[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4585":3,"related-4585":105},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":23,"tags":25,"primary_topic":31,"secondary_topics":37,"classification":38,"search_phrases":71,"slug":74,"view_count":21,"doi":75,"paper":76,"created_at":104},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。",null,"Discover Hazards","2026-10-09T00:00:00Z","论文",10,false,64,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,20,16,12,1,"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。",[24],{"name":10,"url":6},[26,27,28,29,30],"遥感","土地利用","GIS","灾害风险","滑坡易发性",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":45},[44,51,58,66],{"code":32,"score":13,"supported":45,"title":46,"abstract":47,"tags":50},true,[],[48,28,49],"地理信息","geographic information",[28],{"code":52,"score":53,"supported":45,"title":54,"abstract":55,"tags":57},"I3",7,[],[26,56],"remote sensing",[26],{"code":59,"score":60,"supported":45,"title":61,"abstract":62,"tags":65},"H2",6,[],[63,64],"土壤","soil",[],{"code":67,"score":21,"supported":14,"title":68,"abstract":69,"tags":70},"H6",[],[],[27],[72,73],"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":75,"openalex_id":77,"authors":78,"venue":10,"cited_by_count":96,"oa_url":6,"card":97,"direction":101,"ingested_from":103},"W7221122595",[79,82,84,86,88,90,92,94],{"name":80,"orcid":81},"Engdaw Gulbet Tebege","https:\u002F\u002Forcid.org\u002F0009-0008-4252-1249",{"name":83,"orcid":9},"Belete Getahun",{"name":85,"orcid":9},"Yohannes Dessalegn Girma",{"name":87,"orcid":9},"Yibeltal Awoke Temeche",{"name":89,"orcid":9},"Worku Birhan Fenklew",{"name":91,"orcid":9},"Ayalnesh Mihrete Tagele",{"name":93,"orcid":9},"Gashaw Tesfaw Chekole",{"name":95,"orcid":9},"Muluken Mintesinot",0,{"tldr":98,"method":99,"finding":100,"direction":101,"opportunity":102},"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。","农业遥感与作物表型","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。","openalex","2026-10-10T23:30:27.880607Z",{"total":60,"page":21,"page_size":60,"items":106},[107,175,237,296,380,453],{"id":108,"title":109,"url":110,"summary":111,"summary_zh":112,"content":9,"source_name":113,"source_url":110,"published_at":114,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":115,"score_detail":116,"sources":121,"tags":123,"primary_topic":126,"secondary_topics":127,"classification":128,"search_phrases":155,"slug":158,"view_count":96,"doi":159,"paper":160,"created_at":174},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。","Frontiers in Life Sciences and Related Technologies","2026-10-21T00:00:00Z",61,{"impact":17,"substance":117,"depth":118,"authority":20,"freshness":119,"relevant":21,"comment":120},18,14,9,"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。",[122],{"name":113,"url":110},[26,27,124,28,125],"土壤侵蚀","水土保持",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":129},{"candidates":130,"agricultural_evidence":45},[131,135,139,143,150],{"code":32,"score":13,"supported":45,"title":132,"abstract":133,"tags":134},[],[48,28,49],[28],{"code":52,"score":53,"supported":45,"title":136,"abstract":137,"tags":138},[],[26,56],[26],{"code":59,"score":60,"supported":45,"title":140,"abstract":141,"tags":142},[],[63,64],[],{"code":144,"score":145,"supported":45,"title":146,"abstract":147,"tags":149},"H3",3,[],[148],"灌溉",[],{"code":67,"score":151,"supported":14,"title":152,"abstract":153,"tags":154},2,[],[],[27,125],[156,157],"ICONA 模型 侵蚀风险","Kanak 流域 侵蚀","ICONA模型侵蚀风险-5572","10.51753\u002Fflsrt.1828829",{"doi":159,"openalex_id":161,"authors":162,"venue":113,"cited_by_count":96,"oa_url":9,"card":168,"direction":101,"ingested_from":103},"W7223117733",[163,165],{"name":164,"orcid":9},"MERİÇ KURT",{"name":166,"orcid":167},"Celal ŞENOL","https:\u002F\u002Forcid.org\u002F0000-0003-0857-866X",{"tldr":169,"method":170,"finding":171,"direction":172,"opportunity":173},"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。","2026-10-22T11:20:39.475037Z",{"id":176,"title":177,"url":178,"summary":179,"summary_zh":180,"content":9,"source_name":181,"source_url":178,"published_at":182,"category":12,"cover_url":9,"hotness":183,"is_selected":14,"score":184,"score_detail":185,"sources":187,"tags":191,"primary_topic":194,"secondary_topics":195,"classification":200,"search_phrases":215,"slug":218,"view_count":21,"doi":219,"paper":220,"created_at":236},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。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-30T00:00:00Z",25,65,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":119,"relevant":21,"comment":186},"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。",[188,189],{"name":181,"url":178},{"name":181,"url":190},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23053480",[26,27,192,28,193],"Landsat","城市化",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[196],{"code":52,"slug":197,"name":198,"path":199,"parent_code":36},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",{"status":39,"locked":14,"version":40,"method":41,"evidence":201},{"candidates":202,"agricultural_evidence":45},[203,207,211],{"code":32,"score":13,"supported":45,"title":204,"abstract":205,"tags":206},[],[48,28,49],[28],{"code":52,"score":17,"supported":45,"title":208,"abstract":209,"tags":210},[],[26,56],[192,26],{"code":67,"score":21,"supported":14,"title":212,"abstract":213,"tags":214},[],[],[27],[216,217],"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":219,"openalex_id":221,"authors":222,"venue":181,"cited_by_count":96,"oa_url":178,"card":231,"direction":101,"ingested_from":103},"W7214889813",[223,225,227,229],{"name":224,"orcid":9},"Kalyani Machhindra sonawane",{"name":226,"orcid":9},"Sumitra Nandkumar Nikam",{"name":228,"orcid":9},"Sunil W. Gaikwad",{"name":230,"orcid":9},"Yogesh N. Pawar",{"tldr":232,"method":233,"finding":234,"direction":101,"opportunity":235},"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":238,"title":239,"url":240,"summary":241,"summary_zh":242,"content":9,"source_name":181,"source_url":240,"published_at":243,"category":12,"cover_url":9,"hotness":183,"is_selected":14,"score":244,"score_detail":245,"sources":248,"tags":252,"primary_topic":255,"secondary_topics":256,"classification":257,"search_phrases":272,"slug":275,"view_count":21,"doi":276,"paper":277,"created_at":295},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":60,"substance":19,"depth":246,"authority":20,"freshness":119,"relevant":21,"comment":247},13,"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。",[249,250],{"name":181,"url":240},{"name":181,"url":251},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22865602",[26,27,28,253,254],"土地分类","校园规划",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":258},{"candidates":259,"agricultural_evidence":45},[260,264,268],{"code":32,"score":13,"supported":45,"title":261,"abstract":262,"tags":263},[],[48,28,49],[28],{"code":52,"score":53,"supported":45,"title":265,"abstract":266,"tags":267},[],[26,56],[26],{"code":67,"score":21,"supported":14,"title":269,"abstract":270,"tags":271},[],[],[27],[273,274],"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":276,"openalex_id":278,"authors":279,"venue":181,"cited_by_count":96,"oa_url":240,"card":290,"direction":101,"ingested_from":103},"W7213752705",[280,282,284,286,288],{"name":281,"orcid":9},"Alex S. Ortese",{"name":283,"orcid":9},"Innocent E. Bello",{"name":285,"orcid":9},"I. K. SAMAILA",{"name":287,"orcid":9},"M. ALKALI",{"name":289,"orcid":9},"A. Mahmud",{"tldr":291,"method":292,"finding":293,"direction":101,"opportunity":294},"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":297,"title":298,"url":299,"summary":300,"summary_zh":301,"content":9,"source_name":302,"source_url":299,"published_at":303,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":304,"score_detail":305,"sources":307,"tags":309,"primary_topic":311,"secondary_topics":316,"classification":318,"search_phrases":357,"slug":360,"view_count":151,"doi":361,"paper":362,"created_at":379},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":20,"substance":117,"depth":19,"authority":13,"freshness":151,"relevant":21,"comment":306},"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。",[308],{"name":302,"url":299},[26,27,28,310],"灌溉农业",{"code":144,"slug":312,"name":313,"path":314,"parent_code":315},"irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[317],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":319},{"candidates":320,"agricultural_evidence":45},[321,326,330,334,341,347,353],{"code":144,"score":322,"supported":45,"title":323,"abstract":324,"tags":325},15,[312],[148,312],[310],{"code":32,"score":13,"supported":45,"title":327,"abstract":328,"tags":329},[],[48,28,49],[28],{"code":52,"score":53,"supported":45,"title":331,"abstract":332,"tags":333},[],[26,56],[26],{"code":335,"score":60,"supported":45,"title":336,"abstract":337,"tags":340},"B7",[],[338,339],"温室","greenhouse",[],{"code":342,"score":145,"supported":45,"title":343,"abstract":344,"tags":346},"H4",[],[345],"碳汇",[],{"code":348,"score":145,"supported":45,"title":349,"abstract":350,"tags":352},"H8",[],[351],"conservation agriculture",[],{"code":67,"score":21,"supported":14,"title":354,"abstract":355,"tags":356},[],[],[27],[358,359],"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":361,"openalex_id":363,"authors":364,"venue":302,"cited_by_count":96,"oa_url":373,"card":374,"direction":101,"ingested_from":103},"W7211969418",[365,367,369,371],{"name":366,"orcid":9},"Lucia Moroka",{"name":368,"orcid":9},"Benedict Kayombo",{"name":370,"orcid":9},"Matapa Tapela",{"name":372,"orcid":9},"Thembeka Mpuisang","https:\u002F\u002Fgjeta.com\u002Fsites\u002Fdefault\u002Ffiles\u002Ffulltext_pdf\u002FGJETA-2026-0228.pdf",{"tldr":375,"method":376,"finding":377,"direction":101,"opportunity":378},"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":381,"title":382,"url":383,"summary":384,"summary_zh":385,"content":9,"source_name":386,"source_url":383,"published_at":387,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":388,"score_detail":389,"sources":391,"tags":393,"primary_topic":397,"secondary_topics":398,"classification":400,"search_phrases":429,"slug":432,"view_count":96,"doi":433,"paper":434,"created_at":452},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":17,"substance":117,"depth":322,"authority":13,"freshness":119,"relevant":21,"comment":390},"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。",[392],{"name":386,"url":383},[26,28,394,395,396],"农用地适宜性","土地覆被","孟加拉农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[399],{"code":52,"slug":197,"name":198,"path":199,"parent_code":36},{"status":39,"locked":14,"version":40,"method":41,"evidence":401},{"candidates":402,"agricultural_evidence":45},[403,407,411,418,425],{"code":32,"score":117,"supported":45,"title":404,"abstract":405,"tags":406},[28],[48,28,49],[28],{"code":52,"score":322,"supported":45,"title":408,"abstract":409,"tags":410},[56],[26,56],[26],{"code":412,"score":60,"supported":45,"title":413,"abstract":414,"tags":417},"A1",[],[415,416],"稻米","rice",[],{"code":419,"score":60,"supported":45,"title":420,"abstract":421,"tags":424},"G",[],[422,423],"农村发展","rural development",[],{"code":59,"score":60,"supported":45,"title":426,"abstract":427,"tags":428},[],[63,64],[],[430,431],"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":433,"openalex_id":435,"authors":436,"venue":446,"cited_by_count":96,"oa_url":383,"card":447,"direction":101,"ingested_from":103},"W7222895468",[437,439,441,443],{"name":438,"orcid":9},"Raju Ahmed",{"name":440,"orcid":9},"Shaikh Mehdee Mohammad",{"name":442,"orcid":9},"Ummul Momanin Coalee",{"name":444,"orcid":445},"Khandakar Hasan Mahmud","https:\u002F\u002Forcid.org\u002F0000-0003-1222-0791","The Bangladesh Rural Development Studies",{"tldr":448,"method":449,"finding":450,"direction":101,"opportunity":451},"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":454,"title":455,"url":456,"summary":457,"summary_zh":458,"content":9,"source_name":459,"source_url":456,"published_at":460,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":461,"score_detail":462,"sources":465,"tags":467,"primary_topic":471,"secondary_topics":472,"classification":475,"search_phrases":502,"slug":505,"view_count":96,"doi":506,"paper":507,"created_at":522},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",67,{"impact":17,"substance":18,"depth":463,"authority":246,"freshness":119,"relevant":21,"comment":464},17,"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。",[466],{"name":459,"url":456},[26,468,28,469,470],"水资源管理","地下水潜力","乌干达农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[473,474],{"code":52,"slug":197,"name":198,"path":199,"parent_code":36},{"code":144,"slug":312,"name":313,"path":314,"parent_code":315},{"status":39,"locked":14,"version":40,"method":41,"evidence":476},{"candidates":477,"agricultural_evidence":45},[478,482,486,492,496],{"code":32,"score":117,"supported":45,"title":479,"abstract":480,"tags":481},[28],[48,28,49],[28],{"code":52,"score":322,"supported":45,"title":483,"abstract":484,"tags":485},[56],[26,56],[26],{"code":144,"score":17,"supported":45,"title":487,"abstract":488,"tags":491},[],[489,490],"水资源","water resource",[469,468],{"code":59,"score":60,"supported":45,"title":493,"abstract":494,"tags":495},[],[63,64],[],{"code":497,"score":145,"supported":45,"title":498,"abstract":499,"tags":501},"H7",[],[500],"干旱",[],[503,504],"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":506,"openalex_id":508,"authors":509,"venue":459,"cited_by_count":96,"oa_url":456,"card":517,"direction":101,"ingested_from":103},"W7221339030",[510,513,515],{"name":511,"orcid":512},"Ahmed Abdirizak Dirie","https:\u002F\u002Forcid.org\u002F0009-0002-8109-0724",{"name":514,"orcid":9},"Abdulkadir Ahmed Mohamed",{"name":516,"orcid":9},"Ambiga Kannapiran",{"tldr":518,"method":519,"finding":520,"direction":101,"opportunity":521},"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"]