experience greater constraints due to lower precipitation and elevated evapotranspiration. These findings offer actionable directives for agricultural planners, policymakers, and stakeholders seeking to enhance irrigation capacity and strengthen food security resilience amidst evolving climatic conditions.","本研究对尼日利亚全国灌溉土地适宜性进行了综合地理空间评估。研究利用2020年中分辨率成像光谱仪（MODIS）卫星数据，在谷歌地球引擎（GEE）云端计算环境中进行处理。鉴于粮食安全和气候变率日益受到关注，确定适宜灌溉的区域对于促进尼日利亚可持续农业发展至关重要。本研究整合了多时相遥感观测数据，包括归一化植被指数（NDVI）、地表温度（LST）和归一化水体指数（NDWI），以构建灌溉适宜性指数（ISI）。这些数据集以500米空间分辨率进行分析，覆盖全国范围。在GEE环境中进行的加权叠加分析生成了全国灌溉潜力分布图，划分为五个类别：极低、低、中等、高和极高适宜性。研究结果显示，适宜性评分从最低0.11（极低）到最高1（极高）不等。具体而言，尼日利亚北部各州如索科托、凯比、约贝和博尔诺表现出高至极高适宜性。相比之下，南部各州包括拉各斯、河流州、十字河州和三角洲州则以极低适宜性为特征。研究强调了显著的地理差异，特别是干旱的北部地区因降水量较低和蒸散量较高而面临更大限制。这些发现为农业规划者、政策制定者和利益相关者提供了可操作的指导，以在气候条件不断变化的情况下增强灌溉能力并提升粮食安全韧性。",{"impact":26,"substance":452,"depth":120,"authority":660,"freshness":25,"relevant":8,"comment":2337},"基于MODIS与GEE的全国尺度灌溉适宜性制图，方法规范、结论具体，对农业规划有参考价值，但属他国案例，国内落地性有限。",[2339],{"name":324,"url":2333},[2341,225,34,4,2342],"数字农业","灌溉适宜性",{"code":74,"slug":674,"name":940,"path":941,"parent_code":942},[2345,2346],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":2348},{"candidates":2349,"agricultural_evidence":52},[2350,2355,2359,2363,2367,2371,2375,2381],{"code":74,"score":120,"supported":52,"title":2351,"abstract":2352,"tags":2354},[674],[78,674,2353],"evapotranspiration",[],{"code":59,"score":191,"supported":52,"title":2356,"abstract":2357,"tags":2358},[63],[34,63],[34],{"code":39,"score":29,"supported":52,"title":2360,"abstract":2361,"tags":2362},[4],[],[4],{"code":222,"score":60,"supported":52,"title":2364,"abstract":2365,"tags":2366},[],[225,226],[225],{"code":480,"score":75,"supported":52,"title":2368,"abstract":2369,"tags":2370},[],[483],[],{"code":1565,"score":75,"supported":52,"title":2372,"abstract":2373,"tags":2374},[],[1538],[],{"code":2376,"score":75,"supported":52,"title":2377,"abstract":2378,"tags":2380},"J1",[],[2379],"农业规划",[],{"code":894,"score":8,"supported":22,"title":2382,"abstract":2383,"tags":2384},[],[],[2341],[2386,2387],"尼日利亚 灌溉适宜性 遥感","Google Earth Engine 灌溉","尼日利亚灌溉适宜性遥感-3901","10.53030\u002Ftjags.1937471",{"doi":2389,"openalex_id":2391,"authors":2392,"venue":17,"cited_by_count":90,"oa_url":17,"card":2396,"direction":106,"ingested_from":107},"W7214955379",[2393],{"name":2394,"orcid":2395},"Emmanuel M. Menegbo","https:\u002F\u002Forcid.org\u002F0000-0002-6694-3226",{"tldr":2397,"method":2398,"finding":2399,"direction":106,"opportunity":2400},"用遥感与GIS评估尼日利亚全国灌溉适宜性并绘制五级分区图。","2020年MODIS数据在GEE中计算NDVI、LST、NDWI并加权叠加。","北部各州适宜性高，南部低，全国适宜性得分0.11至1。","可结合土壤、地下水与作物需水数据，将静态适宜性图升级为动态灌溉决策支持系统。","2026-10-01T23:30:29.159371Z",{"id":2403,"title":2404,"url":2405,"summary":2406,"summary_zh":2407,"content":17,"source_name":115,"source_url":2405,"published_at":1930,"category":20,"cover_url":17,"hotness":1647,"is_selected":22,"score":2408,"score_detail":2409,"sources":2411,"tags":2415,"primary_topic":2418,"secondary_topics":2419,"classification":2421,"search_phrases":2436,"slug":2439,"view_count":8,"doi":2440,"paper":2441,"created_at":2457},3895,"Analysis Of Changes In Land Use And Land Cover In Pune City Over A Decade Using Geospatial Techniques.","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23053479","Abstract Land use and land cover (LULC) changes play a significant role in reflecting natural and anthropogenic environmental changes. In this study, changes in 'Land Use and Land Cover' (LULC) in Pune city for the period 2015-2025 have been analysed using the techniques of 'Remote Sensing' and 'Geographic Information System' (GIS). The May 2015 and May 2025 30 m resolution Landsat 08 satellite images were used. For LULC classification, the 'Supervised Maximum Likelihood Classification' method was used, resulting in 5 major LULC classes: built-up land, barren land, and agricultural land, vegetation, and water bodies. More than 100 'training samples' were taken for each land cover type to improve classification accuracy. The findings of the study show that there was a considerable shift in the spatial distribution of LULC in this decade. Built-up land increased from 154.48 sq. km (30.48%) in 2015 to 292.26 sq. km (57.86%) in 2025, representing an increase of approximately 137.78 sq. km. Conversely, the area of barren land decreased from 203.94 sq. km (40.24%) to 106.93 sq. km (21.10%). The amount of agricultural land has reduced from 44.39 sq. km (8.75%) to 18.93 sq. km (3.72%), indicating that agricultural land has been converted for urbanisation on a large scale. Regarding vegetation cover, 85.91 sq. km showed a marginal decrease from 16.95% to 15.58%, whereas the area of water bodies decreased from 18.13 sq. km (3.58%) to 10.77 sq. km (2.12%). The results show the rapid growth of Pune city during the study period, which is mainly observed in the loss or transformation of barren land, agricultural land and water bodies. The study shows the usefulness of using Landsat data, ‘supervised maximum likelihood classification’, GIS and ‘change detection' techniques for tracking long-term urban growth and environmental changes. The results of this research can help urban planners and decision makers in formulating policies for sustainable land use and in safeguarding environmentally sensitive areas.","摘要 土地利用与土地覆盖（LULC）变化在反映自然与人为环境变化方面发挥着重要作用。本研究利用遥感（Remote Sensing）和地理信息系统（GIS）技术，分析了浦那市2015—2025年期间土地利用与土地覆盖（LULC）的变化。研究使用了2015年5月和2025年5月分辨率为30米的Landsat 08卫星影像。在LULC分类中，采用了监督最大似然分类（Supervised Maximum Likelihood Classification）方法，最终得到5个主要LULC类别：建设用地、裸地、农用地、植被和水体。为提高分类精度，每种土地覆盖类型均选取了100个以上的训练样本（training samples）。研究结果表明，在这十年间，LULC的空间分布发生了显著变化。建设用地从2015年的154.48平方公里（30.48%）增加到2025年的292.26平方公里（57.86%），增加了约137.78平方公里。相反，裸地面积从203.94平方公里（40.24%）减少到106.93平方公里（21.10%）。农用地面积从44.39平方公里（8.75%）减少到18.93平方公里（3.72%），表明农用地已大规模转化为城市化用地。植被覆盖方面，85.91平方公里略有下降，从16.95%降至15.58%；水体面积则从18.13平方公里（3.58%）减少到10.77平方公里（2.12%）。结果表明，研究期间浦那市快速扩张，主要体现在裸地、农用地和水体的减少或转变上。研究表明，利用Landsat数据、监督最大似然分类、GIS和变化检测（change detection）技术对于追踪长期城市增长与环境变化具有重要价值。本研究结果可帮助城市规划者和决策者制定可持续土地利用政策，并保护环境敏感区域。",65,{"impact":25,"substance":119,"depth":190,"authority":28,"freshness":29,"relevant":8,"comment":2410},"基于Landsat遥感与GIS的浦那市十年土地利用变化研究，数据翔实、结论明确，对农业用地流失与城市扩张监测有参考价值，但属区域案例研究，公共影响有限。",[2412,2413],{"name":115,"url":2405},{"name":115,"url":2414},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23053480",[34,35,2416,4,2417],"Landsat","城市化",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[2420],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":2422},{"candidates":2423,"agricultural_evidence":52},[2424,2428,2432],{"code":39,"score":21,"supported":52,"title":2425,"abstract":2426,"tags":2427},[],[55,4,56],[4],{"code":59,"score":25,"supported":52,"title":2429,"abstract":2430,"tags":2431},[],[34,63],[2416,34],{"code":81,"score":8,"supported":22,"title":2433,"abstract":2434,"tags":2435},[],[],[35],[2437,2438],"土地利用 城市化 遥感 Landsat","土地利用 城市化","土地利用城市化遥感Landsat-3895","10.5281\u002Fzenodo.23053479",{"doi":2440,"openalex_id":2442,"authors":2443,"venue":115,"cited_by_count":90,"oa_url":2405,"card":2452,"direction":106,"ingested_from":107},"W7214889813",[2444,2446,2448,2450],{"name":2445,"orcid":17},"Kalyani Machhindra sonawane",{"name":2447,"orcid":17},"Sumitra Nandkumar Nikam",{"name":2449,"orcid":17},"Sunil W. Gaikwad",{"name":2451,"orcid":17},"Yogesh N. Pawar",{"tldr":2453,"method":2454,"finding":2455,"direction":106,"opportunity":2456},"用遥感与GIS分析印度浦那市2015-2025年土地利用变化，发现建设用地大幅扩张、农地水体锐减。","Landsat 8 30米影像，监督最大似然分类，5类LULC与变化检测。","建设用地从30.48%增至57.86%，农地由8.75%降至3.72%，裸地与水体同步减少。","可结合多时相高分辨率影像与CA-Markov模型，预测城市扩张对农地和水体的未来胁迫。","2026-10-01T23:30:28.617704Z",{"id":2459,"title":2460,"url":2461,"summary":2462,"summary_zh":2463,"content":17,"source_name":2464,"source_url":2461,"published_at":2465,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":326,"score_detail":2466,"sources":2468,"tags":2470,"primary_topic":17,"secondary_topics":2474,"classification":2475,"search_phrases":2490,"slug":2493,"view_count":82,"doi":2494,"paper":2495,"created_at":2506},3851,"Appraisal of GIS and Remote Sensing Applications in Land and Environmental Management in Nigeria","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fijgem.vol.11.no11.2025.pg184.196","Geographic Information Systems (GIS) and Remote Sensing (RS) are now central tools forland resource mapping, administration and environmental management worldwide. InNigeria - a country with diverse ecosystems ranging from coastal mangroves and the NigerDelta to Sahelian drylands — GIS\u002FRS applications have been increasingly used tomonitorland-use\u002Fland-cover (LULC) change, coastal erosion and shoreline dynamics, flood riskanddisaster mapping, desertification, wetland and biodiversity assessment, pollution (includingoil-spill) monitoring, and urban expansion. This paper appraises the state of GIS\u002FRSapplications in Nigerian environmental management: surveying key uses, recent advances, technical and institutional constraints, case-study evidence, and policy and researchrecommendations. We synthesize published studies and institutional capabilities (notablyNASRDA and university research) to identify strengths (availability of multi-temporal satellite data, growing national capacity) and gaps (data-sharing, integration with decision-making, funding, and ground truthing). Finally, we propose a prioritized roadmaptostrengthen GIS\u002FRS contributions to sustainable land and environmental governanceinNigeria.","地理信息系统（GIS）与遥感（RS）现已成为全球土地资源制图、行政管理和环境管理的核心工具。尼日利亚拥有从沿海红树林、尼日尔三角洲到萨赫勒旱地等多样化的生态系统，GIS\u002FRS应用在该国日益广泛，用于监测土地利用\u002F土地覆盖（LULC）变化、海岸侵蚀与岸线动态、洪水风险与灾害制图、荒漠化、湿地与生物多样性评估、污染（包括溢油）监测以及城市扩张。本文评估了GIS\u002FRS在尼日利亚环境管理中的应用现状：调查主要用途、近期进展、技术与制度制约、案例研究证据以及政策与研究建议。我们综合已发表研究和机构能力（尤其是NASRDA和大学科研力量），识别优势（多时相卫星数据的可获取性、不断增长的国家能力）与差距（数据共享、与决策的整合、资金投入和地面验证）。最后，我们提出一项优先路线图，以加强GIS\u002FRS对尼日利亚可持续土地与环境治理的贡献。","IIARD INTERNATIONAL JOURNAL OF GEOGRAPHY AND ENVIRONMENTAL MANAGEMENT","2026-09-28T00:00:00Z",{"impact":25,"substance":190,"depth":191,"authority":28,"freshness":29,"relevant":8,"comment":2467},"综述性论文，系统梳理尼日利亚GIS\u002F遥感在土地与环境管理中的应用现状与瓶颈，对农业信息化有参考价值但非国内三农直接相关。",[2469],{"name":2464,"url":2461},[2471,34,2472,4,2473],"土地管理","环境治理","尼日利亚",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":2476},{"candidates":2477,"agricultural_evidence":22,"reason":284},[2478,2482,2486],{"code":39,"score":26,"supported":52,"title":2479,"abstract":2480,"tags":2481},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":2483,"abstract":2484,"tags":2485},[63],[34,63],[34],{"code":81,"score":67,"supported":52,"title":2487,"abstract":2488,"tags":2489},[],[890,891],[],[2491,2492],"尼日利亚 GIS 遥感 土地管理","土地管理 尼日利亚 环境治理 遥感","尼日利亚GIS遥感土地管理-3851","10.56201\u002Fijgem.vol.11.no11.2025.pg184.196",{"doi":2494,"openalex_id":2496,"authors":2497,"venue":2464,"cited_by_count":90,"oa_url":2500,"card":2501,"direction":106,"ingested_from":107},"W7214632546",[2498],{"name":2499,"orcid":17},"Innocent E. Bello","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FIJGEM\u002FVOL. 11 NO. 11 2025\u002FAPPRAISAL OF GIS AND REMOTE 184-196.pdf",{"tldr":2502,"method":2503,"finding":2504,"direction":106,"opportunity":2505},"综述GIS与遥感在尼日利亚土地与环境管理中的应用现状、瓶颈与改进路线图。","文献综述与机构能力分析，聚焦LULC变化、海岸侵蚀、洪水与荒漠化等案例。","多时相卫星数据与本土能力是优势，但数据共享、决策整合、资金与地面验证仍是主要短板。","可针对尼日利亚多生态区开展LULC与灾害遥感监测的本地化验证及决策支持系统研究。","2026-09-30T23:30:31.177741Z",{"id":2508,"title":2509,"url":2510,"summary":2511,"summary_zh":17,"content":17,"source_name":1598,"source_url":2510,"published_at":2465,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":326,"score_detail":2512,"sources":2514,"tags":2516,"primary_topic":17,"secondary_topics":2518,"classification":2519,"search_phrases":2534,"slug":2537,"view_count":150,"doi":2538,"paper":2539,"created_at":2549},3794,"Assessing Climate Change Impacts on Forest Productivity Using Integrated GIS Remote Sensing Climate and Socioeconomic Methods in Itang Special District Gambella Region Ethiopia","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-10789368\u002Fv1","Assessing Climate Change Impacts on Forest Productivity Using Integrated GIS Remote Sensing Climate and Socioeconomic Methods in Itang Special District Gambella Region Ethiopia。Research Square",{"impact":25,"substance":26,"depth":191,"authority":21,"freshness":29,"relevant":8,"comment":2513},"埃塞俄比亚区域尺度的GIS遥感与气候社会经济综合方法研究，方法有参考价值但地域性强、公共影响有限，时效新。",[2515],{"name":1598,"url":2510},[1487,34,4,2517],"森林生产力",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":2520},{"candidates":2521,"agricultural_evidence":22,"reason":284},[2522,2526,2530],{"code":480,"score":28,"supported":52,"title":2523,"abstract":2524,"tags":2525},[1803],[1803],[1487],{"code":59,"score":28,"supported":52,"title":2527,"abstract":2528,"tags":2529},[63],[63],[34],{"code":39,"score":28,"supported":52,"title":2531,"abstract":2532,"tags":2533},[4],[4],[4],[2535,2536],"Gambella Itang 森林生产力","GIS 遥感 气候变化","GambellaItang森林生产力-3794","10.21203\u002Frs.3.rs-10789368\u002Fv1",{"doi":2538,"openalex_id":2540,"authors":2541,"venue":1598,"cited_by_count":90,"oa_url":2548,"card":17,"direction":106,"ingested_from":107},"W7214650564",[2542,2544,2546],{"name":2543,"orcid":17},"KOAT MACHAR PUR",{"name":2545,"orcid":17},"DAK BANG RUON",{"name":2547,"orcid":17},"DUOL NHIAL LUAK","https:\u002F\u002Fwww.researchsquare.com\u002Farticle\u002Frs-10789368\u002Flatest.pdf","2026-09-29T23:30:30.100133Z",{"id":2551,"title":2552,"url":2553,"summary":2554,"summary_zh":2555,"content":17,"source_name":115,"source_url":2553,"published_at":1930,"category":20,"cover_url":17,"hotness":1647,"is_selected":22,"score":90,"score_detail":2556,"sources":2558,"tags":2562,"primary_topic":2565,"secondary_topics":2566,"classification":2567,"search_phrases":2578,"slug":2581,"view_count":75,"doi":2582,"paper":2583,"created_at":2593},3787,"Applied Geography for Sustainable Regional Development in Maharashtra: Potentials, Challenges and Strategic Directions","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23013796","Abstract: Applied Geography refers to the practical application of geographical knowledge, concepts, techniques and spatial analysis to contemporary social, economic and environmental problems. Maharashtra exhibits considerable regional variations in physical resources, population distribution, agriculture, urbanisation, infrastructure, transportation, health services and economic development. These spatial variations create both opportunities and challenges for balanced regional development. The present study examines the role of Applied Geography in sustainable regional development in Maharashtra, with particular emphasis on regional planning, agricultural development, urbanisation, natural-resource management, disaster management, transportation, tourism and accessibility to public services. The study is primarily based on secondary data obtained from government reports, Census publications, planning documents, geographical literature and institutional sources. It highlights the potential application of Geographic Information System (GIS), Remote Sensing, GPS, spatial statistics and geospatial modelling in evidence-based regional planning. The study also identifies major challenges, including regional disparities, environmental degradation, unplanned urban growth, climate-related hazards, infrastructure gaps and unequal access to resources and services. It proposes an integrated geographical framework based on spatial planning, sustainable resource utilisation, geospatial technologies, community participation and regional coordination. The study concludes that Applied Geography can make a significant contribution to achieving balanced, inclusive and sustainable regional development in Maharashtra.","摘要：应用地理学是指将地理知识、概念、技术及空间分析实际应用于当代社会、经济与环境问题。马哈拉施特拉邦在自然资源、人口分布、农业、城市化、基础设施、交通运输、卫生服务及经济发展等方面呈现出显著的区域差异。这些空间差异为区域均衡发展既带来了机遇，也构成了挑战。本研究考察应用地理学在马哈拉施特拉邦可持续区域发展中的作用，重点关注区域规划、农业发展、城市化、自然资源管理、灾害管理、交通运输、旅游业及公共服务可及性。本研究主要基于来自政府报告、人口普查出版物、规划文件、地理学文献及机构来源的二手数据。研究强调了地理信息系统（GIS）、遥感、全球定位系统（GPS）、空间统计及地理空间建模在循证区域规划中的潜在应用。研究还识别了主要挑战，包括区域差距、环境退化、城市无序扩张、气候相关灾害、基础设施缺口以及资源与服务获取不均等。研究提出了一个基于空间规划、可持续资源利用、地理空间技术、社区参与和区域协调的综合地理框架。研究结论认为，应用地理学可为马哈拉施特拉邦实现均衡、包容和可持续的区域发展作出重要贡献。",{"impact":90,"substance":90,"depth":90,"authority":90,"freshness":90,"relevant":90,"comment":2557},"研究印度马哈拉施特拉邦的区域地理规划，与三农、农业信息化、数字乡村等主题无直接关联，不建议进入每日精选。",[2559,2560],{"name":115,"url":2553},{"name":115,"url":2561},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23013797",[34,4,2563,2564],"应用地理学","区域发展规划",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[],{"status":46,"locked":22,"version":47,"method":48,"evidence":2568},{"candidates":2569,"agricultural_evidence":52},[2570,2574],{"code":39,"score":21,"supported":52,"title":2571,"abstract":2572,"tags":2573},[],[55,1010,4,679,56],[4],{"code":59,"score":60,"supported":52,"title":2575,"abstract":2576,"tags":2577},[],[34,63],[34],[2579,2580],"马哈拉施特拉邦 区域发展","应用地理学 遥感","马哈拉施特拉邦区域发展-3787","10.5281\u002Fzenodo.23013796",{"doi":2582,"openalex_id":2584,"authors":2585,"venue":115,"cited_by_count":90,"oa_url":2553,"card":2588,"direction":106,"ingested_from":107},"W7214632446",[2586],{"name":2587,"orcid":17},"M. D. Shaikh",{"tldr":2589,"method":2590,"finding":2591,"direction":314,"opportunity":2592},"综述应用地理学在马哈拉施特拉邦可持续区域发展中的作用、潜力与挑战。","基于政府报告、普查等二手数据，结合GIS、遥感和空间统计进行评述。","应用地理学与地理空间技术可支撑均衡、包容和可持续的区域发展。","可延伸至农业空间规划与乡村服务可达性的地理空间决策支持研究。","2026-09-29T23:30:28.115123Z",{"id":2595,"title":2596,"url":2597,"summary":2598,"summary_zh":2599,"content":17,"source_name":2600,"source_url":2597,"published_at":2601,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2408,"score_detail":2602,"sources":2604,"tags":2606,"primary_topic":17,"secondary_topics":2608,"classification":2609,"search_phrases":2632,"slug":2635,"view_count":75,"doi":2636,"paper":2637,"created_at":2652},3561,"GIS and Machine Learning Framework for Landslide Susceptibility Mapping: A Raster-Based Approach","https:\u002F\u002Fdoi.org\u002F10.48123\u002Frsgis.1864203","Traditional landslide susceptibility models often rely on statistical methods applied to limited point-based samples, which can limit the spatial continuity of predictions. This study proposes a GIS-integrated, pixel-based machine learning approach that operates directly on raster data to generate continuous landslide susceptibility maps. Implemented in Rwanda, the workflow uses variables derived from a 30 m-resolution digital elevation model (DEM), including slope, aspect, elevation, and curvature, together with auxiliary environmental data such as NDVI, soil type, and distances to hydrological and infrastructural features. Several machine learning algorithms were evaluated, including Random Forest, Support Vector Machine, Logistic Regression, and ensemble approaches. Using only topographic variables, the Stacked Ensemble achieved the highest performance (F1-score = 0.8515; ROC-AUC = 0.9200). When all predictor variables were included, CatBoost achieved the highest performance (F1-score = 0.8860; ROC-AUC = 0.9564). This scalable approach is particularly suitable for landslide susceptibility assessment in data-scarce regions and can contribute to spatial planning and risk reduction efforts in Rwanda and similar regions.","传统的滑坡易发性模型通常依赖统计方法，并应用于有限的点位样本，这可能限制预测的空间连续性。本研究提出了一种集成GIS、基于像素的机器学习方法，直接对栅格数据进行操作，以生成连续的滑坡易发性图。该方法在卢旺达实施，工作流程使用源自30 m分辨率数字高程模型（DEM）的变量，包括坡度、坡向、高程和曲率，并结合NDVI、土壤类型以及距水文和基础设施要素的距离等辅助环境数据。研究评估了多种机器学习算法，包括随机森林、支持向量机、逻辑回归和集成方法。仅使用地形变量时，堆叠集成（Stacked Ensemble）取得了最高性能（F1分数 = 0.8515；ROC-AUC = 0.9200）。当纳入所有预测变量时，CatBoost取得了最高性能（F1分数 = 0.8860；ROC-AUC = 0.9564）。这种可扩展的方法特别适用于数据稀缺地区的滑坡易发性评估，并可为卢旺达及类似地区的空间规划和风险降低工作提供支持。","Turkish Journal of Remote Sensing and GIS","2026-09-24T00:00:00Z",{"impact":25,"substance":119,"depth":120,"authority":28,"freshness":25,"relevant":8,"comment":2603},"方法新颖、指标扎实的遥感机器学习论文，可为丘陵山区农业风险与空间规划提供参考，但属境外案例、应用面偏窄。",[2605],{"name":2600,"url":2597},[1937,1785,141,4,2607],"滑坡风险",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":2610},{"candidates":2611,"agricultural_evidence":22,"reason":284},[2612,2616,2620,2624,2628],{"code":138,"score":191,"supported":52,"title":2613,"abstract":2614,"tags":2615},[142],[141,142],[141],{"code":39,"score":28,"supported":52,"title":2617,"abstract":2618,"tags":2619},[4],[4],[4],{"code":66,"score":67,"supported":52,"title":2621,"abstract":2622,"tags":2623},[],[70,71],[],{"code":59,"score":8,"supported":22,"title":2625,"abstract":2626,"tags":2627},[],[],[1785],{"code":1957,"score":8,"supported":22,"title":2629,"abstract":2630,"tags":2631},[],[],[1937],[2633,2634],"卢旺达 滑坡易发性 机器学习","DEM NDVI 滑坡风险制图","卢旺达滑坡易发性机器学习-3561","10.48123\u002Frsgis.1864203",{"doi":2636,"openalex_id":2638,"authors":2639,"venue":2600,"cited_by_count":90,"oa_url":2646,"card":2647,"direction":106,"ingested_from":107},"W7214227863",[2640,2643],{"name":2641,"orcid":2642},"Albert Iradukunda","https:\u002F\u002Forcid.org\u002F0009-0001-6899-7615",{"name":2644,"orcid":2645},"Kaan Ozgun","https:\u002F\u002Forcid.org\u002F0000-0002-3853-1400","https:\u002F\u002Fdergipark.org.tr\u002Fen\u002Fdownload\u002Farticle-file\u002F5606819",{"tldr":2648,"method":2649,"finding":2650,"direction":106,"opportunity":2651},"提出GIS集成、基于栅格像元的机器学习框架，生成连续滑坡易发性图。","用30米DEM地形变量、NDVI、土壤等，比较RF、SVM、CatBoost等模","加入全部变量后CatBoost最优，F1=0.886，AUC=0.956，优于仅地形变量。","可迁移到农业区滑坡风险评估，结合多时相遥感与作物分布，服务山区耕地安全与规划。","2026-09-26T23:30:32.763631Z",{"id":2654,"title":2655,"url":2656,"summary":2657,"summary_zh":2658,"content":17,"source_name":1531,"source_url":2656,"published_at":2601,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2267,"score_detail":2659,"sources":2661,"tags":2663,"primary_topic":2665,"secondary_topics":2666,"classification":2672,"search_phrases":2707,"slug":2710,"view_count":833,"doi":2711,"paper":2712,"created_at":2734},3495,"Remote Sensing and GIS in Modern Drought Assessment: Bridging Conventional Methods and Emerging Technologies","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fjgeesi\u002F2026\u002Fv30i91123","Drought is a complex and recurring hydroclimatic hazard that affects agricultural production, water resources, ecosystems and socioeconomic development. Effective drought assessment requires approaches capable of capturing its spatial and temporal variability and its multiple dimensions. This review examines the evolution of drought assessment from conventional drought indices to integrated approaches based on remote sensing and Geographic Information Systems (GIS), with an emphasis on their applications, strengths, limitations and emerging developments. Conventional indices, including the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), Reconnaissance Drought Index (RDI) and Percent of Normal Precipitation Index (PNPI), remain widely used because of their established methodologies and long-term applicability. However, their dependence on meteorological observations can limit spatial characterisation and the representation of vegetation, soil moisture and other land-surface responses. Remote sensing provides spatially extensive and repeated observations of vegetation condition, land surface temperature, soil moisture, evapotranspiration and water-related conditions, enabling the development of satellite-derived drought indicators and indices. GIS further facilitates the integration, spatial analysis, visualisation, and mapping of drought-related information from multiple sources. The review also discusses hybrid approaches that combine climate-based indices with satellite-derived indicators, as well as drought monitoring platforms and multi-source assessment frameworks. Despite substantial advances, challenges remain regarding cloud contamination, differences in spatial and temporal resolution, data continuity, ground-based validation and uncertainty associated with multi-source datasets. Emerging machine learning, deep learning and artificial intelligence approaches offer opportunities for integrating heterogeneous datasets and improving drought characterisation and early warning. Overall, the integration of conventional observations, remote sensing, GIS and advanced analytical approaches provides a promising framework for more comprehensive drought monitoring and risk assessment under increasing climate variability and change.","干旱是一种复杂且反复出现的水文气候灾害，影响农业生产、水资源、生态系统和社会经济发展。有效的干旱评估需要能够捕捉其时空变异性和多维特征的方法。本文综述了干旱评估从传统干旱指数到基于遥感与地理信息系统（GIS）的综合方法的演变，重点探讨其应用、优势、局限性和新兴发展。传统指数，包括标准化降水指数（SPI）、标准化降水蒸散指数（SPEI）、帕尔默干旱强度指数（PDSI）、侦察干旱指数（RDI）和降水距平百分率指数（PNPI），因其方法成熟且具有长期适用性而仍被广泛使用。然而，这些指数对气象观测的依赖可能限制其空间表征能力以及对植被、土壤水分和其他陆面响应的刻画。遥感提供了对植被状况、地表温度、土壤水分、蒸散量及与水相关状况的大范围重复观测，使得卫星衍生的干旱指标和指数得以发展。GIS进一步促进了多来源干旱相关信息的整合、空间分析、可视化和制图。本文还讨论了将基于气候的指数与卫星衍生指标相结合的混合方法，以及干旱监测平台和多源评估框架。尽管取得了实质性进展，但在云污染、时空分辨率差异、数据连续性、地面验证以及多源数据集相关的不确定性方面仍存在挑战。新兴的机器学习、深度学习和人工智能方法为整合异质数据集、改进干旱表征和预警提供了机遇。总体而言，在气候变异性和变化日益加剧的背景下，传统观测、遥感、GIS和先进分析方法的整合为更全面的干旱监测和风险评估提供了一个有前景的框架。",{"impact":28,"substance":26,"depth":190,"authority":28,"freshness":25,"relevant":8,"comment":2660},"综述系统梳理遥感与GIS在干旱评估中的应用演进，方法学价值明确，但属综述类论文、非国内落地事件，影响力有限。",[2662],{"name":1531,"url":2656},[872,125,34,4,2664],"干旱监测",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[2667,2671],{"code":480,"slug":2668,"name":2669,"path":2670,"parent_code":942},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":2673},{"candidates":2674,"agricultural_evidence":52},[2675,2679,2684,2688,2695,2699,2703],{"code":39,"score":26,"supported":52,"title":2676,"abstract":2677,"tags":2678},[4],[55,1010,4,679,56],[4],{"code":480,"score":191,"supported":52,"title":2680,"abstract":2682,"tags":2683},[2681],"drought",[483,2681],[2664],{"code":59,"score":191,"supported":52,"title":2685,"abstract":2686,"tags":2687},[63],[34,63],[34],{"code":138,"score":21,"supported":52,"title":2689,"abstract":2690,"tags":2694},[],[2691,141,142,2692,2693],"深度学习","deep learning","artificial intelligence",[125],{"code":66,"score":67,"supported":52,"title":2696,"abstract":2697,"tags":2698},[],[70,71],[],{"code":74,"score":67,"supported":52,"title":2700,"abstract":2701,"tags":2702},[],[477,2353],[],{"code":894,"score":8,"supported":22,"title":2704,"abstract":2705,"tags":2706},[],[],[872],[2708,2709],"遥感 GIS 干旱评估","卫星遥感 干旱指数","遥感GIS干旱评估-3495","10.9734\u002Fjgeesi\u002F2026\u002Fv30i91123",{"doi":2711,"openalex_id":2713,"authors":2714,"venue":1531,"cited_by_count":90,"oa_url":2656,"card":2729,"direction":106,"ingested_from":107},"W7214156857",[2715,2717,2719,2721,2723,2725,2727],{"name":2716,"orcid":17},"V. Dhanalakshmi",{"name":2718,"orcid":17},"N. Manikandan",{"name":2720,"orcid":17},"V. S. Jinsy",{"name":2722,"orcid":17},"K. V. Sumesh",{"name":2724,"orcid":17},"P. Nideesh",{"name":2726,"orcid":17},"P. S. Manju",{"name":2728,"orcid":17},"N. Gopika",{"tldr":2730,"method":2731,"finding":2732,"direction":106,"opportunity":2733},"综述了从传统干旱指数到遥感、GIS及AI集成的现代干旱评估方法演进。","文献综述，对比SPI、SPEI等传统指数与遥感、GIS及混合方法。","遥感与GIS弥补传统指数空间局限，但云污染、分辨率差异和验证仍是挑战。","可探索多源遥感与机器学习融合的干旱早期预警，重点解决数据不确定性与地面验证。","2026-09-25T23:30:30.576065Z",{"id":2736,"title":2737,"url":2738,"summary":2739,"summary_zh":2740,"content":17,"source_name":2741,"source_url":2738,"published_at":2742,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2743,"score_detail":2744,"sources":2746,"tags":2748,"primary_topic":2751,"secondary_topics":2752,"classification":2754,"search_phrases":2791,"slug":2794,"view_count":8,"doi":2795,"paper":2796,"created_at":2806},3364,"Geographical Analysis of Desertification and Environmental Degradation and the Spatial Variation of Their Manifestations in Parts of the Jifara Plain","https:\u002F\u002Fdoi.org\u002F10.65405\u002Fsjh.2.3.85","This research aims to analyze the spatial variation of desertification and environmental degradation manifestations in the Al-Jfara Plain, identify the degrees, intensity, and geographical distribution of desertification, and determine the main manifestations associated with land degradation. It also seeks to identify the effects of natural and human factors on the spread of desertification and determine the areas most vulnerable to it, thereby contributing to efforts to conserve natural resources and reduce land degradation. The research adopted the analytical approach as the main method for analyzing data related to degraded lands, vegetation cover, rangelands, rainfall, erosion, and agricultural and livestock production. It also employed the descriptive approach to present the natural and human characteristics of the research area, as well as the comparative approach to compare different spatial units and time periods. The research further relied on geographical references, scientific studies, and available data, using percentages and rates of change to compare levels of degradation. The research concluded that there is clear spatial variation in the manifestations of desertification and environmental degradation across the Al-Jfara Plain. Wind erosion, declining vegetation cover, drought, and rainfall variability emerged as the most prominent manifestations of degradation. In addition, overgrazing, excessive exploitation of soil and groundwater resources, and urban expansion contributed to increasing pressure on natural resources. The research recommends reducing overgrazing, rationalizing groundwater use, combating erosion, increasing vegetation cover, regulating land use, and enhancing environmental awareness. It also proposes periodic monitoring of desertification using remote sensing and Geographic Information Systems (GIS), preparing updated maps of land degradation, and implementing projects for the rehabilitation of degraded lands.","本研究旨在分析贾法拉平原荒漠化与环境退化表现的空间差异，识别荒漠化的程度、强度及地理分布，并确定与土地退化相关的主要表现。研究还力求查明自然因素和人为因素对荒漠化蔓延的影响，确定最易受荒漠化影响的区域，从而为保护自然资源和减少土地退化的努力作出贡献。研究采用分析方法作为分析与退化土地、植被覆盖、牧场、降雨、侵蚀以及农牧业生产相关数据的主要方法，同时运用描述性方法呈现研究区域的自然和人文特征，并采用比较方法对不同空间单元和时间段进行比较。研究还依托地理文献、科学研究和现有数据，利用百分比和变化率来比较退化程度。研究得出结论：贾法拉平原各地荒漠化与环境退化表现在明显的空间差异。风蚀、植被覆盖下降、干旱和降雨变率是最突出的退化表现。此外，过度放牧、土壤和地下水资源的过程开发以及城市扩张也加剧了对自然资源的压力。研究建议减少过度放牧、合理利用地下水、防治侵蚀、增加植被覆盖、规范土地利用并增强环境意识。研究还提出利用遥感和地理信息系统（GIS）对荒漠化进行定期监测，编制更新的土地退化地图，并实施退化土地恢复项目。","Shihab Journal of Humanities","2026-09-23T00:00:00Z",55,{"impact":25,"substance":26,"depth":27,"authority":67,"freshness":29,"relevant":8,"comment":2745},"区域荒漠化空间分析研究，方法常规、结论有参考价值，但属地方性学术成果，公共影响有限。",[2747],{"name":2741,"url":2738},[1112,457,4,2749,2750],"植被覆盖","荒漠化防治",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[2753],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":2755},{"candidates":2756,"agricultural_evidence":52},[2757,2761,2765,2769,2773,2779,2783,2787],{"code":39,"score":21,"supported":52,"title":2758,"abstract":2759,"tags":2760},[],[55,4,56],[4],{"code":59,"score":25,"supported":52,"title":2762,"abstract":2763,"tags":2764},[],[34,63],[2749,457],{"code":66,"score":67,"supported":52,"title":2766,"abstract":2767,"tags":2768},[],[70,71],[],{"code":480,"score":67,"supported":52,"title":2770,"abstract":2771,"tags":2772},[],[483,2681],[],{"code":2774,"score":75,"supported":52,"title":2775,"abstract":2776,"tags":2778},"C",[],[2777],"livestock",[],{"code":74,"score":75,"supported":52,"title":2780,"abstract":2781,"tags":2782},[],[477],[],{"code":691,"score":8,"supported":22,"title":2784,"abstract":2785,"tags":2786},[],[],[1112],{"code":81,"score":8,"supported":22,"title":2788,"abstract":2789,"tags":2790},[],[],[2750],[2792,2793],"GIS 荒漠化 遥感监测","荒漠化防治 土地退化 植被覆盖 遥感监测","GIS荒漠化遥感监测-3364","10.65405\u002Fsjh.2.3.85",{"doi":2795,"openalex_id":2797,"authors":2798,"venue":2741,"cited_by_count":90,"oa_url":2738,"card":2801,"direction":106,"ingested_from":107},"W7214127171",[2799],{"name":2800,"orcid":17},"حسنية السني رجب البكوري",{"tldr":2802,"method":2803,"finding":2804,"direction":106,"opportunity":2805},"分析吉法拉平原荒漠化与环境退化的空间差异及主要表现，并提出防治建议。","采用分析法、描述法与比较法，结合地理文献和统计数据评估退化程度。","风蚀、植被减少、干旱和降水变率是主要退化表现，过度放牧与地下水超采加剧压力。","可结合遥感与GIS开展荒漠化动态监测，构建多因子退化风险评估模型。","2026-09-24T23:30:21.130938Z",{"id":2808,"title":2809,"url":2810,"summary":2811,"summary_zh":2812,"content":17,"source_name":115,"source_url":2810,"published_at":2813,"category":20,"cover_url":17,"hotness":1647,"is_selected":22,"score":2267,"score_detail":2814,"sources":2816,"tags":2820,"primary_topic":2823,"secondary_topics":2824,"classification":2829,"search_phrases":2852,"slug":2855,"view_count":150,"doi":2856,"paper":2857,"created_at":2871},3279,"ASSESSMENT OF SOIL SALINIZATION IN IRRIGATED LANDS BASED ON REMOTE SENSING AND GIS TECHNOLOGIES","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22900049","This thesis analyzes modern approaches to monitoring and assessing soil salinity in irrigated areas of Uzbekistan and Central Asia. Soil salinization is one of the major land degradation processes affecting the reclamation condition of irrigated lands, crop growth and agricultural productivity. Although conventional field and laboratory surveys provide detailed information, they have limitations in terms of regular monitoring of large areas. Therefore, remote sensing and geographic information systems provide promising tools for rapid and spatial assessment of soil salinity. The study considers the application of satellite imagery, particularly Sentinel-2 and Landsat data, for soil salinity assessment, including the use of spectral bands and salinity indices, GIS-based thematic mapping, and validation using field and laboratory observations. Recent studies demonstrate the potential of remote sensing data for spatial assessment and mapping of soil salinity under the conditions of Uzbekistan. Such an integrated approach can support rapid monitoring of the reclamation status of irrigated lands, identification of salt-affected areas and spatial planning of appropriate reclamation measures.","本论文分析了乌兹别克斯坦和中亚灌溉区土壤盐分监测与评估的现代方法。土壤盐渍化是影响灌溉土地改良状况、作物生长和农业生产力的主要土地退化过程之一。尽管传统的野外调查和实验室分析能够提供详细信息，但在大范围定期监测方面存在局限性。因此，遥感与地理信息系统为土壤盐分的快速空间评估提供了有前景的工具。本研究探讨了卫星影像，特别是Sentinel-2和Landsat数据在土壤盐分评估中的应用，包括光谱波段和盐分指数的使用、基于GIS的主题制图，以及利用野外和实验室观测数据进行验证。近期研究表明，遥感数据在乌兹别克斯坦条件下用于土壤盐分空间评估与制图具有潜力。这种综合方法可支持灌溉土地改良状况的快速监测、盐渍化区域的识别以及适当改良措施的空间规划。","2026-09-22T00:00:00Z",{"impact":28,"substance":26,"depth":191,"authority":28,"freshness":29,"relevant":8,"comment":2815},"基于遥感与GIS的灌溉区土壤盐渍化监测论文，方法成熟、结论可靠，对盐碱地治理与农业信息化有参考价值，但属区域性研究，影响层级有限。",[2817,2818],{"name":115,"url":2810},{"name":115,"url":2819},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22900048",[1112,457,4,2821,2822],"土壤盐渍化","灌溉农业",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[2825,2826],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"code":66,"slug":71,"name":2827,"path":2828,"parent_code":942},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil",{"status":46,"locked":22,"version":47,"method":48,"evidence":2830},{"candidates":2831,"agricultural_evidence":52},[2832,2836,2840,2844,2848],{"code":39,"score":26,"supported":52,"title":2833,"abstract":2834,"tags":2835},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":2837,"abstract":2838,"tags":2839},[63],[34,63],[457],{"code":66,"score":27,"supported":52,"title":2841,"abstract":2842,"tags":2843},[71],[70,71],[],{"code":74,"score":150,"supported":52,"title":2845,"abstract":2846,"tags":2847},[],[78],[2822],{"code":691,"score":8,"supported":22,"title":2849,"abstract":2850,"tags":2851},[],[],[1112],[2853,2854],"乌兹别克斯坦 土壤盐渍化 遥感","Sentinel-2 盐渍化 灌溉","乌兹别克斯坦土壤盐渍化遥感-3279","10.5281\u002Fzenodo.22900049",{"doi":2856,"openalex_id":2858,"authors":2859,"venue":115,"cited_by_count":90,"oa_url":2810,"card":2866,"direction":106,"ingested_from":107},"W7214052773",[2860,2862,2864],{"name":2861,"orcid":17},"Mardiyev",{"name":2863,"orcid":17},"Ergashaliyev",{"name":2865,"orcid":17},"G'aniyev",{"tldr":2867,"method":2868,"finding":2869,"direction":106,"opportunity":2870},"综述遥感与GIS评估乌兹别克斯坦及中亚灌溉土壤盐渍化的方法。","Sentinel-2与Landsat影像、光谱盐分指数、GIS制图及野外验证。","遥感与GIS可快速空间评估盐渍化，支持灌溉地改良状态监测与规划。","可探索多源遥感与机器学习融合的盐分指数模型，提升干旱区盐渍化反演精度与时效。","2026-09-23T23:30:19.341486Z",{"id":2873,"title":2874,"url":2875,"summary":2876,"summary_zh":2877,"content":17,"source_name":115,"source_url":2875,"published_at":2878,"category":20,"cover_url":17,"hotness":1647,"is_selected":22,"score":2879,"score_detail":2880,"sources":2882,"tags":2886,"primary_topic":2889,"secondary_topics":2890,"classification":2891,"search_phrases":2906,"slug":2909,"view_count":8,"doi":2910,"paper":2911,"created_at":2928},3068,"MAPPING LAND USE OF BENUE STATE UNIVERSITY, MAKURDI MAIN CAMPUS, BENUE STATE, NIGERIA USING GEOSPATIAL TECHNIQUES","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22865603","This study examined the spatial distribution and extent of land use types within Benue State University (BSU), Makurdi Main Campus, using Geographic Information System (GIS) and remote sensing techniques. Satellite imagery obtained from the National Space Research and Development Agency (NASRDA) was processed and analyzed in ArcGIS 10.8. Land use classification was achieved through on-screen digitization supported by intensive field survey and ground-truthing. The results reveal a heterogeneous land use structure with a total mapped area of 166.69 hectares. Agricultural land use dominates with 20.35%, followed by residential (15.24%) and forest cover (12.29%). Environmentally sensitive land uses, including forestry, green areas, and marshlands, collectively account for 29.18% of the total mapped area, indicating significant ecological value. Institutional land uses (administrative, educational, and religious) account for 15.50%, while commercial and mixed uses constitute 9.29%. The findings highlight a semi-urban institutional landscape undergoing gradual transformation, with increasing development pressures. The study demonstrates the effectiveness of GIS in land use planning and recommends sustainable land management strategies to balance development with environmental conservation.","本研究利用地理信息系统（GIS）和遥感技术，考察了马库尔迪贝努埃州立大学（BSU）主校区内土地利用类型的空间分布与范围。研究对来自国家空间研究与发展局（NASRDA）的卫星影像在ArcGIS 10.8中进行了处理与分析。土地利用分类通过屏幕数字化完成，并辅以密集的实地调查与地面验证。结果显示，该区域土地利用结构具有异质性，总制图面积为166.69公顷。农业用地占主导地位，为20.35%，其次为住宅用地（15.24%）和林地覆盖（12.29%）。环境敏感型土地利用类型，包括林业用地、绿地和沼泽地，合计占总制图面积的29.18%，表明其具有显著的生态价值。机构用地（行政、教育和宗教）占15.50%，而商业和混合用途占9.29%。研究结果凸显出一个正处于逐步转型中的半城市机构景观，其面临日益增大的开发压力。本研究证明了GIS在土地利用规划中的有效性，并建议采取可持续土地管理策略，以平衡开发与环境保护。","2026-09-21T00:00:00Z",56,{"impact":67,"substance":190,"depth":660,"authority":28,"freshness":29,"relevant":8,"comment":2881},"基于GIS与遥感的校园土地利用分类研究，方法规范、数据具体，但属尼日利亚个案，对国内三农与农业信息化参考价值有限。",[2883,2884],{"name":115,"url":2875},{"name":115,"url":2885},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22865602",[34,35,4,2887,2888],"土地分类","校园规划",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[],{"status":46,"locked":22,"version":47,"method":48,"evidence":2892},{"candidates":2893,"agricultural_evidence":52},[2894,2898,2902],{"code":39,"score":21,"supported":52,"title":2895,"abstract":2896,"tags":2897},[],[55,4,56],[4],{"code":59,"score":60,"supported":52,"title":2899,"abstract":2900,"tags":2901},[],[34,63],[34],{"code":81,"score":8,"supported":22,"title":2903,"abstract":2904,"tags":2905},[],[],[35],[2907,2908],"土地分类 土地利用 校园规划 遥感","土地分类 土地利用","土地分类土地利用校园规划遥感-3068","10.5281\u002Fzenodo.22865603",{"doi":2910,"openalex_id":2912,"authors":2913,"venue":115,"cited_by_count":90,"oa_url":2875,"card":2923,"direction":106,"ingested_from":107},"W7213752705",[2914,2916,2917,2919,2921],{"name":2915,"orcid":17},"Alex S. Ortese",{"name":2499,"orcid":17},{"name":2918,"orcid":17},"I. K. SAMAILA",{"name":2920,"orcid":17},"M. ALKALI",{"name":2922,"orcid":17},"A. Mahmud",{"tldr":2924,"method":2925,"finding":2926,"direction":106,"opportunity":2927},"用GIS和遥感技术绘制尼日利亚贝努埃州立大学主校区土地利用分布图。","NASRDA卫星影像，ArcGIS 10.8屏幕数字化，结合实地调查与地面验证。","农业用地占20.35%居首，环境敏感用地共占29.18%，校园呈半城市化转型压力。","可延伸至校园及城郊农业用地动态监测与生态敏感区保护规划研究。","2026-09-21T23:30:23.914355Z",{"id":2930,"title":2931,"url":2932,"summary":2933,"summary_zh":2934,"content":17,"source_name":2935,"source_url":2932,"published_at":2936,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2408,"score_detail":2937,"sources":2939,"tags":2941,"primary_topic":2944,"secondary_topics":2945,"classification":2947,"search_phrases":2981,"slug":2984,"view_count":82,"doi":2985,"paper":2986,"created_at":3005},3020,"Spatial variability of soil fertility indicators using GIS for sustainable land management in Banaskantha district western India","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44378-026-00320-y","Soil fertility assessment is fundamental for sustainable land management and precision agriculture, particularly in semi-arid regions where soil properties exhibit considerable spatial variability. This study investigated the spatial distribution of major soil fertility indicators across Banaskantha district, Gujarat, India, using a systematic 15 × 15 km grid-based sampling approach integrated with Geographic Information System (GIS) analysis and multivariate statistics. A total of 46 geo-referenced composite soil samples were collected from agricultural fields representing all fourteen talukas and analysed for soil moisture, pH, electrical conductivity (EC), organic carbon (OC), available nitrogen (AvN), available phosphorus (AvP), and available potassium (AvK). GIS-based Inverse Distance Weighting (IDW) interpolation was employed to visualize the regional distribution of soil properties, while Pearson correlation analysis and Principal Component Analysis (PCA) were used to examine relationships among soil fertility indicators and identify the major factors influencing soil variability. The results revealed substantial spatial heterogeneity across the district, with alkaline and saline soils predominantly occurring in the western region, whereas comparatively higher soil moisture and organic carbon were observed in the eastern and northern areas. Available phosphorus was generally deficient throughout the district, while available nitrogen and potassium exhibited pronounced spatial variation associated with parent material, land use, and agricultural management practices. PCA identified salinity-related factors and organic matter–nutrient interactions as the principal contributors to soil fertility variability. The generated spatial distribution maps provide valuable baseline information for identifying nutrient-deficient zones and understanding regional patterns of soil fertility. Although the proposed nutrient management strategies require further validation through field-based agronomic studies, the integration of laboratory soil analysis, GIS, and multivariate statistical techniques provides an effective framework for regional soil fertility assessment and supports informed decision-making for sustainable land management in semi-arid environments.","土壤肥力评估是可持续土地管理和精准农业的基础，尤其是在土壤属性表现出显著空间变异性的半干旱地区。本研究采用基于15 × 15 km网格的系统采样方法，结合地理信息系统（GIS）分析和多元统计方法，调查了印度古吉拉特邦巴纳斯坎塔县主要土壤肥力指标的空间分布。共从代表全部十四个乡的农田中采集了46个地理参照复合土壤样品，并分析了土壤水分、pH、电导率（EC）、有机碳（OC）、有效氮（AvN）、有效磷（AvP）和有效钾（AvK）。采用基于GIS的反距离加权（IDW）插值法可视化土壤属性的区域分布，同时运用Pearson相关分析和主成分分析（PCA）考察土壤肥力指标之间的关系，并识别影响土壤变异性的主要因素。结果表明，该县土壤存在显著的空间异质性，碱性和盐渍化土壤主要分布在西部地区，而东部和北部地区土壤水分和有机碳相对较高。有效磷在整个县域普遍缺乏，而有效氮和有效钾则表现出与母质、土地利用和农业管理措施相关的显著空间变异。PCA识别出盐分相关因子和有机质—养分相互作用是土壤肥力变异性的主要贡献因素。所生成的空间分布图为识别养分缺乏区和理解土壤肥力区域格局提供了有价值的基线信息。尽管所提出的养分管理策略需要通过田间农艺研究进一步验证，但实验室土壤分析、GIS和多元统计技术的整合为区域土壤肥力评估提供了有效框架，并为半干旱环境下可持续土地管理的科学决策提供了支持。","Discover Soil.","2026-09-19T00:00:00Z",{"impact":25,"substance":119,"depth":190,"authority":28,"freshness":29,"relevant":8,"comment":2938},"基于GIS与多元统计的区域土壤肥力空间变异研究，方法规范、数据翔实，对精准农业与可持续土地管理有参考价值，但属区域性案例，公共影响有限。",[2940],{"name":2935,"url":2932},[2942,1538,34,4,2943],"精准农业","土壤肥力",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[2946],{"code":66,"slug":71,"name":2827,"path":2828,"parent_code":942},{"status":46,"locked":22,"version":47,"method":48,"evidence":2948},{"candidates":2949,"agricultural_evidence":52},[2950,2954,2958,2963,2969,2973,2977],{"code":39,"score":26,"supported":52,"title":2951,"abstract":2952,"tags":2953},[4],[55,4,56],[4],{"code":66,"score":191,"supported":52,"title":2955,"abstract":2956,"tags":2957},[71],[70,71],[2943],{"code":894,"score":60,"supported":52,"title":2959,"abstract":2960,"tags":2962},[],[2942,2961],"precision agriculture",[2942],{"code":2964,"score":75,"supported":52,"title":2965,"abstract":2966,"tags":2968},"F3",[],[2967],"养分管理",[],{"code":480,"score":75,"supported":52,"title":2970,"abstract":2971,"tags":2972},[],[483],[],{"code":1565,"score":8,"supported":22,"title":2974,"abstract":2975,"tags":2976},[],[],[1538],{"code":59,"score":8,"supported":22,"title":2978,"abstract":2979,"tags":2980},[],[],[34],[2982,2983],"Banaskantha 土壤肥力 GIS","印度 半干旱区 土壤养分","Banaskantha土壤肥力GIS-3020","10.1007\u002Fs44378-026-00320-y",{"doi":2985,"openalex_id":2987,"authors":2988,"venue":2935,"cited_by_count":90,"oa_url":2932,"card":3000,"direction":178,"ingested_from":107},"W7213587271",[2989,2992,2994,2996,2998],{"name":2990,"orcid":2991},"Mukesh P. Chaudhari","https:\u002F\u002Forcid.org\u002F0009-0000-2187-2375",{"name":2993,"orcid":17},"Ruchi Nair",{"name":2995,"orcid":17},"Pratik Chavda",{"name":2997,"orcid":17},"Dharmik Patel",{"name":2999,"orcid":17},"Divya Mishra",{"tldr":3001,"method":3002,"finding":3003,"direction":106,"opportunity":3004},"用GIS与多元统计评估印度半干旱区Banaskantha土壤肥力指标的空间变异。","15×15 km网格采样46个样点，结合IDW插值、Pearson相关与PCA分","西部土壤偏碱盐化，东部北部有机碳较高，全区分区有效磷普遍缺乏。","可结合遥感植被指数与机器学习提升半干旱区土壤肥力制图精度并验证养分管理策略。","2026-09-20T23:30:43.716518Z",{"id":3007,"title":3008,"url":3009,"summary":3010,"summary_zh":3011,"content":17,"source_name":3012,"source_url":3009,"published_at":3013,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":326,"score_detail":3014,"sources":3016,"tags":3018,"primary_topic":3021,"secondary_topics":3022,"classification":3024,"search_phrases":3045,"slug":3048,"view_count":82,"doi":3049,"paper":3050,"created_at":3069},2943,"SPATIO-TEMPORAL DYNAMICS OF LAND USE AND LAND COVER IN A GRANITE QUARRYING AREA IN MANÉAH, GUINEA: A REMOTE SENSING AND GIS-BASED ANALYSIS FROM 1980 TO 2024","https:\u002F\u002Fdoi.org\u002F10.30574\u002Fgscarr.2026.28.3.0222","Quarrying is a major driver of transformation in peri-urban areas, particularly in spaces experiencing both rapid urbanization and increasing pressure on natural resources. This study analyzes the spatio-temporal dynamics of land cover in the urban commune of Manéah, Guinea, between 1980, 2020, and 2024, in order to characterize the territorial changes associated with the development of extractive activities and urban expansion. The methodological approach relies on the use of multi-temporal satellite imagery, its processing in a GIS environment, supervised classification of the main land cover classes, diachronic analysis of changes, construction of a transition matrix, and evaluation of the quality of the classifications using the Kappa index. The results highlight a profound transformation of the landscape. Between 1980 and 2024, the proportion of built-up areas increased from 7.22% to 32.67%, a rise of 25.45 percentage points, while quarries and construction sites, absent in 1980, represented 2.05% of the territory in 2024, after reaching 7.50% in 2020. Conversely, cultivated land and fallow land increased overall by 18.58 percentage points. In contrast, natural formations experienced a sharp decline: shrub savannas decreased from 40.50% to 1.73%, bodies of water from 31.46% to 11.30%, and mangroves from 8.85% to 0.84%. The Kappa values of 0.76, 0.79, and 0.82 indicate a satisfactory agreement between the classifications. These changes reflect the increasing human impact on the territory, resulting from the combined effects of urbanization, agriculture, and extractive activities. The change matrix also confirms a structural recomposition of the territory, with built-up areas increasing from 963.406 ha to 4,357.55 ha, while shrub savannas decreased from 5,401.819 ha to only 230.389 ha over the entire study period. The study thus highlights the need to further integrate remote sensing data and GIS tools into land-use planning, environmental monitoring, and the spatial management of quarries in Manéah.","采石活动是城郊地区转型的主要驱动力，尤其是在同时经历快速城市化和自然资源压力加剧的区域。本研究分析了几内亚马内阿（Manéah）城市公社在1980年、2020年和2024年的土地覆盖时空动态，以刻画与采掘活动发展和城市扩张相关的领土变化。研究方法依赖于多时相卫星影像的使用、在GIS环境中的处理、主要土地覆盖类别的监督分类、变化的历史对比分析、转移矩阵的构建，以及利用Kappa指数评估分类质量。结果揭示了景观的深刻转变。1980年至2024年间，建成区比例从7.22%增至32.67%，上升了25.45个百分点；而采石场和建筑工地1980年尚不存在，2020年达到7.50%，2024年占领土的2.05%。相反，耕地和休耕地总体增加了18.58个百分点。相比之下，自然 formations 急剧减少：灌木草原从40.50%降至1.73%，水体从31.46%降至11.30%，红树林从8.85%降至0.84%。Kappa值分别为0.76、0.79和0.82，表明分类之间具有令人满意的一致性。这些变化反映了人类对领土日益加剧的影响，这是城市化、农业和采掘活动共同作用的结果。变化矩阵也证实了领土的结构性重组，建成区从963.406公顷增至4，357.55公顷，而灌木草原在整个研究期内从5，401.819公顷降至仅230.389公顷。因此，本研究强调了进一步将遥感数据和GIS工具纳入马内阿的土地利用规划、环境监测和采石场空间管理的必要性。","GSC Advanced Research and Reviews","2026-09-18T00:00:00Z",{"impact":25,"substance":26,"depth":191,"authority":21,"freshness":29,"relevant":8,"comment":3015},"基于多时相遥感与GIS的矿区土地利用变化研究，方法规范、数据翔实，但地域性强、与国内农业信息化关联有限，可作为遥感应用案例参考。",[3017],{"name":3012,"url":3009},[3019,457,35,4,3020],"城镇化","矿区生态",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},[3023],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":3025},{"candidates":3026,"agricultural_evidence":52},[3027,3031,3035,3041],{"code":59,"score":191,"supported":52,"title":3028,"abstract":3029,"tags":3030},[63],[34,63],[457],{"code":39,"score":28,"supported":52,"title":3032,"abstract":3033,"tags":3034},[4],[4],[4],{"code":3036,"score":75,"supported":52,"title":3037,"abstract":3038,"tags":3040},"I7",[],[3039],"研究方法",[],{"code":81,"score":82,"supported":22,"title":3042,"abstract":3043,"tags":3044},[],[],[35,3020],[3046,3047],"Manéah 几内亚 土地利用","遥感 GIS 采石场 土地覆盖","Manéah几内亚土地利用-2943","10.30574\u002Fgscarr.2026.28.3.0222",{"doi":3049,"openalex_id":3051,"authors":3052,"venue":3012,"cited_by_count":90,"oa_url":3009,"card":3064,"direction":106,"ingested_from":107},"W7213550535",[3053,3055,3057,3060,3062],{"name":3054,"orcid":17},"Sogbè KEITA",{"name":3056,"orcid":17},"Mamady Minata CONDÉ",{"name":3058,"orcid":3059},"Ibrahima Thiam","https:\u002F\u002Forcid.org\u002F0000-0001-8553-1043",{"name":3061,"orcid":17},"Lucien SOLIE",{"name":3063,"orcid":17},"Alpha Issaga Pallé Diallo",{"tldr":3065,"method":3066,"finding":3067,"direction":106,"opportunity":3068},"基于遥感与GIS分析几内亚Manéah采石区1980-2024年土地利用与覆盖的时空变化。","多时相卫星影像、GIS监督分类、变化矩阵与Kappa精度评价。","建设用地由7.22%升至32.67%，灌丛草原由40.50%降至1.73%，采石场2024年占2.0","可延伸至采石与城市化对周边农地、红树林的耦合影响及生态修复监测研究。","2026-09-19T23:30:32.836654Z",{"id":3071,"title":3072,"url":3073,"summary":3074,"summary_zh":3075,"content":17,"source_name":3076,"source_url":3073,"published_at":3077,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":90,"score_detail":3078,"sources":3080,"tags":3082,"primary_topic":17,"secondary_topics":3083,"classification":3084,"search_phrases":3103,"slug":3106,"view_count":60,"doi":3107,"paper":3108,"created_at":3125},2793,"Delineation of groundwater potential zones using analytical hierarchy process and GIS in Bhilangana Block of Tehri Garhwal District, Uttarakhand, India","https:\u002F\u002Fdoi.org\u002F10.33765\u002Fthate.16.4.4","Groundwater is one of the most reliable freshwater resources globally, but overexploitation has led to declining water tables, deteriorating water quality, and increased water scarcity. These problems have raised serious questions about how sustainable groundwater management can be achieved. In recent times, geospatial techniques and the Analytical Hierarchy Process (AHP) have been increasingly applied to assess groundwater availability. This research aims to delineate groundwater potential zones in the Bhilangana Block using the above-mentioned methods. Initially, remote sensing data were employed to generate thematic layers, including geomorphology, geology, slope, elevation, drainage density, lineament density, soil, rainfall, and land use\u002Fland cover. Subsequently, these layers were integrated using a multi-criteria evaluation approach, and weights were assigned using AHP-based weighted overlay analysis. The resulting groundwater potential zones were classified into five categories: very low and low (over 45 %), moderate (35.05 %), high (16.66 %), and very high (3.81 %). The findings of this research offer insights into groundwater occurrence in the study area, which could be helpful for sustainable groundwater management and long-term planning of water resources.","地下水是全球最可靠的淡水资源之一，但过度开采已导致地下水位下降、水质恶化以及水资源短缺加剧。这些问题引发了关于如何实现可持续地下水管理的严肃思考。近年来，地理空间技术和层次分析法（Analytical Hierarchy Process, AHP）越来越多地被应用于地下水可获得性评估。本研究旨在利用上述方法圈定Bhilangana区块的地下水潜力区。首先，利用遥感数据生成专题图层，包括地貌、地质、坡度、高程、河网密度、线性构造密度、土壤、降雨以及土地利用\u002F土地覆盖。随后，采用多准则评价方法整合这些图层，并利用基于AHP的加权叠加分析分配权重。所得到的地下水潜力区被划分为五类：极低和低（超过45 %）、中等（35.05 %）、高（16.66 %）以及极高（3.81 %）。本研究结果有助于认识研究区地下水的赋存情况，可为可持续地下水管理和水资源长期规划提供参考。","The holistic approach to environment","2026-09-16T00:00:00Z",{"impact":90,"substance":90,"depth":90,"authority":90,"freshness":90,"relevant":90,"comment":3079},"该论文研究印度北阿坎德邦地下水潜力区划，属水文地质与遥感应用领域，与三农、农业信息化、智慧农业等主题无直接关联，不建议进入每日精选。",[3081],{"name":3076,"url":3073},[34,665,4],[],{"status":269,"locked":22,"version":47,"method":48,"evidence":3085},{"candidates":3086,"agricultural_evidence":22,"reason":284},[3087,3091,3095,3099],{"code":39,"score":29,"supported":52,"title":3088,"abstract":3089,"tags":3090},[4],[],[4],{"code":59,"score":60,"supported":52,"title":3092,"abstract":3093,"tags":3094},[],[34,63],[34],{"code":66,"score":67,"supported":52,"title":3096,"abstract":3097,"tags":3098},[],[70,71],[],{"code":74,"score":150,"supported":52,"title":3100,"abstract":3101,"tags":3102},[],[477],[665],[3104,3105],"水资源管理 遥感 GIS","水资源管理 遥感","水资源管理遥感GIS-2793","10.33765\u002Fthate.16.4.4",{"doi":3107,"openalex_id":3109,"authors":3110,"venue":3076,"cited_by_count":90,"oa_url":3119,"card":3120,"direction":106,"ingested_from":107},"W7213317885",[3111,3114,3117],{"name":3112,"orcid":3113},"Siddharth Rana","https:\u002F\u002Forcid.org\u002F0009-0006-5304-3233",{"name":3115,"orcid":3116},"Gaurav Gaurav","https:\u002F\u002Forcid.org\u002F0000-0001-8857-5797",{"name":3118,"orcid":17},"Mohan Singh Panwar","https:\u002F\u002Fcasopis.hrcpo.com\u002Fwp-content\u002Fuploads\u002F2026\u002F09\u002FRana-et-al_HAE_16_2026_4.pdf",{"tldr":3121,"method":3122,"finding":3123,"direction":106,"opportunity":3124},"用AHP与GIS遥感数据划分印度Bhilangana区块地下水潜力区。","遥感专题图层+AHP加权叠加多准则评价。","潜力区以低和极低为主（超45%），极高仅3.81%。","可结合灌溉需求与作物分布，将地下水潜力图用于农业用水优化与井位选址。","2026-09-17T23:30:36.203631Z",{"id":3127,"title":3128,"url":3129,"summary":3130,"summary_zh":3131,"content":17,"source_name":3132,"source_url":3129,"published_at":3133,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2743,"score_detail":3134,"sources":3136,"tags":3138,"primary_topic":3140,"secondary_topics":3141,"classification":3142,"search_phrases":3161,"slug":3164,"view_count":82,"doi":3165,"paper":3166,"created_at":3184},2784,"Monitoring & Evaluating of Urban Expansion and Its Impact on Land use Land Cover Change of Sargodha, Pakistan (2000-2025)","https:\u002F\u002Fdoi.org\u002F10.71317\u002Fjgst.2.9(s).2026.624","Urban growth is a significant land-use transition that is taking place in many rapidly growing cities, especially where the expansion is taking place on productive agricultural land. The purpose of this research was to explore the Spatio-temporal pattern of urban expansion and changes in land use\u002Fland cover (LULC) in Sargodha Tehsil, Pakistan, for the period 2000-2025. This study used the remote sensing and GIS techniques to analyze the satellite imageries of 6 years. These years include 2000, 2005, 2010, 2015, 2020 and 2025. The study area covered an expanse of 1536 km² and comprised four land use\u002Fland cover (LULC) classes, including agricultural land, built-up area, barren land, and water bodies. The study used supervised classification Maximum likelihood classifier (MLC) to identify the dominant land use and land cover types and determine the percentage of the region that was covered by each class. The results show that there is a growing trend in the built-up area throughout the years. It increased from 115 km² in 2000 to 180 km² in 2005, 233 km² in 2010, 297 km² in 2015, 361 km² in 2020, and 440 km² in 2025. Thus, it can be stated that there was an increase in the built-up area by 325 km² or 282.6% over the studied period. In contrast, the amount of farmland decreased from 1,014 km² to 815 km² or 199 km². The area of barren land decreased as well from 280 km² to 153 km². At the same time, there was no significant change in the amount of water bodies from 127 km² to 128 km². Findings reveal a significant change from a primarily agricultural region to a region with a considerable presence of developed areas and emphasize the increasing pressure on productive land. The research underlines the significance of planned urbanization, protection of productive agricultural lands, regular geospatial monitoring, and appropriate management of the periphery belt.","城市增长是许多快速发展的城市正在经历的重要土地利用转变，尤其是在生产力较高的农业用地上发生扩张的地区。本研究旨在探讨巴基斯坦萨戈达县（Sargodha Tehsil）2000—2025年期间城市扩张的时空格局及土地利用\u002F土地覆盖（LULC）变化。本研究采用遥感与GIS技术，对6个年份的卫星影像进行了分析，包括2000年、2005年、2010年、2015年、2020年和2025年。研究区面积为1536 km²，涵盖四种土地利用\u002F土地覆盖（LULC）类型，包括农业用地、建设用地、裸地和水体。研究采用监督分类中的最大似然分类器（MLC）识别主要土地利用与土地覆盖类型，并确定各类型所占区域百分比。结果表明，建设用地面积在各年份间呈持续增长趋势，从2000年的115 km²增至2005年的180 km²、2010年的233 km²、2015年的297 km²、2020年的361 km²，以及2025年的440 km²。因此可以认为，在研究期间建设用地面积增加了325 km²，增幅达282.6%。相比之下，农田面积从1014 km²减少至815 km²，减少了199 km²。裸地面积也从280 km²减少至153 km²。与此同时，水体面积从127 km²变化至128 km²，没有显著变化。研究结果揭示了该区域从以农业为主向建设用地显著增加的区域发生了重大转变，并凸显了生产性土地日益增大的压力。本研究强调了有计划城市化、保护生产性农业用地、定期地理空间监测以及对外围地带进行适当管理的重要性。","Journal of Global Social Transformation","2026-09-17T00:00:00Z",{"impact":25,"substance":26,"depth":27,"authority":67,"freshness":29,"relevant":8,"comment":3135},"基于遥感与GIS的巴基斯坦城市扩张对农用地影响研究，数据翔实但属区域案例，对国内三农信息化参考价值有限。",[3137],{"name":3132,"url":3129},[1539,457,35,4,3139],"城市扩张",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},[],{"status":46,"locked":22,"version":47,"method":48,"evidence":3143},{"candidates":3144,"agricultural_evidence":52},[3145,3149,3153,3157],{"code":59,"score":60,"supported":52,"title":3146,"abstract":3147,"tags":3148},[],[34,63],[457],{"code":39,"score":150,"supported":52,"title":3150,"abstract":3151,"tags":3152},[],[4],[4],{"code":691,"score":8,"supported":22,"title":3154,"abstract":3155,"tags":3156},[],[],[1539],{"code":81,"score":8,"supported":22,"title":3158,"abstract":3159,"tags":3160},[],[],[35],[3162,3163],"土地利用 城市扩张 耕地保护 遥感监测","土地利用 城市扩张","土地利用城市扩张耕地保护遥感监测-2784","10.71317\u002Fjgst.2.9(s).2026.624",{"doi":3165,"openalex_id":3167,"authors":3168,"venue":3132,"cited_by_count":90,"oa_url":3129,"card":3179,"direction":106,"ingested_from":107},"W7213443079",[3169,3171,3174,3176],{"name":3170,"orcid":17},"Muhammad Israr",{"name":3172,"orcid":3173},"Omar Riaz","https:\u002F\u002Forcid.org\u002F0000-0002-5391-109X",{"name":3175,"orcid":17},"Muhammad Safeer Hussain",{"name":3177,"orcid":3178},"Muhammad Imran","https:\u002F\u002Forcid.org\u002F0000-0003-4072-4997",{"tldr":3180,"method":3181,"finding":3182,"direction":106,"opportunity":3183},"用遥感与GIS分析巴基斯坦萨戈达2000-2025年城市扩张及土地利用变化。","6期Landsat影像，最大似然监督分类，提取四类LULC并统计面积。","建设用地增325km²（282.6%），耕地减199km²，城市扩张大量侵占优质农田。","可结合耕地质量与作物生产力数据，量化城市扩张对农业产能的具体损失并构建预警模型。","2026-09-17T23:30:34.285631Z",{"id":3186,"title":3187,"url":3188,"summary":3189,"summary_zh":3190,"content":17,"source_name":587,"source_url":3188,"published_at":3191,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":7,"score_detail":3192,"sources":3194,"tags":3196,"primary_topic":3198,"secondary_topics":3199,"classification":3201,"search_phrases":3220,"slug":3223,"view_count":82,"doi":3224,"paper":3225,"created_at":3243},2673,"Flood Hazard Zone Mapping of Vashishti River Basin by Using Remote Sensing and GIS Techniques","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fijecc\u002F2026\u002Fv16i95677","Floods are among the most destructive natural hazards in regions characterised by high and intense rainfall, frequently causing substantial loss of human life and considerable damage to agriculture, infrastructure, property, and the natural environment. The Vashishti River basin, situated within the ecologically sensitive Western Ghats, is particularly susceptible to recurrent and severe flooding owing to its distinctive hydro-meteorological and physiographic characteristics. The interaction of intense monsoonal rainfall, basin topography, drainage conditions, and increasing human intervention further contributes to the basin's flood susceptibility. In this context, flood hazard mapping provides an effective means of identifying areas with varying levels of exposure to flooding and can support the reduction of disaster risks associated with human settlements, agricultural activities, infrastructure development, and, in particular, expanding urban areas. Therefore, the present study aims to identify, delineate, and characterise flood hazard zones within the Vashishti River basin. The resulting spatial information is expected to provide a scientific basis for improved flood risk assessment, land-use planning, disaster preparedness, and the formulation of effective flood mitigation and management strategies. A total of ten flood-influencing factors, namely elevation, slope, drainage density, distance from the river, land use\u002Fland cover, rainfall, runoff derived using the SCS-CN method, geomorphology, lithology, and soil texture, were analysed in a Geographic Information System (GIS). Weights were assigned using the Analytic Hierarchy Process (AHP). With a consistency ratio (CR) of 0.06 for the correlation matrix, the flood hazard zone map indicates that 0.81% of the study area falls within a very low hazard zone, 13.49% within a low hazard zone, 47.90% within a moderate zone, 20.59% within a high flood hazard zone, and 17.20% within a very high flood hazard zone. Rainfall, elevation, and slope are the primary factors influencing flood risk. The AHP-based approach used in this study provides a practical framework for flood hazard mapping and may be applied to other regions for flood hazard management and mitigation.","洪水是降雨量大且强度高的地区最具破坏性的自然灾害之一，常造成重大人员伤亡以及对农业、基础设施、财产和自然环境的严重破坏。瓦希什蒂河流域位于生态敏感的西高止山脉地区，由于其独特的水文气象和地形特征，特别容易遭受反复且严重的洪水。强烈的季风降雨、流域地形、排水条件以及日益增加的人类干预相互作用，进一步加剧了该流域的洪水易发性。在此背景下，洪水灾害制图为识别不同洪水暴露程度区域提供了有效手段，并可支持降低与人类住区、农业活动、基础设施建设以及特别是不断扩张的城市区域相关的灾害风险。因此，本研究旨在识别、划定并表征瓦希什蒂河流域内的洪水灾害区。所生成的空间信息预期可为改进洪水风险评估、土地利用规划、灾害防备以及制定有效的洪水减缓与管理策略提供科学依据。研究在地理信息系统（GIS）中分析了十个洪水影响因子，即高程、坡度、河网密度、距河流距离、土地利用\u002F土地覆被、降雨、采用SCS-CN方法得出的径流、地貌、岩性和土壤质地。采用层次分析法（AHP）确定权重。相关矩阵的一致性比率（CR）为0.06，洪水灾害区图表明，研究区0.81%属于极低灾害区，13.49%属于低灾害区，47.90%属于中等灾害区，20.59%属于高洪水灾害区，17.20%属于极高洪水灾害区。降雨、高程和坡度是影响洪水风险的主要因素。本研究采用的基于AHP的方法为洪水灾害制图提供了实用框架，并可应用于其他地区的洪水灾害管理与减缓。","2026-09-15T00:00:00Z",{"impact":28,"substance":26,"depth":190,"authority":660,"freshness":25,"relevant":8,"comment":3193},"基于遥感与GIS的流域洪水危险性制图研究，方法规范、数据翔实，对农业防灾减灾与土地利用规划有参考价值，但属区域性案例研究，公共影响有限。",[3195],{"name":587,"url":3188},[34,3197,4,1052,1373],"农业防灾",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[3200],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":3202},{"candidates":3203,"agricultural_evidence":52},[3204,3208,3212,3216],{"code":39,"score":26,"supported":52,"title":3205,"abstract":3206,"tags":3207},[4],[55,4,56],[4],{"code":59,"score":29,"supported":52,"title":3209,"abstract":3210,"tags":3211},[63],[],[34],{"code":66,"score":67,"supported":52,"title":3213,"abstract":3214,"tags":3215},[],[70,71],[],{"code":480,"score":82,"supported":22,"title":3217,"abstract":3218,"tags":3219},[],[],[3197,1373],[3221,3222],"农业防灾 洪水风险 流域治理 遥感","农业防灾 洪水风险","农业防灾洪水风险流域治理遥感-2673","10.9734\u002Fijecc\u002F2026\u002Fv16i95677",{"doi":3224,"openalex_id":3226,"authors":3227,"venue":587,"cited_by_count":90,"oa_url":3188,"card":3238,"direction":106,"ingested_from":107},"W7213314416",[3228,3230,3232,3234,3236],{"name":3229,"orcid":17},"Bhagyalaxmi Kallihal",{"name":3231,"orcid":17},"S. S. Nagarkar",{"name":3233,"orcid":17},"B. L. Ayare",{"name":3235,"orcid":17},"S.T. Patil",{"name":3237,"orcid":17},"S. V. Deshmukh",{"tldr":3239,"method":3240,"finding":3241,"direction":106,"opportunity":3242},"用遥感与GIS结合AHP方法，对Vashishti河流域进行洪水灾害分区制图。","遥感与GIS空间分析，选取10个洪水影响因子，AHP赋权（CR=0.06）。","47.90%区域属中等危险区，17.20%为极高危险区；降雨、高程和坡度是主控因子。","可结合作物分布与农情数据，将洪水危险分区延伸至农田尺度风险评估与减灾决策。","2026-09-16T23:30:30.712391Z",{"id":3245,"title":3246,"url":3247,"summary":3248,"summary_zh":17,"content":17,"source_name":1598,"source_url":3247,"published_at":3191,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":188,"score_detail":3249,"sources":3251,"tags":3253,"primary_topic":17,"secondary_topics":3257,"classification":3258,"search_phrases":3269,"slug":3272,"view_count":833,"doi":3273,"paper":3274,"created_at":3279},2669,"Assessment of Fire Distribution across Elevation Zones Using GIS and Remote Sensing On Mount Mulanje, Malawi","https:\u002F\u002Fdoi.org\u002F10.21203\u002Frs.3.rs-11012933\u002Fv1","Assessment of Fire Distribution across Elevation Zones Using GIS and Remote Sensing On Mount Mulanje, Malawi。Research Square",{"impact":67,"substance":27,"depth":660,"authority":29,"freshness":25,"relevant":8,"comment":3250},"基于GIS与遥感的山地林火垂直分布研究，方法规范但属区域性案例，对国内三农信息化参考价值有限。",[3252],{"name":1598,"url":3247},[34,4,3254,3255,3256],"林火监测","马拉维","山地生态",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":3259},{"candidates":3260,"agricultural_evidence":22,"reason":284},[3261,3265],{"code":59,"score":28,"supported":52,"title":3262,"abstract":3263,"tags":3264},[63],[63],[34],{"code":39,"score":28,"supported":52,"title":3266,"abstract":3267,"tags":3268},[4],[4],[4],[3270,3271],"山地生态 林火监测 马拉维 遥感","山地生态 林火监测","山地生态林火监测马拉维遥感-2669","10.21203\u002Frs.3.rs-11012933\u002Fv1",{"doi":3273,"openalex_id":3275,"authors":3276,"venue":1598,"cited_by_count":90,"oa_url":3247,"card":17,"direction":106,"ingested_from":107},"W7213293906",[3277,3278],{"name":1635,"orcid":17},{"name":1637,"orcid":17},"2026-09-16T23:30:30.392533Z",{"id":3281,"title":3282,"url":3283,"summary":3284,"summary_zh":3285,"content":17,"source_name":3286,"source_url":3283,"published_at":3191,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":588,"score_detail":3287,"sources":3289,"tags":3291,"primary_topic":17,"secondary_topics":3296,"classification":3297,"search_phrases":3312,"slug":3315,"view_count":82,"doi":3316,"paper":3317,"created_at":3331},2668,"Assessment of the Current Sanitary and Technical Condition of Irrigation Reservoirs in Azerbaijan","https:\u002F\u002Fdoi.org\u002F10.33619\u002F2414-2948\u002F130\u002F12","The article presents a comprehensive assessment of the current sanitary and technical condition of irrigation reservoirs in Azerbaijan, analyzing the operational characteristics of hydraulic structures, the level of technical deterioration, and the primary risk factors affecting their safe operation. The study aims to determine the condition of reservoirs vital to irrigation systems, identify factors influencing operational reliability, and evaluate the applicability of modern monitoring and management approaches. The research utilizes comparative analysis, a systems approach, statistical assessment methods, hydro-technical observation data, regulatory documentation, and geographic information systems (GIS) combined with remote sensing. Particular attention is given to dam stability, the structural integrity of hydraulic facilities, sediment accumulation, seepage, deformation processes, and key sanitary water quality indicators. Results indicate that prolonged operation, structural wear, sedimentation, and insufficient monitoring contribute to declining safety and efficiency. Conversely, the implementation of digital monitoring, GIS-based analytical tools, and automated systems is essential for improving reliability and sustainability. The scientific novelty lies in the integrated assessment of these reservoirs using contemporary technological frameworks.","本文对阿塞拜疆灌溉水库当前的卫生与技术状况进行了综合评估，分析了水工建筑物的运行特征、技术老化程度以及影响其安全运行的主要风险因素。研究旨在确定对灌溉系统至关重要的水库状况，识别影响运行可靠性的因素，并评估现代监测与管理方法的适用性。研究采用比较分析、系统方法、统计评估方法、水工观测数据、规范性文件以及地理信息系统（GIS）与遥感相结合的手段。研究特别关注大坝稳定性、水工设施的结构完整性、泥沙淤积、渗漏、变形过程及关键卫生水质指标。结果表明，长期运行、结构磨损、淤积及监测不足导致安全性和效率下降。相反，实施数字化监测、基于GIS的分析工具及自动化系统对于提高可靠性和可持续性至关重要。该研究的科学新颖性在于运用当代技术框架对这些水库进行综合评估。","Bulletin of Science and Practice",{"impact":25,"substance":26,"depth":190,"authority":28,"freshness":29,"relevant":8,"comment":3288},"论文以GIS与遥感综合评估阿塞拜疆灌溉水库卫生技术状况，方法有参考价值，但属他国区域研究，对国内三农实践影响有限，可作技术借鉴而非每日精选头条。",[3290],{"name":3286,"url":3283},[3292,457,4,3293,3294,3295],"农业基础设施","灌溉水库","水利工程","数字监测",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":3298},{"candidates":3299,"agricultural_evidence":22,"reason":284},[3300,3304,3308],{"code":74,"score":27,"supported":52,"title":3301,"abstract":3302,"tags":3303},[674],[78,674],[],{"code":39,"score":21,"supported":52,"title":3305,"abstract":3306,"tags":3307},[],[55,4,56],[4],{"code":59,"score":60,"supported":52,"title":3309,"abstract":3310,"tags":3311},[],[34,63],[457],[3313,3314],"农业基础设施 数字监测 水利工程 灌溉水库","农业基础设施 数字监测","农业基础设施数字监测水利工程灌溉水库-2668","10.33619\u002F2414-2948\u002F130\u002F12",{"doi":3316,"openalex_id":3318,"authors":3319,"venue":3286,"cited_by_count":90,"oa_url":3283,"card":3326,"direction":106,"ingested_from":107},"W7213287517",[3320,3322,3324],{"name":3321,"orcid":17},"Sh. Guliyev",{"name":3323,"orcid":17},"E. Ganbarov",{"name":3325,"orcid":17},"O. Imanli",{"tldr":3327,"method":3328,"finding":3329,"direction":106,"opportunity":3330},"综合评估阿塞拜疆灌溉水库的卫生与技术状况，分析老化风险并提出数字化监测建议。","比较分析、系统方法、统计评估、水文观测数据、GIS与遥感。","长期运行、结构磨损、淤积和监测不足导致水库安全与效率下降，数字化监测是关键。","可延伸研究：将GIS遥感与物联网传感器结合，构建灌溉水库实时安全预警与水质监测系统。","2026-09-16T23:30:30.293789Z",{"id":3333,"title":3334,"url":3335,"summary":3336,"summary_zh":3337,"content":17,"source_name":3338,"source_url":3335,"published_at":3339,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":23,"score_detail":3340,"sources":3342,"tags":3344,"primary_topic":3345,"secondary_topics":3346,"classification":3348,"search_phrases":3367,"slug":3370,"view_count":82,"doi":3371,"paper":3372,"created_at":3383},2529,"Flood Risk Assessment and Environmental Change Analysis Using GIS and Remote Sensing","https:\u002F\u002Fdoi.org\u002F10.34248\u002Fbsengineering.1994338","Floods can be very destructive natural hazard; it causes significant environmental, social, and economic impacts. Havza is a district in Northern part of Türkiye, experienced major flood events in May 1998 and May 2026, which emphasize the need of identify flood-prone areas and analyze the factors that influence flood vulnerability. The aim of this study is to asses flood risk and analyzes land use\u002Fland cover (LULC) monitoring derived from remote sensing data in Havza. Furthermore, topographic characteristics were also obtained from Shuttle Radar Topography Mission (SRTM) and Digital Elevation Model (DEM) using Geographic Information Systems (GIS). Hydrological analyses include slope and flow accumulation models, and these analyses were used to identify susceptible areas. It has been observed that the mean NDVI value increased from 0.4239 in 1998 to 0.7447 in 2026, indicating a substantial increase in vegetation cover. LULC classification results also showed that urban areas increased from 16% to 20% while agricultural land decreased 54% to 50% in approximately last 3 decades. 3-Dimensional (3D) terrain visualization and river corridor-based flood risk mapping revealed that low elevation valley floors and settlements located very near to stream channels, which is the most vulnerable areas of floods. The findings of this study demonstrate the effectiveness of integration of GIS and remote sensing, topographic analysis, and LULC change detection within a single framework for flood risk assessment and sustainable land management. The results provide valuable support for disaster risk reduction, urban planning, and future development strategies in Havza and similar watershed environments.","洪水是一种极具破坏性的自然灾害，会对环境、社会和经济造成显著影响。哈夫扎（Havza）是土耳其北部的一个区，1998年5月和2026年5月经历了重大洪水事件，这凸显了识别洪水易发区域并分析影响洪水脆弱性因素的必要性。本研究旨在评估哈夫扎的洪水风险，并分析基于遥感数据获得的土地利用\u002F土地覆盖（LULC）监测结果。此外，还利用地理信息系统（GIS）从航天飞机雷达地形测绘任务（SRTM）和数字高程模型（DEM）中获取了地形特征。水文分析包括坡度和汇流累积模型，这些分析用于识别易受洪水影响的区域。研究发现，NDVI均值从1998年的0.4239上升至2026年的0.7447，表明植被覆盖显著增加。LULC分类结果还显示，在近三十年间，城市面积从16%增加至20%，而农业用地从54%减少至50%。三维（3D）地形可视化和基于河流廊道的洪水风险制图表明，低海拔河谷底部和紧邻河道的居民点是洪水最脆弱的区域。本研究结果表明，将GIS与遥感、地形分析以及LULC变化检测整合于同一框架内，对于洪水风险评估和可持续土地管理具有有效性。研究结果为哈夫扎及类似流域环境的减灾、城市规划和未来发展战略提供了有价值的支持。","Black Sea Journal of Engineering and Science","2026-09-14T00:00:00Z",{"impact":25,"substance":26,"depth":191,"authority":28,"freshness":25,"relevant":8,"comment":3341},"以GIS与遥感融合评估土耳其流域洪水风险与土地利用变化，方法框架对农业防灾与乡村空间规划有参考价值，但属区域案例研究，公共影响有限。",[3343],{"name":3338,"url":3335},[1000,34,1990,4,458],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[3347],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":3349},{"candidates":3350,"agricultural_evidence":52},[3351,3355,3359,3363],{"code":39,"score":26,"supported":52,"title":3352,"abstract":3353,"tags":3354},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":3356,"abstract":3357,"tags":3358},[63],[34,63],[34],{"code":480,"score":82,"supported":22,"title":3360,"abstract":3361,"tags":3362},[],[],[1990,1000],{"code":81,"score":8,"supported":22,"title":3364,"abstract":3365,"tags":3366},[],[],[458],[3368,3369],"土地利用变化 洪水风险评估 防灾减灾 遥感","土地利用变化 洪水风险评估","土地利用变化洪水风险评估防灾减灾遥感-2529","10.34248\u002Fbsengineering.1994338",{"doi":3371,"openalex_id":3373,"authors":3374,"venue":3338,"cited_by_count":90,"oa_url":3335,"card":3378,"direction":106,"ingested_from":107},"W7212642487",[3375],{"name":3376,"orcid":3377},"Sibel Canaz","https:\u002F\u002Forcid.org\u002F0000-0001-5552-6067",{"tldr":3379,"method":3380,"finding":3381,"direction":106,"opportunity":3382},"结合GIS与遥感评估土耳其Havza地区洪水风险，并分析近30年土地利用与植被变化。","使用SRTM\u002FDEM地形分析、坡度与汇流模型、NDVI及LULC分类。","低海拔河谷与近河道居民点最易受灾；城区扩张、农地减少、植被覆盖显著增加。","可引入时序遥感与机器学习，构建流域尺度洪水风险动态预警与土地利用协同优化模型。","2026-09-15T23:30:20.567355Z",{"id":3385,"title":3386,"url":3387,"summary":3388,"summary_zh":3389,"content":17,"source_name":3390,"source_url":3387,"published_at":3391,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":3392,"score_detail":3393,"sources":3395,"tags":3397,"primary_topic":17,"secondary_topics":3398,"classification":3399,"search_phrases":3422,"slug":3425,"view_count":82,"doi":3426,"paper":3427,"created_at":3456},2425,"GIS-Based Multi-Criteria Modelling of Soil Erosion Susceptibility Using AHP in Ikere-Ekiti, Southwestern Nigeria","https:\u002F\u002Fdoi.org\u002F10.54536\u002Fajgt.v5i1.8103","Soil erosion remains a critical environmental challenge in tropical regions, particularly in areas experiencing rapid land-use change and geomorphic instability. This study presents a GIS-based multi-criteria modelling approach for assessing soil erosion susceptibility in Ikere-Ekiti, Southwestern Nigeria. Twelve conditioning factors-land use\u002Fland cover (LULC), slope, aspect, elevation, drainage density, soil type, rainfall, Normalized Difference Vegetation Index (NDVI), geology, rainfall erosivity (R-factor), soil erodibility (K-factor), and Topographic Wetness Index (TWI)-were integrated using an Analytic Hierarchy Process (AHP) framework. Spatial datasets derived from ASTER DEM, Landsat 8 imagery, soil and geological maps, and rainfall records were standardized and weighted using pairwise comparison, with model consistency validated (CR = 0.06). A weighted overlay model was employed to generate erosion susceptibility zones. Results indicate that low and moderate susceptibility zones dominate (90.48%), while high and very high-risk areas account for 4.50% and 0.03%, respectively. High-risk zones are strongly associated with steep slopes, high drainage density, sparse vegetation, and erodible soils. The study demonstrates the robustness of GIS-based multi-criteria modelling in erosion prediction and provides a decision-support framework for sustainable land management in tropical environments.","土壤侵蚀仍然是热带地区面临的严峻环境挑战，尤其是在土地利用快速变化和地貌不稳定的区域。本研究提出了一种基于GIS的多准则建模方法，用于评估尼日利亚西南部伊凯雷-埃基蒂（Ikere-Ekiti）地区的土壤侵蚀敏感性。研究整合了12个条件因子——土地利用\u002F土地覆盖（LULC）、坡度、坡向、高程、河网密度、土壤类型、降雨量、归一化植被指数（NDVI）、地质、降雨侵蚀力（R因子）、土壤可蚀性（K因子）和地形湿度指数（TWI），并采用层次分析法（AHP）框架进行分析。来自ASTER DEM、Landsat 8影像、土壤与地质图及降雨记录的空间数据集经过标准化处理，并通过成对比较法赋权，模型一致性得到验证（CR = 0.06）。采用加权叠加模型生成侵蚀敏感性分区。结果表明，低度和中度敏感区占主导地位（90.48%），而高风险区和极高风险区分别占4.50%和0.03%。高风险区与陡坡、高河网密度、稀疏植被和易蚀土壤密切相关。本研究证明了基于GIS的多准则建模在侵蚀预测中的稳健性，并为热带环境下的可持续土地管理提供了决策支持框架。","American Journal of Geospatial Technology","2026-09-12T00:00:00Z",62,{"impact":25,"substance":26,"depth":191,"authority":660,"freshness":25,"relevant":8,"comment":3394},"基于GIS与AHP的土壤侵蚀敏感性建模研究，方法规范、结论可靠，对热带地区土地管理与农业生态保护有参考价值，但属区域性案例研究，公共影响有限。",[3396],{"name":3390,"url":3387},[1937,34,36,4,37],[],{"status":269,"locked":22,"version":47,"method":48,"evidence":3400},{"candidates":3401,"agricultural_evidence":22,"reason":284},[3402,3406,3410,3414,3418],{"code":66,"score":27,"supported":52,"title":3403,"abstract":3404,"tags":3405},[71],[70,71],[],{"code":39,"score":28,"supported":52,"title":3407,"abstract":3408,"tags":3409},[4],[4],[4],{"code":81,"score":8,"supported":22,"title":3411,"abstract":3412,"tags":3413},[],[],[37],{"code":59,"score":8,"supported":22,"title":3415,"abstract":3416,"tags":3417},[],[],[34],{"code":1957,"score":8,"supported":22,"title":3419,"abstract":3420,"tags":3421},[],[],[1937],[3423,3424],"土壤侵蚀 数字乡村 水土保持 遥感","土壤侵蚀 数字乡村","土壤侵蚀数字乡村水土保持遥感-2425","10.54536\u002Fajgt.v5i1.8103",{"doi":3426,"openalex_id":3428,"authors":3429,"venue":3390,"cited_by_count":90,"oa_url":3450,"card":3451,"direction":106,"ingested_from":107},"W7212388696",[3430,3432,3435,3438,3441,3444,3446,3448],{"name":3431,"orcid":17},"Samuel Fatile",{"name":3433,"orcid":3434},"Elochukwu Moka","https:\u002F\u002Forcid.org\u002F0000-0001-6089-1392",{"name":3436,"orcid":3437},"Olaniran Emmanuel Aluko","https:\u002F\u002Forcid.org\u002F0000-0002-8750-1742",{"name":3439,"orcid":3440},"Ugonna C. Nkwunonwo","https:\u002F\u002Forcid.org\u002F0000-0002-6944-0675",{"name":3442,"orcid":3443},"Seyi F. Olatoyinbo","https:\u002F\u002Forcid.org\u002F0000-0002-6859-9350",{"name":3445,"orcid":17},"Ndukwe Emmanuel Chiemelu",{"name":3447,"orcid":17},"Peter Damulak DAKUNG",{"name":3449,"orcid":17},"Mark Fredrick OCHOLI","https:\u002F\u002Fjournals.e-palli.com\u002Fhome\u002Findex.php\u002Fajgt\u002Farticle\u002Fdownload\u002F8103\u002F4012",{"tldr":3452,"method":3453,"finding":3454,"direction":106,"opportunity":3455},"用GIS与AHP多准则模型评估尼日利亚Ikere-Ekiti地区土壤侵蚀敏感性并划分风险区。","整合12个因子，基于AHP加权叠加，数据来自ASTER DEM、Landsat ","低与中度敏感区占90.48%，高与极高风险区仅4.53%，高风险与陡坡、高排水密度、稀疏植被和易蚀土","可引入机器学习或时序遥感提升AHP权重客观性，并验证侵蚀风险与作物产量的空间关联。","2026-09-14T23:30:24.740002Z",{"id":3458,"title":3459,"url":3460,"summary":3461,"summary_zh":3462,"content":17,"source_name":3463,"source_url":3460,"published_at":3464,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":3465,"score_detail":3466,"sources":3468,"tags":3470,"primary_topic":3474,"secondary_topics":3475,"classification":3476,"search_phrases":3495,"slug":3498,"view_count":150,"doi":3499,"paper":3500,"created_at":3523},2326,"Drone-based leak detection and real-time monitoring of urban water in Harare, Zimbabwe","https:\u002F\u002Fdoi.org\u002F10.2166\u002Fwashdev.2026.227","ABSTRACT Increasing water scarcity resulting from inefficient urban water distribution systems across many African cities threatens the attainment of the Sustainable Development Goals. This is concerning given additional pressures on water resources such as climate change, pollution, increased demand from population growth and agriculture. Thus, there is a need to develop efficient, rapid and repeatable methods for tracking both urban water distribution and water use. This study applied drone-based thermal infra-red imaging for real-time leak detection and monitoring of Harare's aging water network by characterizing water distribution infrastructure with emphasis on spatial variations in pipe material and age. Very high-resolution thermal imagery was acquired using a DJI Mavic 3T drone and then processed before being integrated with water distribution infrastructure data within a GIS to identify temperature anomalies indicative of leaks. A scalable thermally based remote sensing algorithm was developed for detecting water leaks. The model achieved a precision of 82% and a recall of 90%, demonstrating the high accuracy of the model in detecting most leaks. An F1-Score of 0.86 demonstrated a strong balance between detection accuracy and false alarms, suitable for operational use. The integration of drone data within a GIS platform offers a scalable framework for a proactive approach in water-scarce urban contexts.","摘要 许多非洲城市因城市配水系统效率低下而加剧的水资源短缺，威胁着可持续发展目标的实现。考虑到气候变化、污染、人口增长和农业用水需求增加对水资源造成的额外压力，这一情况令人担忧。因此，有必要开发高效、快速且可重复的方法来追踪城市配水和水资源利用情况。本研究应用基于无人机的热红外成像技术，对哈拉雷老化的供水管网进行实时漏损检测与监测，通过刻画配水基础设施特征，重点关注管道材质和管龄的空间变化。研究使用DJI Mavic 3T无人机获取超高分辨率热红外影像，经处理后与GIS中的配水基础设施数据整合，以识别指示漏损的温度异常。研究开发了一种可扩展的基于热红外的遥感算法用于检测漏水。该模型达到了82%的精确率和90%的召回率，表明其在检测大多数漏损方面具有较高准确性。F1分数为0.86，表明检测准确性与误报之间取得了良好平衡，适合实际业务应用。将无人机数据整合至GIS平台，为水资源短缺的城市环境提供了一种可扩展的主动管理框架。","Journal of Water Sanitation and Hygiene for Development","2026-09-11T00:00:00Z",74,{"impact":27,"substance":740,"depth":26,"authority":660,"freshness":25,"relevant":8,"comment":3467},"基于无人机热红外与GIS的城市供水漏损检测研究，方法可复用于农业灌溉管网监测，但场景偏城市水务，与三农直接关联有限。",[3469],{"name":3463,"url":3460},[3471,457,4,3472,3473],"无人机","智慧水务","城市供水",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},[],{"status":46,"locked":22,"version":47,"method":48,"evidence":3477},{"candidates":3478,"agricultural_evidence":52},[3479,3483,3487,3491],{"code":59,"score":60,"supported":52,"title":3480,"abstract":3481,"tags":3482},[],[34,63],[457],{"code":480,"score":67,"supported":52,"title":3484,"abstract":3485,"tags":3486},[],[1487,1803],[],{"code":39,"score":150,"supported":52,"title":3488,"abstract":3489,"tags":3490},[],[4],[4],{"code":74,"score":75,"supported":52,"title":3492,"abstract":3493,"tags":3494},[],[477],[],[3496,3497],"城市供水 智慧水务 遥感监测 无人机","城市供水 智慧水务","城市供水智慧水务遥感监测无人机-2326","10.2166\u002Fwashdev.2026.227",{"doi":3499,"openalex_id":3501,"authors":3502,"venue":3463,"cited_by_count":90,"oa_url":3460,"card":3518,"direction":106,"ingested_from":107},"W7212404404",[3503,3506,3509,3512,3515],{"name":3504,"orcid":3505},"Godknows Ignatius Junior Mugabe","https:\u002F\u002Forcid.org\u002F0009-0000-6557-3481",{"name":3507,"orcid":3508},"Webster Gumindoga","https:\u002F\u002Forcid.org\u002F0000-0001-8530-7383",{"name":3510,"orcid":3511},"Munyaradzi Davis Shekede","https:\u002F\u002Forcid.org\u002F0000-0002-6540-3316",{"name":3513,"orcid":3514},"Alexander Mhizha","https:\u002F\u002Forcid.org\u002F0000-0002-6890-5143",{"name":3516,"orcid":3517},"Manuel Ndebele","https:\u002F\u002Forcid.org\u002F0000-0002-1432-6322",{"tldr":3519,"method":3520,"finding":3521,"direction":316,"opportunity":3522},"用无人机热红外成像检测津巴布韦哈拉雷城市供水管网泄漏并实时监测。","DJI Mavic 3T热红外影像结合GIS管网数据，开发热遥感泄漏检测算法。","模型精度82%、召回率90%、F1值0.86，可有效检测多数泄漏点。","可将无人机热红外泄漏检测拓展至农业灌溉管网，结合物联网实现精准漏损预警。","2026-09-13T23:30:23.478384Z",{"id":3525,"title":3526,"url":3527,"summary":3528,"summary_zh":3529,"content":17,"source_name":3530,"source_url":3527,"published_at":3391,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2408,"score_detail":3531,"sources":3533,"tags":3535,"primary_topic":3538,"secondary_topics":3539,"classification":3541,"search_phrases":3572,"slug":3575,"view_count":150,"doi":3576,"paper":3577,"created_at":3589},2319,"Assessing Forest Resource Depletion and Rural Livelihood Sustainability in Ovia Southwest, Nigeria using Remote Sensing, GIS, and Qualitative Socio-Economic Data","https:\u002F\u002Fdoi.org\u002F10.70882\u002Fjosrar.2026.v3i5.278","Forest resources are fundamental to rural livelihoods in sub-Saharan Africa, yet rapid land-use change threatens their sustainability. This study assessed forest cover change, available forest resources, socio-economic drivers of household dependence, and community perceptions of forest contributions to socio-economic development in Ovia Southwest LGA., Edo State, Nigeria. A mixed-methods approach was used to integrate remote sensing and GIS analysis of Landsat imagery (1987–2024), a household survey (n = 390), factor analysis, multiple regression, and chi-square tests. Land use land cover classification revealed that natural environment (forest cover) declined from 76.95% (202,031.28ha) in 1987 to 42.07% (110,449.55ha) in 2024, representing a 50% loss. Disturbed forest increased from 13.48% to 27.80%, while farmland expanded from 6.90% to 26.08%. Factor analysis identified four dominant forest resource categories: timber\u002Fcharcoal\u002Ffibres (35.4% variance), medicinal plants\u002Froots\u002Fforest soil (14.8%), fruits\u002Fanimal fodder (9.9%), and meat\u002Fhoney (7.0%). Multiple regression showed socio-economic factors significantly influenced household forest dependence (R² = 0.279, F = 29.779, p \u003C 0.001), with education, age, and occupation as the strongest predictors. Chi-square analysis confirmed that communities perceive a significant contribution of forest resources to socio-economic development (χ² = 221.718, df = 32, p \u003C 0.001). The study concludes that agricultural expansion and timber extraction are primary drivers of forest degradation, and livelihood diversification interventions are urgently needed to reduce forest dependence while sustaining rural well-being. And recommended implementation of community-participatory forest conservation programmes; investment in rural education\u002Fexpanded vocational training to provide alternative income sources; and regular monitoring using remote sensing should continue to track forest cover trends and inform adaptive management.","森林资源是撒哈拉以南非洲农村生计的基础，但快速的土地利用变化威胁着其可持续性。本研究评估了尼日利亚埃多州奥维亚西南地方政府区的森林覆盖变化、可利用森林资源、家庭依赖的社会经济驱动因素以及社区对森林促进社会经济发展的认知。研究采用混合方法，整合了1987—2024年Landsat影像的遥感与GIS分析、入户调查（n = 390）、因子分析、多元回归和卡方检验。土地利用\u002F土地覆盖分类显示，自然环境（森林覆盖）从1987年的76.95%（202,031.28公顷）下降至2024年的42.07%（110,449.55公顷），减少了50%。受干扰森林从13.48%增至27.80%，农田从6.90%扩展至26.08%。因子分析识别出四类主要森林资源：木材\u002F木炭\u002F纤维（方差贡献率35.4%）、药用植物\u002F根茎\u002F森林土壤（14.8%）、水果\u002F动物饲料（9.9%）以及肉类\u002F蜂蜜（7.0%）。多元回归表明，社会经济因素显著影响家庭对森林的依赖（R² = 0.279，F = 29.779，p \u003C 0.001），其中教育程度、年龄和职业是最强的预测因子。卡方分析证实，社区认为森林资源对社会经济发展具有显著贡献（χ² = 221.718，df = 32，p \u003C 0.001）。研究结论认为，农业扩张和木材采伐是森林退化的主要驱动因素，亟需通过生计多样化干预措施来减少对森林的依赖，同时维持农村福祉。研究建议：实施社区参与式森林保护项目；投资农村教育\u002F扩大职业培训以提供替代收入来源；持续利用遥感进行定期监测，以追踪森林覆盖趋势并为适应性管理提供依据。","Journal of Science Research and Reviews",{"impact":25,"substance":119,"depth":190,"authority":28,"freshness":29,"relevant":8,"comment":3532},"基于Landsat长时序遥感与入户调查的尼日利亚森林退化与生计依赖研究，方法扎实、数据翔实，但属区域案例，对国内三农信息化仅有方法借鉴价值。",[3534],{"name":3530,"url":3527},[457,35,4,3536,3537],"森林资源","农村生计",{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},[3540],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":3542},{"candidates":3543,"agricultural_evidence":52},[3544,3548,3552,3556,3562,3568],{"code":59,"score":191,"supported":52,"title":3545,"abstract":3546,"tags":3547},[63],[34,63],[457],{"code":39,"score":28,"supported":52,"title":3549,"abstract":3550,"tags":3551},[4],[4],[4],{"code":66,"score":67,"supported":52,"title":3553,"abstract":3554,"tags":3555},[],[70,71],[],{"code":3557,"score":75,"supported":52,"title":3558,"abstract":3559,"tags":3561},"B6",[],[3560],"药用植物",[],{"code":3563,"score":75,"supported":52,"title":3564,"abstract":3565,"tags":3567},"C4",[],[3566],"饲料",[],{"code":81,"score":8,"supported":22,"title":3569,"abstract":3570,"tags":3571},[],[],[35],[3573,3574],"农村生计 土地利用 森林资源 遥感监测","农村生计 土地利用","农村生计土地利用森林资源遥感监测-2319","10.70882\u002Fjosrar.2026.v3i5.278",{"doi":3576,"openalex_id":3578,"authors":3579,"venue":3530,"cited_by_count":90,"oa_url":3527,"card":3584,"direction":106,"ingested_from":107},"W7212392638",[3580,3582],{"name":3581,"orcid":17},"David E. Eighemhenrio",{"name":3583,"orcid":17},"Akan A. Tom",{"tldr":3585,"method":3586,"finding":3587,"direction":106,"opportunity":3588},"结合遥感与入户调查，评估尼日利亚Ovia西南部森林资源枯竭及农户生计依赖。","Landsat影像(1987–2024)、GIS分类、390户问卷、因子分析与回","森林覆盖减少50%，农业扩张与伐木为主因，教育、年龄和职业显著影响生计依赖。","可延伸至多时相遥感与农户生计耦合建模，识别森林退化热点并评估替代生计干预效果。","2026-09-13T23:30:22.724040Z",{"id":3591,"title":3592,"url":3593,"summary":3594,"summary_zh":3595,"content":17,"source_name":115,"source_url":3593,"published_at":1930,"category":20,"cover_url":17,"hotness":1647,"is_selected":22,"score":1481,"score_detail":3596,"sources":3598,"tags":3602,"primary_topic":3605,"secondary_topics":3606,"classification":3607,"search_phrases":3639,"slug":3642,"view_count":150,"doi":3643,"paper":3644,"created_at":3654},2317,"\"Bharat @2047: A Geographical Perspective on Sustainable and Inclusive Regional Development\"","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22706245","India’s vision of becoming a developed nation by 2047 depends on achieving balanced development across its diverse regions. Differences in landforms, climate, soils, water resources, population, agriculture, infrastructure and economic activities have created uneven development opportunities. While some regions have experienced rapid urbanization, industrialization and improved connectivity, rural, remote and environmentally fragile areas continue to face developmental challenges. This paper examines sustainable and inclusive regional development under Viksit Bharat @2047 from a geographical perspective. It focuses on regional disparities, rural transformation, urbanization, agriculture, infrastructure, natural-resource management, environmental sustainability, climate resilience, digital inclusion and tourism. Special attention is given to GIS and Remote Sensing for understanding spatial patterns and supporting development planning. The study is based on secondary information from government publications, institutional reports, academic literature and development documents, using a descriptive and analytical approach. The study argues that a uniform development model may not address India’s regional diversity effectively. Development strategies should consider local resources, environmental conditions, population characteristics, connectivity and economic potential. Strengthening rural–urban linkages, improving infrastructure, promoting sustainable resource use and expanding digital access can help reduce regional inequalities. A geographically sensitive approach can make Viksit Bharat @2047 more inclusive, sustainable and responsive to the varied needs of different regions.","印度到2047年成为发达国家的愿景，取决于能否在其多样化的各地区实现均衡发展。地貌、气候、土壤、水资源、人口、农业、基础设施和经济活动的差异，造成了发展机会的不均衡。一些地区经历了快速的城市化、工业化和连通性改善，而农村、偏远和环境脆弱地区仍面临发展挑战。本文从地理学视角考察“Viksit Bharat @2047”框架下的可持续和包容性区域发展。研究聚焦于区域差距、农村转型、城市化、农业、基础设施、自然资源管理、环境可持续性、气候韧性、数字包容和旅游业。特别关注地理信息系统（GIS）和遥感在理解空间格局及支持发展规划方面的作用。本研究基于政府出版物、机构报告、学术文献和发展文件的二手资料，采用描述性和分析性方法。研究认为，统一的发展模式可能无法有效应对印度的区域多样性。发展战略应考虑当地资源、环境条件、人口特征、连通性和经济潜力。加强城乡联系、改善基础设施、促进资源可持续利用和扩大数字接入，有助于缩小区域不平等。一种具有地理敏感性的方法可以使“Viksit Bharat @2047”更具包容性、可持续性，并更好地回应不同地区的多样化需求。",{"impact":190,"substance":27,"depth":191,"authority":28,"freshness":90,"relevant":8,"comment":3597},"从地理视角讨论印度2047区域均衡发展，涉及遥感与GIS应用及农村转型，对农业信息化有参考价值，但属宏观综述且时效性差。",[3599,3600],{"name":115,"url":3593},{"name":115,"url":3601},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22706244",[1937,34,3603,4,3604],"农业可持续发展","区域协调发展",{"code":43,"slug":129,"name":130,"path":131,"parent_code":17},[],{"status":134,"locked":22,"version":47,"method":48,"evidence":3608},{"candidates":3609,"agricultural_evidence":52,"reason":158},[3610,3614,3618,3622,3626,3631,3635],{"code":59,"score":60,"supported":52,"title":3611,"abstract":3612,"tags":3613},[],[34,63],[34],{"code":39,"score":60,"supported":52,"title":3615,"abstract":3616,"tags":3617},[],[55,4],[4],{"code":66,"score":75,"supported":52,"title":3619,"abstract":3620,"tags":3621},[],[70],[],{"code":74,"score":75,"supported":52,"title":3623,"abstract":3624,"tags":3625},[],[477],[],{"code":480,"score":75,"supported":52,"title":3627,"abstract":3628,"tags":3630},[],[3629],"climate resilience",[],{"code":1565,"score":8,"supported":22,"title":3632,"abstract":3633,"tags":3634},[],[],[3603],{"code":1957,"score":8,"supported":22,"title":3636,"abstract":3637,"tags":3638},[],[],[1937],[3640,3641],"农业可持续发展 区域协调发展 数字乡村 遥感","农业可持续发展 区域协调发展","农业可持续发展区域协调发展数字乡村遥感-2317","10.5281\u002Fzenodo.22706245",{"doi":3643,"openalex_id":3645,"authors":3646,"venue":115,"cited_by_count":90,"oa_url":3593,"card":3649,"direction":106,"ingested_from":107},"W7212248989",[3647],{"name":3648,"orcid":17},"Jayram Sunil Pawar",{"tldr":3650,"method":3651,"finding":3652,"direction":314,"opportunity":3653},"从地理视角分析印度2047年可持续包容性区域发展，强调因地制宜与GIS遥感支持规划。","基于政府报告等二手资料，采用描述性与分析性方法，结合GIS和遥感。","统一发展模式难以应对区域多样性，需因地制宜并加强城乡联系与数字接入。","可探究GIS\u002F遥感如何量化区域差异并支撑差异化数字乡村发展策略。","2026-09-13T23:30:22.373477Z",{"id":3656,"title":3657,"url":3658,"summary":3659,"summary_zh":3660,"content":17,"source_name":2464,"source_url":3658,"published_at":3661,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":90,"score_detail":3662,"sources":3664,"tags":3666,"primary_topic":17,"secondary_topics":3667,"classification":3668,"search_phrases":3683,"slug":3686,"view_count":75,"doi":3687,"paper":3688,"created_at":3699},2310,"Geospatial Analysis of Topographic and Hydrological Controls on Flood Susceptibility","https:\u002F\u002Fdoi.org\u002F10.56201\u002Fijgem.vol.12.no3.2026.pg279.299","This study evaluates the influence of topographic and hydrological factors on flood susceptibility in the South–South region of Nigeria using Geographic Information Systems (GIS), Remote Sensing, and the Analytical Hierarchy Process (AHP). Digital Elevation Model (DEM), slope, aspect, drainage density, stream density, flow direction, and distance from river variables were analysed to determine their contribution to flooding. The results show that elevation ranges from approximately 13 m in low-lying coastal areas (Delta, Rivers, Bayelsa, and Akwa Ibom States) to about 256 m in elevated inland areas (Cross River and parts of Edo State). Slope analysis indicates that coastal areas are dominated by very gentle slopes (0°–3.37°), which promote water accumulation and increase flood susceptibility. Aspect results further reveal that much of the coastal region is predominantly flat (−1), limiting directional flow and enhancing water stagnation. Hydrological analysis shows that drainage density is mainly very low to moderate (0 89.89 km\u002Fkm²), indicating high infiltration but increased water retention, while localized high values (89.9–134.8 km\u002Fkm²) enhance runoff. Stream density is highest (228.1–811 km\u002Fkm²) in Delta, Bayelsa, and Rivers States, whereas lower values occur in Edo and Cross River. Flow direction exhibits a dominant east–west pattern, with accumulation values ranging from 1–16, indicating runoff convergence. Distance-to-river analysis shows that large areas lie within 0 1,000 m of river channels. Flood susceptibility is highest in coastal zones and lowest in inland elevated areas. The study demonstrates that terrain morphology and hydrological network characteristics are key determinants of flooding in the region and highlights the effectiveness of geospatial techniques in flood susceptibility assessment and management in the South–South region of Nigeria","本研究利用地理信息系统（GIS）、遥感技术和层次分析法（AHP），评估了地形与水文因素对尼日利亚南南地区洪水易发性的影响。通过分析数字高程模型（DEM）、坡度、坡向、河网密度、河流密度、流向及距河流距离等变量，确定其对洪水的贡献。结果表明，高程从沿海低洼地区（三角洲州、河流州、巴耶尔萨州和阿夸伊博姆州）约13 m，到内陆高地区域（克罗斯河州及埃多州部分地区）约256 m不等。坡度分析表明，沿海地区以极缓坡（0°–3.37°）为主，有利于水分积聚并增加洪水易发性。坡向结果进一步显示，沿海大部分区域以平坦（−1）为主，限制了定向径流并加剧了水分滞留。水文分析表明，河网密度主要为极低至中等（0–89.89 km\u002Fkm²），表明入渗率高但持水量增加，而局部高值（89.9–134.8 km\u002Fkm²）则增强径流。河流密度在三角洲州、巴耶尔萨州和河流州最高（228.1–811 km\u002Fkm²），而在埃多州和克罗斯河州较低。流向呈现主导性的东西向格局，汇流累积值在1–16之间，表明径流汇聚。距河流距离分析显示，大片区域位于河道0–1,000 m范围内。洪水易发性在沿海地带最高，在内陆高地区域最低。研究表明，地形形态和水文网络特征是该地区洪水的关键决定因素，并凸显了地理空间技术在尼日利亚南南地区洪水易发性评估与管理中的有效性。","2026-09-10T00:00:00Z",{"impact":90,"substance":90,"depth":90,"authority":90,"freshness":90,"relevant":90,"comment":3663},"该研究聚焦尼日利亚洪水易发性评估，属地理环境领域，与三农、农业信息化、智慧农业等主题无直接关联，不建议进入每日精选。",[3665],{"name":2464,"url":3658},[34,4,1373],[],{"status":269,"locked":22,"version":47,"method":48,"evidence":3669},{"candidates":3670,"agricultural_evidence":22,"reason":284},[3671,3675,3679],{"code":39,"score":21,"supported":52,"title":3672,"abstract":3673,"tags":3674},[],[55,4,56],[4],{"code":59,"score":60,"supported":52,"title":3676,"abstract":3677,"tags":3678},[],[34,63],[34],{"code":480,"score":8,"supported":22,"title":3680,"abstract":3681,"tags":3682},[],[],[1373],[3684,3685],"洪水风险 遥感 GIS","洪水风险 遥感","洪水风险遥感GIS-2310","10.56201\u002Fijgem.vol.12.no3.2026.pg279.299",{"doi":3687,"openalex_id":3689,"authors":3690,"venue":2464,"cited_by_count":90,"oa_url":3693,"card":3694,"direction":316,"ingested_from":107},"W7212169235",[3691],{"name":3692,"orcid":17},"Anthony Chikaike Nwinye-Harrison","https:\u002F\u002Fiiardjournals.org\u002Fget\u002FIJGEM\u002FVOL. 12 NO. 3 2026\u002FGEOSPATIAL ANALYSIS OF TOPOGRAPHIC 279-299.pdf",{"tldr":3695,"method":3696,"finding":3697,"direction":106,"opportunity":3698},"用GIS、遥感和AHP评估尼日利亚南部地形与水文因子对洪水易发性的影响。","GIS、遥感、AHP，基于DEM、坡度、坡向、河网密度等因子分析。","沿海低平区洪水易发性最高，内陆高地区最低，地形与水文网络是关键决定因素。","可结合实时降雨与土地利用变化，构建动态洪水易发性模型并服务农业风险管理。","2026-09-13T23:30:12.636598Z",{"id":3701,"title":3702,"url":3703,"summary":3704,"summary_zh":3705,"content":17,"source_name":1778,"source_url":3703,"published_at":3706,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":866,"score_detail":3707,"sources":3709,"tags":3711,"primary_topic":3714,"secondary_topics":3715,"classification":3717,"search_phrases":3745,"slug":3748,"view_count":8,"doi":3749,"paper":3750,"created_at":3767},2056,"Land suitability assessment for irrigated lentil cultivation in Southwest Shewa Zone, Ethiopia using remote sensing, GIS, and the analytic hierarchy process","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-70025-3","Sustainable expansion of irrigated agriculture requires accurate identification of suitable land areas based on biophysical conditions. This study evaluates land suitability for irrigated lentils cultivation in Southwest Shewa Zone, Ethiopia, using an integrated Remote Sensing (RS), Geographic Information System (GIS), and Analytical Hierarchy Process (AHP) approach. Nine suitability criteria, including temperature, land use\u002Fland cover, slope, elevation, soil type, soil texture, soil pH, soil drainage, and distance to water sources, were analyzed to develop a spatial suitability map. The AHP approach was applied to determine the relative importance of each criterion, with distance to water (32.5%) and slope (28.2%) identified as the most influential factors. The results classified the study area into four suitability categories: highly suitable (10.47%), moderately suitable (30.47%), marginally suitable (38.88%), and not suitable (20.18%). Model performance was evaluated using Receiver Operating Characteristic (ROC) analysis, producing an Area Under the Curve (AUC) value of 0.766, indicating good predictive performance of the suitability model. The findings reveal that 40.94% of the area has high to moderate potential for irrigated lentils production, while limitations are mainly associated with soil conditions, slope, and water accessibility. The study provides a spatial decision-support framework for identifying suitable areas, prioritizing irrigation development, and promoting sustainable land resource management and climate-resilient lentils production in Ethiopia.","灌溉农业的可持续扩展需要基于生物物理条件准确识别适宜土地区域。本研究采用遥感（RS）、地理信息系统（GIS）与层次分析法（AHP）相结合的方法，评估埃塞俄比亚西南绍阿区灌溉小扁豆种植的土地适宜性。研究分析了九个适宜性指标，包括温度、土地利用\u002F土地覆盖、坡度、海拔、土壤类型、土壤质地、土壤pH值、土壤排水和距水源距离，以绘制空间适宜性图。采用层次分析法确定各指标的相对重要性，其中距水源距离（32.5%）和坡度（28.2%）被识别为影响最大的因素。结果将研究区划分为四个适宜性等级：高度适宜（10.47%）、中度适宜（30.47%）、勉强适宜（38.88%）和不适宜（20.18%）。采用受试者工作特征（ROC）分析评估模型性能，得到曲线下面积（AUC）值为0.766，表明适宜性模型具有良好的预测性能。研究结果表明，40.94%的区域具有灌溉小扁豆生产的高度至中度潜力，而限制因素主要与土壤条件、坡度和水源可及性有关。本研究提供了一个空间决策支持框架，用于识别适宜区域、优先安排灌溉开发，并促进埃塞俄比亚土地资源的可持续管理和气候适应型小扁豆生产。","2026-09-09T00:00:00Z",{"impact":28,"substance":740,"depth":120,"authority":27,"freshness":25,"relevant":8,"comment":3708},"方法集成规范、结论有数据支撑，但属埃塞俄比亚区域案例，对国内三农实践的直接参考价值有限，适合作为农业遥感方法类资讯收录。",[3710],{"name":1778,"url":3703},[34,4,3712,666,3713],"智慧灌溉","小扁豆",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[3716],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":3718},{"candidates":3719,"agricultural_evidence":52},[3720,3724,3728,3732,3736,3741],{"code":39,"score":26,"supported":52,"title":3721,"abstract":3722,"tags":3723},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":3725,"abstract":3726,"tags":3727},[63],[34,63],[34],{"code":74,"score":60,"supported":52,"title":3729,"abstract":3730,"tags":3731},[],[78,674],[3712],{"code":66,"score":67,"supported":52,"title":3733,"abstract":3734,"tags":3735},[],[70,71],[],{"code":480,"score":75,"supported":52,"title":3737,"abstract":3738,"tags":3740},[],[3739],"气候适应",[],{"code":691,"score":8,"supported":22,"title":3742,"abstract":3743,"tags":3744},[],[],[666],[3746,3747],"土地适宜性 智慧灌溉 小扁豆 遥感","土地适宜性 智慧灌溉","土地适宜性智慧灌溉小扁豆遥感-2056","10.1038\u002Fs41598-026-70025-3",{"doi":3749,"openalex_id":3751,"authors":3752,"venue":1778,"cited_by_count":90,"oa_url":3703,"card":3762,"direction":106,"ingested_from":107},"W7211993031",[3753,3754,3756,3758,3759],{"name":301,"orcid":302},{"name":3755,"orcid":17},"Diro Lenjisa Geleto",{"name":3757,"orcid":17},"Aster Chalchisa Eggi",{"name":304,"orcid":305},{"name":3760,"orcid":3761},"Bekele Bedada Damtie","https:\u002F\u002Forcid.org\u002F0000-0003-3673-8560",{"tldr":3763,"method":3764,"finding":3765,"direction":106,"opportunity":3766},"用遥感、GIS与AHP评估埃塞俄比亚西南绍阿区灌溉扁豆种植土地适宜性并制图。","遥感、GIS与层次分析法（AHP），分析9项生物物理与水源距离指标，ROC验证。","高至中度适宜区占40.94%，距水源与坡度影响最大，模型AUC为0.766。","可引入多时相遥感与气候情景，动态评估灌溉适宜性并耦合作物模型优化布局。","2026-09-10T23:30:27.675890Z",{"id":3769,"title":3770,"url":3771,"summary":3772,"summary_zh":3773,"content":17,"source_name":3774,"source_url":3771,"published_at":3775,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":3776,"score_detail":3777,"sources":3779,"tags":3781,"primary_topic":3782,"secondary_topics":3783,"classification":3785,"search_phrases":3822,"slug":3825,"view_count":82,"doi":3826,"paper":3827,"created_at":3844},2000,"ANALYSIS OF LAND USE LAND COVER CHANGE IN THE GLEN VALLEY IRRIGATION SCHEME OF SOUTH-EASTERN BOTSWANA","https:\u002F\u002Fdoi.org\u002F10.30574\u002Fgjeta.2026.28.3.0228","This study focused on assessing land use land cover (LULC) changes in the Glen Valley Irrigation Scheme of South Eastern Botswana between 2002 and 2022. The study employed remote sensing (RS) and geographic information systems (GIS) tools for analysing LULC changes in the study area during the study period. Landsat 7 ETM+ and Landsat 8 OLI images of 6 February 2002 and 21 February 2022, respectively, were used to detect LULC changes. Image classification was done using a supervised classification approach based on a Maximum Likelihood Classifier. Seven LULC types, namely, Built up, Cultivation, Water body, Sparse vegetation, Moderately dense vegetation, Dense vegetation, and Bare ground, were identified in the area. Post Classification Comparison (PCC) approach was used to detect LULC change during the study period. A pronounced 250 ha increase of cultivated land resulted from 13.2% conversion of sparse vegetation, with adverse implication on greenhouse gas (GHG) emissions and global warming. A noticeable 105 ha increase of Built-up area in the City of Gaborone resulted from 4.3% conversion of sparse vegetation, with implications on land planning process related to rapid urbanization. All changes of LULC types relied on availability of sparse vegetation as a key carbon sink and stabilizer of GHG emissions. Mitigation strategies including conservation agriculture, efficient irrigation and renewable energy are considered necessary.","本研究旨在评估2002年至2022年间博茨瓦纳东南部格伦谷灌溉计划区土地利用\u002F土地覆盖（LULC）的变化。研究采用遥感（RS）和地理信息系统（GIS）工具，对研究期间该区域的土地利用\u002F土地覆盖变化进行分析。分别利用2002年2月6日的Landsat 7 ETM+影像和2022年2月21日的Landsat 8 OLI影像来检测土地利用\u002F土地覆盖变化。影像分类采用基于最大似然分类器的监督分类方法。研究区域内识别出七种土地利用\u002F土地覆盖类型，即建设用地、耕地、水体、稀疏植被、中等密度植被、高密度植被和裸地。采用分类后比较（PCC）方法检测研究期间的土地利用\u002F土地覆盖变化。耕地面积显著增加250公顷，其中13.2%来自稀疏植被的转化，这对温室气体（GHG）排放和全球变暖产生了不利影响。哈博罗内市建设用地面积明显增加105公顷，其中4.3%来自稀疏植被的转化，这对与快速城市化相关的土地规划过程产生了影响。所有土地利用\u002F土地覆盖类型的变化均依赖于稀疏植被作为关键碳汇和温室气体排放稳定器的可用性。研究认为，采取保护性农业、高效灌溉和可再生能源等减缓策略十分必要。","Global Journal of Engineering and Technology Advances","2026-09-08T00:00:00Z",58,{"impact":28,"substance":26,"depth":190,"authority":21,"freshness":82,"relevant":8,"comment":3778},"研究利用遥感和GIS分析博茨瓦纳灌溉区土地利用变化，对农业规划有参考价值，但地域偏远且时效性低。",[3780],{"name":3774,"url":3771},[34,35,4,2822],{"code":74,"slug":674,"name":940,"path":941,"parent_code":942},[3784],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":3786},{"candidates":3787,"agricultural_evidence":52},[3788,3792,3796,3800,3807,3813,3818],{"code":74,"score":191,"supported":52,"title":3789,"abstract":3790,"tags":3791},[674],[78,674],[2822],{"code":39,"score":21,"supported":52,"title":3793,"abstract":3794,"tags":3795},[],[55,4,56],[4],{"code":59,"score":60,"supported":52,"title":3797,"abstract":3798,"tags":3799},[],[34,63],[34],{"code":3801,"score":67,"supported":52,"title":3802,"abstract":3803,"tags":3806},"B7",[],[3804,3805],"温室","greenhouse",[],{"code":3808,"score":75,"supported":52,"title":3809,"abstract":3810,"tags":3812},"H4",[],[3811],"碳汇",[],{"code":1565,"score":75,"supported":52,"title":3814,"abstract":3815,"tags":3817},[],[3816],"conservation agriculture",[],{"code":81,"score":8,"supported":22,"title":3819,"abstract":3820,"tags":3821},[],[],[35],[3823,3824],"土地利用 灌溉农业 遥感 GIS","土地利用 灌溉农业","土地利用灌溉农业遥感GIS-2000","10.30574\u002Fgjeta.2026.28.3.0228",{"doi":3826,"openalex_id":3828,"authors":3829,"venue":3774,"cited_by_count":90,"oa_url":3838,"card":3839,"direction":106,"ingested_from":107},"W7211969418",[3830,3832,3834,3836],{"name":3831,"orcid":17},"Lucia Moroka",{"name":3833,"orcid":17},"Benedict Kayombo",{"name":3835,"orcid":17},"Matapa Tapela",{"name":3837,"orcid":17},"Thembeka Mpuisang","https:\u002F\u002Fgjeta.com\u002Fsites\u002Fdefault\u002Ffiles\u002Ffulltext_pdf\u002FGJETA-2026-0228.pdf",{"tldr":3840,"method":3841,"finding":3842,"direction":106,"opportunity":3843},"利用遥感与GIS分析博茨瓦纳Glen Valley灌区2002-2022年土地利用变化，发现耕地和建","采用Landsat影像、监督分类（最大似然法）和分类后比较法分析LULC变化。","耕地增加250公顷，建设用地增加105公顷，主要侵占稀疏植被，影响碳汇和温室气体排放。","可延伸研究灌溉农业扩张对碳汇的影响，结合高分辨率影像和碳模型量化区域碳排放，探索可持续灌溉与土地利用优化策略。","2026-09-09T23:30:22.675859Z",{"id":3846,"title":3847,"url":3848,"summary":3849,"summary_zh":3850,"content":17,"source_name":737,"source_url":3848,"published_at":3851,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2140,"score_detail":3852,"sources":3854,"tags":3856,"primary_topic":17,"secondary_topics":3859,"classification":3860,"search_phrases":3875,"slug":3878,"view_count":90,"doi":3879,"paper":3880,"created_at":3897},1903,"Integration of GIS, remote sensing and AHP technique for delineation of groundwater potential zones in Mahoba district Uttar Pradesh, India","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs44288-026-00716-x","An essential component of life and the ecology is groundwater. This Precious resource is under extreme strain in India due to man-made and natural caused factors. Determining groundwater potential zones (GWPZs) is becoming a more crucial undertaking due to the world’s increasing demand for freshwater. In the current study, the groundwater potential zones of the Mahoba district are identified using geospatial and Analytical Hierarchy Process (AHP) technique. Mahoba district falls in the state of Uttar Pradesh, India which is a very water scare region. The influencing factors that affects the potentiality of the research region i.e. lithology (LI), geomorphology (GM), rainfall, slope, land use and land cover (LULC), lineament density and drainage density taken under the consideration to evaluate the groundwater potential zones. The GIS software was used to create these influencing factors with the satellite images, which is acquired from many websites and organizations. The GWPZs maps were created by superimposing all of the thematic layers on top of one another after the appropriate weights were assigned using AHP technique. The delineated Groundwater potential zones (GWPZs) were divided into several categories, including very high, high, moderate, low, and very low GWPZs. The moderate form of GWPZ occupies the highest area within the research region. Well discharge data was used to validate the obtained GWPZs. The validation shows the 80% accuracy of the model. The proposed research gives the first insights of groundwater exploration.","地下水是生命和生态的重要组成部分。在印度，由于人为和自然因素，这一宝贵资源正承受着极大的压力。鉴于全球对淡水需求的日益增长，确定地下水潜力区（GWPZs）已成为一项日益关键的任务。本研究利用地理空间技术与层次分析法（AHP），识别了马霍巴地区的地下水潜力区。马霍巴地区位于印度北方邦，是一个水资源极度匮乏的区域。研究考虑了影响该区域潜力的因素，包括岩性（LI）、地貌（GM）、降雨量、坡度、土地利用与土地覆盖（LULC）、线性体密度和排水密度，以评估地下水潜力区。利用GIS软件，结合从多个网站和组织获取的卫星图像，生成了这些影响因素图层。通过AHP技术赋予各专题图层适当权重后，将所有图层叠加，生成了地下水潜力区（GWPZs）图。划分出的地下水潜力区被分为多个等级，包括极高、高、中、低和极低潜力区。其中，中等潜力的GWPZ在研究区域内占据面积最大。利用井涌水量数据对所获得的GWPZs进行了验证，结果显示模型精度达到80%。本研究为地下水勘探提供了初步见解。","2026-09-06T00:00:00Z",{"impact":28,"substance":26,"depth":190,"authority":21,"freshness":75,"relevant":8,"comment":3853},"研究结合GIS、遥感和AHP评估印度缺水地区地下水潜力，方法成熟，对农业水资源管理有参考价值，但区域局限且时效性低。",[3855],{"name":737,"url":3848},[2195,4,3857,745,3858],"遥感技术","AHP",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":3861},{"candidates":3862,"agricultural_evidence":22,"reason":284},[3863,3867,3871],{"code":39,"score":28,"supported":52,"title":3864,"abstract":3865,"tags":3866},[4],[4],[4],{"code":59,"score":29,"supported":52,"title":3868,"abstract":3869,"tags":3870},[63],[],[3857],{"code":74,"score":833,"supported":52,"title":3872,"abstract":3873,"tags":3874},[],[477],[2195,745],[3876,3877],"农业水资源 地下水潜力 遥感技术 AHP","农业水资源 地下水潜力","农业水资源地下水潜力遥感技术AHP-1903","10.1007\u002Fs44288-026-00716-x",{"doi":3879,"openalex_id":3881,"authors":3882,"venue":737,"cited_by_count":90,"oa_url":3891,"card":3892,"direction":106,"ingested_from":107},"W7210268114",[3883,3886,3889],{"name":3884,"orcid":3885},"Mahesh Kumar","https:\u002F\u002Forcid.org\u002F0000-0001-7583-4841",{"name":3887,"orcid":3888},"Pitam Singh","https:\u002F\u002Forcid.org\u002F0000-0001-9258-3132",{"name":3890,"orcid":17},"Priyamvada Singh","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs44288-026-00716-x.pdf",{"tldr":3893,"method":3894,"finding":3895,"direction":106,"opportunity":3896},"利用GIS、遥感和AHP技术绘制印度Mahoba地区地下水潜力区，并验证模型精度。","结合GIS、遥感与AHP，叠加岩性、地貌、降雨等七类因子图层。","中等潜力区面积最大，模型验证精度达80%。","可扩展至农业灌溉规划，结合实时水文数据与机器学习提升预测精度。","2026-09-08T23:30:19.133523Z",{"id":3899,"title":3900,"url":3901,"summary":3902,"summary_zh":3903,"content":17,"source_name":587,"source_url":3901,"published_at":3904,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":326,"score_detail":3905,"sources":3907,"tags":3909,"primary_topic":3911,"secondary_topics":3912,"classification":3915,"search_phrases":3942,"slug":3945,"view_count":82,"doi":3946,"paper":3947,"created_at":3964},1768,"Remote Sensing and GIS-Based Spatial Planning of Soil and Water Conservation Measures in a Semi-Arid Watershed Maliwadgaon of Maharashtra, India","https:\u002F\u002Fdoi.org\u002F10.9734\u002Fijecc\u002F2026\u002Fv16i95662","Site-specific planning of water harvesting and soil and water conservation (SWC) measures is important for improving water availability and watershed resilience in semi-arid regions. This study aimed to identify and prioritise suitable locations for SWC structures in the 43 km² Maliwadgaon watershed of Chhatrapati Sambhajinagar district, Maharashtra, India, using an integrated remote sensing (RS) and Geographic Information System (GIS) approach. A 30 m Shuttle Radar Topography Mission (SRTM) Digital Elevation Model and Landsat-8 imagery were used to derive terrain, drainage, land use\u002Fland cover (LULC), and vegetation characteristics. Elevation, slope, drainage density, stream order, dissection index, LULC, and normalized difference vegetation index (NDVI) were integrated through multi-criteria evaluation (MCE) for site-suitability assessment. The watershed has an elevation range of approximately 509–591 m and a dendritic, fourth-order drainage network with a drainage density of 0.991 km\u002Fkm². The MCE identified 40 potential conservation structures: 13 farm ponds, 13 cement nala bunds, 5 percolation tanks, 4 underground barriers, and 5 gully plugs. The proposed locations provide a spatial basis for runoff interception, erosion control, water storage, groundwater recharge, and agricultural water management. The findings demonstrate the practical utility of RS–GIS-based MCE as a decision-support approach for prioritising site-specific SWC interventions in a semi-arid watershed.","在半干旱地区，水资源收集及水土保持（SWC）措施的定点规划对于改善水资源可利用性和增强流域韧性至关重要。本研究旨在利用遥感（RS）与地理信息系统（GIS）集成方法，识别并优先确定印度马哈拉施特拉邦恰特拉帕蒂·桑巴吉纳加尔区Maliwadgaon流域（面积43平方公里）内适宜建设水土保持设施的位置。研究采用30米分辨率的航天飞机雷达地形任务（SRTM）数字高程模型和Landsat-8影像，提取地形、水系、土地利用\u002F土地覆盖（LULC）及植被特征。通过多准则评价（MCE）整合高程、坡度、排水密度、河流等级、切割指数、土地利用\u002F土地覆盖及归一化差异植被指数（NDVI），进行选址适宜性评估。该流域海拔范围约为509–591米，水系呈树枝状，为四级排水网络，排水密度为0.991公里\u002F平方公里。多准则评价识别出40处潜在的水土保持设施：13座田间池塘、13座水泥沟壑拦水坝、5座渗滤池、4座地下屏障及5处冲沟堵截设施。所提出的选址为径流拦截、侵蚀控制、蓄水、地下水补给及农业水资源管理提供了空间依据。研究结果表明，基于遥感与地理信息系统的多准则评价作为一种决策支持方法，在半干旱流域优先确定定点水土保持干预措施方面具有实际应用价值。","2026-09-05T00:00:00Z",{"impact":28,"substance":26,"depth":190,"authority":28,"freshness":82,"relevant":8,"comment":3906},"研究利用遥感和GIS技术在半干旱流域进行水土保持措施选址，方法实用，但时效性较低。",[3908],{"name":587,"url":3901},[2195,34,4,37,3910],"半干旱区",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[3913,3914],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"code":66,"slug":71,"name":2827,"path":2828,"parent_code":942},{"status":46,"locked":22,"version":47,"method":48,"evidence":3916},{"candidates":3917,"agricultural_evidence":52},[3918,3922,3926,3930,3934,3938],{"code":39,"score":26,"supported":52,"title":3919,"abstract":3920,"tags":3921},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":3923,"abstract":3924,"tags":3925},[63],[34,63],[34],{"code":66,"score":752,"supported":52,"title":3927,"abstract":3928,"tags":3929},[71],[71],[],{"code":74,"score":150,"supported":52,"title":3931,"abstract":3932,"tags":3933},[],[477],[2195],{"code":81,"score":150,"supported":52,"title":3935,"abstract":3936,"tags":3937},[],[37],[37],{"code":480,"score":75,"supported":52,"title":3939,"abstract":3940,"tags":3941},[],[483],[],[3943,3944],"农业水资源 半干旱区 水土保持 遥感","农业水资源 半干旱区","农业水资源半干旱区水土保持遥感-1768","10.9734\u002Fijecc\u002F2026\u002Fv16i95662",{"doi":3946,"openalex_id":3948,"authors":3949,"venue":587,"cited_by_count":90,"oa_url":3901,"card":3959,"direction":106,"ingested_from":107},"W7208812908",[3950,3953,3955,3957],{"name":3951,"orcid":3952},"Prasannajit D. Gangurde","https:\u002F\u002Forcid.org\u002F0009-0002-9266-8931",{"name":3954,"orcid":17},"Sanjay N. Pawar",{"name":3956,"orcid":17},"M. S. Pendke",{"name":3958,"orcid":17},"Anilkumar M. Kamble",{"tldr":3960,"method":3961,"finding":3962,"direction":106,"opportunity":3963},"利用遥感和GIS对半干旱流域进行水土保持措施的空间规划与选址。","集成SRTM DEM、Landsat-8影像，通过多准则评价进行选址。","识别出40个潜在保护结构，包括池塘、堤坝等，用于水资源管理。","可扩展至其他半干旱流域，结合高分辨率影像和机器学习优化选址精度。","2026-09-06T23:30:27.290464Z",{"id":3966,"title":3967,"url":3968,"summary":3969,"summary_zh":3970,"content":17,"source_name":3971,"source_url":3968,"published_at":3972,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":3776,"score_detail":3973,"sources":3975,"tags":3977,"primary_topic":17,"secondary_topics":3979,"classification":3980,"search_phrases":4007,"slug":4010,"view_count":8,"doi":4011,"paper":4012,"created_at":4041},1738,"Integrated Remote Sensing and GIS-Based Agricultural Drought Vulnerability Assessment in Sivagangai District, Tamil Nadu, India","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fbiosphere2030009","Agricultural drought is an important issue for food security, water availability and rural livelihoods, particularly in the semi-arid regions of the Indian state of Tamil Nadu, especially in Sivagangai District. This study combines multi-temporal remote sensing data and GIS techniques to evaluate the agricultural drought vulnerability during a 30-year time frame (1994–2024). Landsat satellite imagery and climate data were used to derive some key bio-physical indicators such as NDVI, NDWI, VCI, SMI, LST, LULC and SPI. An AHP was used to assign weights to each parameter and was created. The spatiotemporal analysis shows that there is a substantial reduction in vegetated and moist areas as well as a high growth of high and very high temperature areas and built-up land. The percentage of areas classified as ‘Very High’ drought vulnerability has increased significantly from 1.08% (1994) to 40.04% (2024), highlighting a growing threat from drought conditions. NDVI and NDWI were chosen as the most significant indices that affect drought. The findings reflect the deteriorating environmental condition and stress the need for specific mitigation measures, including afforestation, sustainable land-use planning and management of water resources. This study is both spatially explicit and scalable; it provides key information to local planners, policymakers and stakeholders to support agricultural resilience in drought-prone regions.","农业干旱是粮食安全、水资源供应和农村生计面临的重要问题，尤其是在印度泰米尔纳德邦半干旱地区，特别是西瓦冈盖县。本研究结合多时相遥感数据和GIS技术，评估了1994年至2024年30年间的农业干旱脆弱性。利用Landsat卫星影像和气候数据，提取了若干关键生物物理指标，如NDVI、NDWI、VCI、SMI、LST、LULC和SPI。采用层次分析法（AHP）为各参数赋予权重并构建模型。时空分析表明，植被覆盖区和湿润区面积显著减少，而高温和极高温度区域以及建设用地面积大幅增加。被归类为“极高”干旱脆弱性的区域比例从1994年的1.08%显著上升至2024年的40.04%，凸显了干旱状况日益加剧的威胁。NDVI和NDWI被确定为影响干旱的最重要指标。研究结果反映了环境状况的恶化，并强调了采取具体缓解措施的必要性，包括植树造林、可持续土地利用规划和水资源管理。本研究兼具空间明确性和可扩展性，为当地规划者、政策制定者和利益相关者提供了关键信息，以支持干旱易发地区的农业韧性建设。","Biosphere","2026-09-04T00:00:00Z",{"impact":28,"substance":26,"depth":190,"authority":21,"freshness":82,"relevant":8,"comment":3974},"基于遥感和GIS的农业干旱脆弱性评估，方法成熟，数据详实，对区域农业防灾有参考价值。",[3976],{"name":3971,"url":3968},[1785,3978,4,2664],"农业信息化",[],{"status":269,"locked":22,"version":47,"method":48,"evidence":3981},{"candidates":3982,"agricultural_evidence":52,"reason":695},[3983,3987,3991,3995,3999,4003],{"code":480,"score":191,"supported":52,"title":3984,"abstract":3985,"tags":3986},[2681],[483,2681],[2664],{"code":59,"score":191,"supported":52,"title":3988,"abstract":3989,"tags":3990},[63],[34,63],[1785],{"code":39,"score":28,"supported":52,"title":3992,"abstract":3993,"tags":3994},[4],[4],[4],{"code":222,"score":67,"supported":52,"title":3996,"abstract":3997,"tags":3998},[],[225,226],[],{"code":74,"score":75,"supported":52,"title":4000,"abstract":4001,"tags":4002},[],[477],[],{"code":894,"score":8,"supported":22,"title":4004,"abstract":4005,"tags":4006},[],[],[3978],[4008,4009],"农业信息化 农业遥感 干旱监测 GIS","农业信息化 农业遥感","农业信息化农业遥感干旱监测GIS-1738","10.3390\u002Fbiosphere2030009",{"doi":4011,"openalex_id":4013,"authors":4014,"venue":3971,"cited_by_count":90,"oa_url":3968,"card":4036,"direction":106,"ingested_from":107},"W7208763077",[4015,4018,4021,4024,4027,4030,4033],{"name":4016,"orcid":4017},"Kongeswaran Thangaraj","https:\u002F\u002Forcid.org\u002F0000-0002-0752-8727",{"name":4019,"orcid":4020},"M. Rajendran","https:\u002F\u002Forcid.org\u002F0000-0001-7944-7259",{"name":4022,"orcid":4023},"Perumal Velmayil","https:\u002F\u002Forcid.org\u002F0000-0002-5744-0870",{"name":4025,"orcid":4026},"Venkatramanan Senapathi","https:\u002F\u002Forcid.org\u002F0000-0002-1698-1101",{"name":4028,"orcid":4029},"Prabakaran Kulandaisamy","https:\u002F\u002Forcid.org\u002F0000-0002-3393-8033",{"name":4031,"orcid":4032},"Raghu R. Krishnamoorthy","https:\u002F\u002Forcid.org\u002F0000-0001-7278-4324",{"name":4034,"orcid":4035},"Sakthi Sivakumar","https:\u002F\u002Forcid.org\u002F0009-0001-5839-8096",{"tldr":4037,"method":4038,"finding":4039,"direction":106,"opportunity":4040},"利用遥感和GIS评估印度Sivagangai地区农业干旱脆弱性，发现极高脆弱区从1.08%增至40.","结合Landsat影像和气候数据，计算NDVI、NDWI等指标，采用AHP加权和","植被和湿润区减少，高温和建设用地增加，干旱脆弱性显著上升，NDVI和NDWI是关键指标。","可扩展至其他半干旱区，结合高分辨率影像和机器学习优化权重，并纳入社会经济因素以增强适应性策略。","2026-09-05T23:30:27.688056Z",{"id":4043,"title":4044,"url":4045,"summary":4046,"summary_zh":4047,"content":17,"source_name":4048,"source_url":4045,"published_at":4049,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":2743,"score_detail":4050,"sources":4052,"tags":4054,"primary_topic":4057,"secondary_topics":4058,"classification":4059,"search_phrases":4078,"slug":4081,"view_count":8,"doi":4082,"paper":4083,"created_at":4091},1626,"Assessing and Mapping Drought Vulnerability Areas in Homa Bay County, Kenya","https:\u002F\u002Fdoi.org\u002F10.59765\u002Fkfw6y","Drought is a recurring environmental hazard in Homa Bay County, Kenya, affecting agriculture, water resources, and community livelihoods.Despite its impacts, there is limited spatially explicit information on drought-prone areas within the county.This study aimed to map drought vulnerability in Homa Bay County using remote sensing and GIS techniques.The study was anchored on two theories; Disaster risk reduction theory and Vulnerability theory.The study used MODIS NDVI data (2020-2023) to map drought severity, while ESA World Cover land use and CHIRPS rainfall data were integrated as vulnerability factors.A weighted overlay analysis was run in QGIS to combine three factors: drought severity (50%), land use (30%), and rainfall (20%).The final vulnerability map was classified into four classes: low, moderate, mild, and severe.The results show that 0.91% of the county falls under severe vulnerability, concentrated in Mbita and Karachuonyo sub-counties.Moderate vulnerability dominates 53.69% of the county, followed by mild (31.22%) and low (14.18%).The study provides spatially explicit information to support county-level drought planning and intervention strategies.The paper recommends development in severe vulnerable counties; Mbita and Karachuonyo with carefully drought planning and intervention strategies.","干旱是肯尼亚霍马贝县反复出现的环境灾害，影响农业、水资源和社区生计。尽管其影响重大，但该县内关于干旱易发区域的空间明确信息仍然有限。本研究旨在利用遥感和GIS技术绘制霍马贝县的干旱脆弱性地图。研究基于两大理论：灾害风险减轻理论和脆弱性理论。研究使用MODIS NDVI数据（2020-2023年）绘制干旱严重程度图，同时整合ESA World Cover土地利用数据和CHIRPS降雨数据作为脆弱性因素。在QGIS中进行了加权叠加分析，以综合三个因素：干旱严重程度（50%）、土地利用（30%）和降雨量（20%）。最终脆弱性地图分为四个等级：低、中、轻度和严重。结果显示，该县0.91%的面积属于严重脆弱性，集中在姆比塔和卡拉丘奥尼分区。中度脆弱性占全县面积的53.69%，其次是轻度（31.22%）和低度（14.18%）。本研究提供了空间明确的信息，以支持县级干旱规划和干预策略。论文建议在严重脆弱的分区——姆比塔和卡拉丘奥尼，制定周密的干旱规划和干预策略。","Journal of Research Innovation and Implications in Education","2026-09-02T00:00:00Z",{"impact":25,"substance":26,"depth":190,"authority":21,"freshness":75,"relevant":8,"comment":4051},"研究利用遥感与GIS技术绘制肯尼亚Homa Bay县干旱脆弱性地图，为当地农业规划提供空间信息，但影响范围局限于县级，时效性较低。",[4053],{"name":4048,"url":4045},[1785,4055,4,2664,4056],"肯尼亚","灾害评估",{"code":480,"slug":2668,"name":2669,"path":2670,"parent_code":942},[],{"status":46,"locked":22,"version":47,"method":48,"evidence":4060},{"candidates":4061,"agricultural_evidence":52},[4062,4066,4070,4074],{"code":480,"score":190,"supported":52,"title":4063,"abstract":4064,"tags":4065},[2681],[483,2681],[2664,4056],{"code":59,"score":60,"supported":52,"title":4067,"abstract":4068,"tags":4069},[],[34,63],[1785],{"code":39,"score":150,"supported":52,"title":4071,"abstract":4072,"tags":4073},[],[4],[4],{"code":74,"score":75,"supported":52,"title":4075,"abstract":4076,"tags":4077},[],[477],[],[4079,4080],"农业遥感 干旱监测 灾害评估 肯尼亚","农业遥感 干旱监测","农业遥感干旱监测灾害评估肯尼亚-1626","10.59765\u002Fkfw6y",{"doi":4082,"openalex_id":4084,"authors":4085,"venue":4048,"cited_by_count":90,"oa_url":4045,"card":4086,"direction":316,"ingested_from":107},"W7206217503",[],{"tldr":4087,"method":4088,"finding":4089,"direction":106,"opportunity":4090},"利用遥感和GIS技术绘制肯尼亚霍马贝县干旱脆弱性地图，识别脆弱区域。","MODIS NDVI、ESA土地覆盖和CHIRPS降雨数据，加权叠加分析。","严重脆弱区占0.91%，集中在Mbita和Karachuonyo；中度脆弱占53.69%。","可扩展至其他地区，结合社会经济数据，提高干旱脆弱性评估精度，并制定针对性适应策略。","2026-09-04T23:30:13.864272Z",{"id":4093,"title":4094,"url":4095,"summary":4096,"summary_zh":4097,"content":17,"source_name":4098,"source_url":4095,"published_at":4099,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":1532,"score_detail":4100,"sources":4102,"tags":4104,"primary_topic":4108,"secondary_topics":4109,"classification":4111,"search_phrases":4130,"slug":4133,"view_count":8,"doi":4134,"paper":4135,"created_at":4159},1613,"Landscape heterogeneity and integrated landscape management practices in Benin: a remote sensing, GIS, and stakeholder-based analysis","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1898550","Introduction Balancing social, economic, and environmental priorities remains a central challenge in integrated landscape management (ILM). Despite increasing recognition of ILM as a framework for addressing these interconnected objectives, empirical evidence on how landscape heterogeneity influences the implementation of ILM practices remains limited, particularly in tropical socio-ecological systems. This study aimed to develop a systematic characterization of landscape unit types in the Agoua Forest Massifs, Monts Kouffé, and Wari-Maro region in central Benin, with a specific focus on integrated landscape management practices. Methods The study combined remote sensing and Geographic Information Systems (GIS) with a participatory approach involving local stakeholders. First, high-resolution satellite imagery was used to generate a detailed map of landscape unit types, highlighting dominant land-use and land-cover patterns. In a second step, household surveys conducted with 459 randomly selected households were used to identify the range of integrated landscape management practices implemented within each landscape unit. Adoption patterns were first summarized using descriptive statistics and Pearson’s chi-square tests, while composite adoption scores for the four ILM pillars (production systems, biodiversity conservation, livelihoods, and conflict management) were compared among landscape units using the Kruskal-Wallis test. Results Four landscape unit types were identified: Mixed Forest-Cropland Landscape (LU1), Agricultural Production Landscape (LU2), Forest-Dominated Landscape (LU3), and Agroforestry Landscape (LU4). LU1 is characterized by a predominance of natural woody vegetation (46% of land cover), whereas LU2 shows a higher proportion of annual cropland (38%). LU3 is strongly dominated by natural woody vegetation (70%), while LU4 exhibits the highest share of tree-based cropping systems (46%). The implementation of ILM practices differed significantly among landscape units across all four pillars (Kruskal-Wallis, p \u003C 0.001). Practices related to production systems and biodiversity, such as crop diversification, agroforestry, and soil fertility management, were more frequently implemented in LU3 and LU4 than in LU1 and LU2. Livelihood diversification and conflict management practices also showed greater implementation in these more heterogeneous landscape units. Discussion Overall, the findings demonstrate that landscape heterogeneity is associated with distinct combinations of ILM practices and that the different landscape units play complementary roles in supporting agricultural production, biodiversity conservation, rural livelihoods, and local resource governance. This study provides a spatially explicit empirical basis for understanding the implementation of ILM in tropical landscapes and contributes to informing future landscape assessments in Sub-Saharan Africa.","平衡社会、经济与环境优先事项仍是综合景观管理（ILM）中的核心挑战。尽管ILM作为应对这些相互关联目标的框架日益受到认可，但关于景观异质性如何影响ILM实践实施的实证证据仍然有限，尤其是在热带社会-生态系统方面。本研究旨在对贝宁中部Agoua森林地块、Monts Kouffé和Wari-Maro地区的景观单元类型进行系统化表征，重点关注综合景观管理实践。方法：本研究将遥感与地理信息系统（GIS）同涉及当地利益相关者的参与式方法相结合。首先，利用高分辨率卫星影像生成详细的景观单元类型图，突出主要土地利用和土地覆盖模式。其次，对随机选取的459户家庭进行入户调查，以识别各景观单元内实施的各种综合景观管理实践。采用描述性统计和皮尔逊卡方检验对采纳模式进行初步总结，同时运用Kruskal-Wallis检验比较各景观单元在ILM四大支柱（生产系统、生物多样性保护、生计和冲突管理）方面的综合采纳得分。结果：共识别出四种景观单元类型：混合森林-农田景观（LU1）、农业生产景观（LU2）、森林主导景观（LU3）和农林业景观（LU4）。LU1以天然木本植被为主（占土地覆盖的46%），而LU2的一年生农田比例较高（38%）。LU3以天然木本植被占绝对主导（70%），LU4则以木本作物种植系统占比最高（46%）。各景观单元在四大支柱方面的ILM实践实施情况存在显著差异（Kruskal-Wallis检验，p \u003C 0.001）。与生产系统和生物多样性相关的实践，如作物多样化、农林业和土壤肥力管理，在LU3和LU4中的实施频率高于LU1和LU2。生计多样化和冲突管理实践在这些异质性较高的景观单元中也表现出更高的实施水平。讨论：总体而言，研究结果表明景观异质性与ILM实践的实施存在关联。","Frontiers in Sustainable Food Systems","2026-09-03T00:00:00Z",{"impact":28,"substance":119,"depth":26,"authority":28,"freshness":60,"relevant":8,"comment":4101},"基于遥感和GIS的贝宁景观异质性与综合景观管理实践研究，数据详实，对热带农业景观管理有参考价值。",[4103],{"name":4098,"url":4095},[1785,4105,4,4106,4107],"热带农业","景观管理","贝宁",{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},[4110],{"code":59,"slug":338,"name":339,"path":340,"parent_code":43},{"status":46,"locked":22,"version":47,"method":48,"evidence":4112},{"candidates":4113,"agricultural_evidence":52},[4114,4118,4122,4126],{"code":39,"score":26,"supported":52,"title":4115,"abstract":4116,"tags":4117},[4],[55,4,56],[4],{"code":59,"score":191,"supported":52,"title":4119,"abstract":4120,"tags":4121},[63],[34,63],[1785],{"code":66,"score":67,"supported":52,"title":4123,"abstract":4124,"tags":4125},[],[70,71],[],{"code":81,"score":67,"supported":52,"title":4127,"abstract":4128,"tags":4129},[],[890,891],[],[4131,4132],"农业遥感 景观管理 热带农业 贝宁","农业遥感 景观管理","农业遥感景观管理热带农业贝宁-1613","10.3389\u002Ffsufs.2026.1898550",{"doi":4134,"openalex_id":4136,"authors":4137,"venue":4098,"cited_by_count":90,"oa_url":4153,"card":4154,"direction":316,"ingested_from":107},"W7207777106",[4138,4141,4143,4146,4148,4151],{"name":4139,"orcid":4140},"Symphorien Dossouhoui","https:\u002F\u002Forcid.org\u002F0000-0003-2822-6610",{"name":4142,"orcid":17},"Comlan Hervé Sossou",{"name":4144,"orcid":4145},"Epiphane Sodjinou","https:\u002F\u002Forcid.org\u002F0000-0002-6350-2273",{"name":4147,"orcid":17},"Omoto Aurelle Christelle Sedegnan",{"name":4149,"orcid":4150},"Gérard Nounagnon Gouwakinnou","https:\u002F\u002Forcid.org\u002F0000-0002-3595-9831",{"name":4152,"orcid":17},"Niéyidouba Lamien","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1898550\u002Fpdf",{"tldr":4155,"method":4156,"finding":4157,"direction":106,"opportunity":4158},"结合遥感和GIS与利益相关者参与，分析贝宁中部景观异质性对综合景观管理实践的影响。","遥感与GIS制图，459户调查，卡方检验和Kruskal-Wallis检验。","景观异质性显著影响ILM实践，森林和农林景观中实践更丰富。","可探索景观异质性指标与ILM实践成效的定量关系，为区域可持续管理提供决策支持。","2026-09-04T23:30:08.228101Z",{"id":4161,"title":4162,"url":4163,"summary":4164,"summary_zh":4165,"content":17,"source_name":4166,"source_url":4163,"published_at":4167,"category":20,"cover_url":17,"hotness":21,"is_selected":22,"score":4168,"score_detail":4169,"sources":4171,"tags":4173,"primary_topic":4176,"secondary_topics":4177,"classification":4184,"search_phrases":4239,"slug":4242,"view_count":8,"doi":4243,"paper":4244,"created_at":4286},1442,"Morphological, Taxonomic and Soil Suitability Evaluation for Sustainable Crop Production Using GIS and Remote Sensing in Gudvella Block, Balangir District, Odisha State, India","https:\u002F\u002Fdoi.org\u002F10.56557\u002Fjoban\u002F2026\u002Fv18i211054","A comprehensive soil-landscape assessment was undertaken to characterise the morphological, physicochemical and taxonomic properties of soils and to evaluate their suitability for major crops using a GIS-based approach. The study area exhibited considerable physiographic heterogeneity, comprising upper and lower pedi-plains, depressions, hillside slopes, foothill slopes, hillocks and stream-bank positions. Twenty-five representative pedons were examined for morphological and physicochemical characteristics and classified according to Soil Taxonomy. Soil depth varied from 14 to 125 cm, while textures ranged from loamy-skeletal to fine. Soil reaction ranged from strongly acidic to slightly alkaline (pH 4.97-7.85), whereas electrical conductivity (0.01-0.08 dS m-1) and exchangeable sodium percentage (0.56-8.35%) indicated negligible salinity and sodicity constraints. Organic carbon was generally low (0.05-0.50%), while CEC (3.85-37.69 cmol(p⁺) kg-1) and base saturation (21.04-72.90%) varied substantially among pedons. The soils were classified mainly as Entisols, Inceptisols and Alfisols, with Aquic, Lithic, Vertic and related intergrades reflecting contrasting soil-forming environments. Crop suitability assessment revealed marked differences among land-use types. Paddy had 68.3% of the area within the S1-S3 classes, whereas maize, potato and sugarcane each occupied approximately 86% within S2-S3. Cotton, mustard and sunflower were predominantly marginally suitable, with substantial areas classified as N1. Approximately 4% of the area was permanently unsuitable (N2). The results demonstrate that soil suitability is controlled by the interaction of soil properties and landscape processes. The integration of soil survey, taxonomy and GIS-based suitability evaluation provides a robust basis for crop-specific land-use planning, soil and water conservation and sustainable agricultural intensification.","为表征土壤的形态学、物理化学及分类学特性，并采用基于GIS的方法评估其对主要作物的适宜性，开展了一项综合的土壤-景观评估。研究区域表现出显著的地貌异质性，包括上、下麓原、洼地、山坡、山麓坡、丘陵及河岸带。对25个代表性土壤剖面进行了形态学和物理化学特性分析，并根据土壤系统分类法进行分类。土壤深度变化范围为14至125厘米，质地从壤质砾石到细质不等。土壤反应范围从强酸性到微碱性（pH 4.97-7.85），而电导率（0.01-0.08 dS m⁻¹）和交换性钠百分比（0.56-8.35%）表明盐分和钠质限制可忽略不计。有机碳普遍较低（0.05-0.50%），而阳离子交换量（3.85-37.69 cmol(p⁺) kg⁻¹）和盐基饱和度（21.04-72.90%）在各剖面间差异显著。土壤主要归类为新成土、始成土和淋溶土，其中包含潮湿润、石质、变性及相关的过渡类型，反映了不同的成土环境。作物适宜性评估揭示了不同土地利用类型间的显著差异。水稻有68.3%的面积属于S1-S3等级，而玉米、马铃薯和甘蔗在S2-S3等级中各占约86%。棉花、芥菜和向日葵主要为边缘适宜，有相当面积的区域被归类为N1。约4%的区域为永久不适宜（N2）。结果表明，土壤适宜性受土壤性质与景观过程相互作用的控制。土壤调查、分类学与基于GIS的适宜性评价的整合，为特定作物的土地利用规划、水土保持及可持续农业集约化提供了坚实基础。","Journal of biology and nature","2026-09-01T00:00:00Z",52,{"impact":25,"substance":26,"depth":190,"authority":25,"freshness":82,"relevant":8,"comment":4170},"区域土壤适宜性评价研究，数据详实，但影响范围有限，时效性较低。",[4172],{"name":4166,"url":4163},[1785,4174,4175,4],"土壤调查","作物适宜性",{"code":66,"slug":71,"name":2827,"path":2828,"parent_code":942},[4178,4179],{"code":39,"slug":40,"name":41,"path":42,"parent_code":43},{"code":4180,"slug":4181,"name":4182,"path":4183,"parent_code":1306},"A6","cash-crops","棉麻糖与特色经作","\u002Ftopic\u002Ffield-crops\u002Fcash-crops",{"status":46,"locked":22,"version":47,"method":48,"evidence":4185},{"candidates":4186,"agricultural_evidence":52},[4187,4191,4195,4203,4207,4211,4218,4225,4231,4235],{"code":66,"score":27,"supported":52,"title":4188,"abstract":4189,"tags":4190},[71],[70,71],[],{"code":39,"score":28,"supported":52,"title":4192,"abstract":4193,"tags":4194},[4],[4],[4],{"code":4180,"score":29,"supported":52,"title":4196,"abstract":4197,"tags":4202},[],[4198,4199,4200,4201],"棉花","甘蔗","cotton","sugarcane",[],{"code":59,"score":29,"supported":52,"title":4204,"abstract":4205,"tags":4206},[63],[],[1785],{"code":213,"score":67,"supported":52,"title":4208,"abstract":4209,"tags":4210},[],[216,219],[],{"code":4212,"score":67,"supported":52,"title":4213,"abstract":4214,"tags":4217},"A3",[],[4215,4216],"玉米","maize",[],{"code":4219,"score":67,"supported":52,"title":4220,"abstract":4221,"tags":4224},"A5",[],[4222,4223],"马铃薯","potato",[],{"code":4226,"score":75,"supported":52,"title":4227,"abstract":4228,"tags":4230},"A4",[],[4229],"向日葵",[],{"code":81,"score":75,"supported":52,"title":4232,"abstract":4233,"tags":4234},[],[37],[],{"code":1565,"score":75,"supported":52,"title":4236,"abstract":4237,"tags":4238},[],[1538],[],[4240,4241],"作物适宜性 农业遥感 土壤调查 GIS","作物适宜性 农业遥感","作物适宜性农业遥感土壤调查GIS-1442","10.56557\u002Fjoban\u002F2026\u002Fv18i211054",{"doi":4243,"openalex_id":4245,"authors":4246,"venue":4166,"cited_by_count":90,"oa_url":4163,"card":4281,"direction":106,"ingested_from":107},"W7204891281",[4247,4249,4251,4254,4256,4259,4261,4263,4265,4267,4269,4271,4273,4275,4277,4279],{"name":4248,"orcid":17},"D. N. Roy",{"name":4250,"orcid":17},"Shaikh Mohitpasha",{"name":4252,"orcid":4253},"Saumen Saha","https:\u002F\u002Forcid.org\u002F0000-0003-2768-883X",{"name":4255,"orcid":17},"D. C. Sarkar",{"name":4257,"orcid":4258},"M. K. Singh","https:\u002F\u002Forcid.org\u002F0000-0003-0118-3614",{"name":4260,"orcid":17},"Sumit Raizada",{"name":4262,"orcid":17},"Ravi Gautam",{"name":4264,"orcid":17},"Monika",{"name":4266,"orcid":17},"Indra Bahadur",{"name":4268,"orcid":17},"R.T. Bankar",{"name":4270,"orcid":17},"R. K. Setia",{"name":4272,"orcid":17},"R. L. Meena",{"name":4274,"orcid":17},"N. S. Gahlod",{"name":4276,"orcid":17},"Y. Suresh Kumar",{"name":4278,"orcid":17},"Kumar Rajeev",{"name":4280,"orcid":17},"S. K. Tripathi",{"tldr":4282,"method":4283,"finding":4284,"direction":106,"opportunity":4285},"利用GIS和遥感评估印度某地块土壤特性及作物适宜性，为可持续生产提供规划依据。","土壤调查、形态理化分析、土壤分类及GIS适宜性评价。","水稻适宜性高，棉花等边际适宜，约4%永久不宜，需针对性规划。","可结合高分辨率遥感与机器学习，动态监测土壤属性并预测作物适宜性，提升区域精准农业决策。","2026-09-02T23:30:53.627384Z"]