[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-1900":3,"related-1900":86},{"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":18,"tags":20,"primary_topic":22,"secondary_topics":28,"classification":29,"search_phrases":65,"slug":66,"view_count":67,"doi":68,"paper":69,"created_at":85},1900,"Spatiotemporal Evolution and Obstacle Factor Analysis of Agricultural Heritage System Resilience: A Case Study of Xinjiang, China","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu18179186","Arid-zone agricultural heritage systems (AHSs) face severe challenges from ecological fragility, water scarcity, and socioeconomic pressures; scientifically understanding their system resilience is a critical prerequisite for achieving sustainable development. This study constructs a three-dimensional resilience evaluation indicator system following the Pressure–State–Response (PSR) framework tailored to arid oasis conditions. Drawing on the entropy weight method, GIS spatial analysis, the ARIMA model, and the obstacle degree model, it adopts statistical and remote sensing data of Xinjiang from 2015 to 2024 to systematically analyze the resilience levels, spatiotemporal evolution characteristics, future development trends, and core obstacle factors of six AHSs. The results reveal that the overall resilience of AHSs in Xinjiang exhibited a fluctuating upward trend over the decade, showing an obvious spatial differentiation pattern of “high in Northern Xinjiang, low in Eastern and Southern Xinjiang.” ARIMA forecasting indicates that resilience will maintain a positive growth trajectory from 2025 to 2028, yet inter-site hierarchical gaps persist. The primary constraints hindering resilience improvement include industrial structure upgrading index, per capita regional GDP, annual NDVI, vegetation coverage, and the number of intangible cultural heritage items, with a clear differentiation between long-term structural bottlenecks and temporary short-term constraints. The study concludes that, although the resilience of AHSs in Xinjiang possesses long-term improvement potential, persistent challenges such as fragile ecological foundations, low-end industrial structures, and insufficient cultural inheritance remain prominent. Targeted differentiated strategies—short-term emergency regulation, medium-term industrial–cultural integration, and long-term adaptive governance—are therefore required to enhance systemic resilience in the future. These findings enrich empirical research on AHS resilience in arid regions and provide case references for the scientific conservation, revitalized utilization, and sustainable development of AHSs in Xinjiang and other global dryland areas.","干旱区农业文化遗产系统（Arid-zone Agricultural Heritage Systems, AHSs）面临生态脆弱性、水资源短缺和社会经济压力的严峻挑战，科学认知其系统恢复力是实现可持续发展的关键前提。本研究遵循压力-状态-响应（Pressure-State-Response, PSR）框架，针对干旱区绿洲条件构建三维恢复力评价指标体系。采用熵权法、GIS空间分析、ARIMA模型及障碍度模型，基于2015—2024年新疆统计与遥感数据，系统分析六个农业文化遗产系统的恢复力水平、时空演变特征、未来发展趋势及核心障碍因子。结果表明：新疆农业文化遗产系统整体恢复力在十年间呈波动上升态势，空间分异格局明显，表现为“北疆高、东疆和南疆低”的特征；ARIMA预测显示，2025—2028年恢复力将保持正向增长趋势，但各遗产点间的层级差距依然存在；制约恢复力提升的首要障碍因子包括产业结构升级指数、人均地区生产总值、年均NDVI、植被覆盖度和非物质文化遗产项目数量，且存在长期结构性瓶颈与短期临时性制约的明显分化。研究认为，尽管新疆农业文化遗产系统恢复力具备长期提升潜力，但生态基础脆弱、产业结构低端化、文化传承不足等持续性挑战依然突出，未来需采取差异化的针对性策略——短期应急调控、中期产业-文化融合、长期适应性治理——以增强系统恢复力。本研究丰富了干旱区农业文化遗产恢复力的实证研究，为新疆及全球其他干旱地区农业文化遗产的科学保护、活化利用与可持续发展提供了案例参考。",null,"Sustainability","2026-09-07T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"主题为农业文化遗产系统韧性评估，不直接涉及三农信息化或智慧农业，相关性不足。",[19],{"name":10,"url":6},[21],"农业文化遗产",{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},"I4","gis","GIS与空间分析","\u002Ftopic\u002Fdigital-agriculture\u002Fgis","I",[],{"status":30,"locked":14,"version":31,"method":32,"evidence":33},"classified","2026-10-22.2","rules",{"candidates":34,"agricultural_evidence":37},[35,44,52,59],{"code":23,"score":36,"supported":37,"title":38,"abstract":39,"tags":43},9,true,[],[40,41,42],"空间分析","GIS","spatial analysis",[],{"code":45,"score":46,"supported":37,"title":47,"abstract":48,"tags":51},"I3",6,[],[49,50],"遥感","remote sensing",[],{"code":53,"score":54,"supported":37,"title":55,"abstract":56,"tags":58},"H3",3,[],[57],"水资源",[],{"code":60,"score":54,"supported":37,"title":61,"abstract":62,"tags":64},"H7",[],[63],"干旱",[],[],"SpatiotemporalEvolutionandObstacleFactor-1900",1,"10.3390\u002Fsu18179186",{"doi":68,"openalex_id":70,"authors":71,"venue":10,"cited_by_count":15,"oa_url":6,"card":77,"direction":83,"ingested_from":84},"W7211870448",[72,74],{"name":73,"orcid":9},"Jinming Sun",{"name":75,"orcid":76},"Xiang Bai","https:\u002F\u002Forcid.org\u002F0000-0003-0214-9880",{"tldr":78,"method":79,"finding":80,"direction":81,"opportunity":82},"构建干旱区农业文化遗产系统韧性评价体系，分析新疆六处遗产的时空演变与障碍因子。","基于PSR框架，结合熵权法、GIS空间分析、ARIMA模型和障碍度模型，利用20","新疆农业文化遗产系统韧性呈波动上升趋势，空间上北疆高、东疆和南疆低，主要障碍为产业结构升级指数等。","农业绿色发展与碳","可延伸研究不同干旱区农业文化遗产系统韧性的对比，或探索韧性提升策略的定量评估与优化路径。","农业遥感与作物表型","openalex","2026-09-08T23:30:18.900882Z",{"total":46,"page":67,"page_size":46,"items":87},[88,162,229,290,346,419],{"id":89,"title":90,"url":91,"summary":92,"summary_zh":93,"content":9,"source_name":94,"source_url":91,"published_at":95,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":96,"score_detail":97,"sources":103,"tags":105,"primary_topic":109,"secondary_topics":110,"classification":111,"search_phrases":143,"slug":146,"view_count":15,"doi":147,"paper":148,"created_at":161},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":98,"substance":99,"depth":100,"authority":101,"freshness":36,"relevant":67,"comment":102},8,18,14,12,"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。",[104],{"name":94,"url":91},[49,106,107,41,108],"土地利用","土壤侵蚀","水土保持",{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},[],{"status":30,"locked":14,"version":31,"method":32,"evidence":112},{"candidates":113,"agricultural_evidence":37},[114,120,125,132,137],{"code":23,"score":13,"supported":37,"title":115,"abstract":116,"tags":119},[],[117,41,118],"地理信息","geographic information",[41],{"code":45,"score":121,"supported":37,"title":122,"abstract":123,"tags":124},7,[],[49,50],[49],{"code":126,"score":46,"supported":37,"title":127,"abstract":128,"tags":131},"H2",[],[129,130],"土壤","soil",[],{"code":53,"score":54,"supported":37,"title":133,"abstract":134,"tags":136},[],[135],"灌溉",[],{"code":138,"score":139,"supported":14,"title":140,"abstract":141,"tags":142},"H6",2,[],[],[106,108],[144,145],"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":147,"openalex_id":149,"authors":150,"venue":94,"cited_by_count":15,"oa_url":9,"card":156,"direction":83,"ingested_from":84},"W7223117733",[151,153],{"name":152,"orcid":9},"MERİÇ KURT",{"name":154,"orcid":155},"Celal ŞENOL","https:\u002F\u002Forcid.org\u002F0000-0003-0857-866X",{"tldr":157,"method":158,"finding":159,"direction":81,"opportunity":160},"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。","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":163,"title":164,"url":165,"summary":166,"summary_zh":167,"content":9,"source_name":168,"source_url":165,"published_at":169,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":170,"sources":172,"tags":174,"primary_topic":178,"secondary_topics":183,"classification":185,"search_phrases":206,"slug":209,"view_count":15,"doi":210,"paper":211,"created_at":228},5485,"Integrating machine learning and geospatial technologies for spatio-temporal analysis of urban expansion and land use transformation in Gambella Town, Ethiopia","https:\u002F\u002Fdoi.org\u002F10.1371\u002Fjournal.pone.0360419","Rapid urbanization and the associated expansion of built-up areas are transforming land resources, ecosystem functions, and the spatial structure of cities. Distinguishing urban growth, urban expansion, and urban sprawl is essential for understanding the processes and patterns of urban transformation and supporting sustainable urban planning. This study integrates machine learning and geospatial technologies to analyze spatio-temporal land use and land cover (LULC) dynamics and urban expansion in Gambella Town, Ethiopia. Multi-temporal Landsat satellite images from 2005, 2015, and 2025 were processed using remote sensing techniques and a supervised machine learning approach based on the Random Forest (RF) classifier. Six major LULC classes were identified: Agricultural Land, Bush with Grass, Built-Up Area, Bare Land, Forest Land, and Water Bodies. The classification achieved overall accuracies of 90%, 90%, and 89% for 2005, 2015, and 2025, respectively. The results revealed substantial land transformation and rapid physical urban expansion, with the built-up area increasing from 93 ha (2.0%) in 2005–1,956 ha (41.3%) in 2025. This expansion was accompanied by major transformations of surrounding land resources, particularly the conversion of Bush with Grass and other open areas to built-up land. Agricultural land increased from 634 ha (13.4%) to 1,750 ha (36.9%), whereas Bush with Grass declined from 3,375 ha (71.1%) to 652 ha (13.7%). Socio-economic information collected from 277 respondents indicated that population growth, rural–urban migration, housing demand, employment opportunities, and infrastructure development were major drivers of urban expansion. The study distinguishes urban expansion, represented by the increase in built-up land, from urban sprawl, which refers to the spatial pattern and form of outward urban development. The integration of Random Forest classification and GIS-based spatial analysis provides valuable evidence of land transformation, vegetation loss, and increasing pressure on urban services, supporting more sustainable urban planning and land management in Gambella Town.","快速城市化及与之相关的建成区扩张正在改变土地资源、生态系统功能和城市空间结构。区分城市增长（urban growth）、城市扩张（urban expansion）和城市蔓延（urban sprawl），对于理解城市转型的过程与格局、支撑可持续城市规划至关重要。本研究融合机器学习与地理空间技术，分析埃塞俄比亚甘贝拉镇（Gambella Town）土地利用与土地覆盖（LULC）的时空动态及城市扩张。采用遥感技术和基于随机森林（RF）分类器的监督机器学习方法，处理了2005年、2015年和2025年的多时相Landsat卫星影像。研究识别出六类主要LULC类型：农业用地、灌草地、建成区、裸地、林地和水体。2005年、2015年和2025年的分类总体精度分别为90%、90%和89%。结果表明，土地发生了显著转变，城市实体空间快速扩张，建成区面积从2005年的93公顷（2.0%）增至2025年的1,956公顷（41.3%）。这一扩张伴随着周边土地资源的重大转变，尤其是灌草地及其他开阔地被转化为建成用地。农业用地从634公顷（13.4%）增至1,750公顷（36.9%），而灌草地则从3,375公顷（71.1%）降至652公顷（13.7%）。从277名受访者收集的社会经济信息表明，人口增长、城乡迁移、住房需求、就业机会和基础设施建设是城市扩张的主要驱动因素。本研究将城市扩张（以建成用地增加为表征）与城市蔓延（指城市向外发展的空间格局与形态）加以区分。随机森林分类与基于GIS的空间分析的融合，为土地转变、植被丧失及城市服务压力加剧提供了有价值的证据，有助于甘贝拉镇实现更可持续的城市规划与土地管理。","PLoS ONE","2026-10-20T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":171},"研究聚焦埃塞俄比亚城市扩张与土地利用变化，属城市地理与遥感应用，与三农、农业信息化主题无直接关联，不建议进入每日精选。",[173],{"name":168,"url":165},[175,176,106,177],"机器学习","遥感监测","城市扩张",{"code":179,"slug":180,"name":181,"path":182,"parent_code":27},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",[184],{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},{"status":30,"locked":14,"version":31,"method":32,"evidence":186},{"candidates":187,"agricultural_evidence":37},[188,194,198,202],{"code":179,"score":189,"supported":37,"title":190,"abstract":192,"tags":193},15,[191],"machine learning",[175,191],[175],{"code":23,"score":36,"supported":37,"title":195,"abstract":196,"tags":197},[],[40,41,42],[],{"code":45,"score":121,"supported":37,"title":199,"abstract":200,"tags":201},[],[49,50],[176],{"code":138,"score":67,"supported":14,"title":203,"abstract":204,"tags":205},[],[],[106],[207,208],"Gambella Town 城市扩张","Random Forest 土地利用分类","GambellaTown城市扩张-5485","10.1371\u002Fjournal.pone.0360419",{"doi":210,"openalex_id":212,"authors":213,"venue":168,"cited_by_count":15,"oa_url":165,"card":223,"direction":83,"ingested_from":84},"W7223022155",[214,217,219,221],{"name":215,"orcid":216},"Kanenus Fufa Dararo","https:\u002F\u002Forcid.org\u002F0009-0007-5747-1558",{"name":218,"orcid":9},"Goanar Jal Dup",{"name":220,"orcid":9},"Weyesa Merga Chemeda",{"name":222,"orcid":9},"Shankar Karuppannan",{"tldr":224,"method":225,"finding":226,"direction":83,"opportunity":227},"用机器学习与遥感分析埃塞俄比亚甘贝拉镇2005-2025年城市扩张与土地利用变化。","Landsat多时相影像、随机森林分类与GIS空间分析，结合277份问卷。","建成区从93公顷增至1956公顷，灌草地大幅转为建成区和农地。","可将随机森林时序分类与驱动力调查结合，扩展到更多非洲小城镇并耦合城市增长模拟。","2026-10-21T23:30:23.271293Z",{"id":230,"title":231,"url":232,"summary":233,"summary_zh":234,"content":9,"source_name":235,"source_url":232,"published_at":236,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":237,"sources":239,"tags":241,"primary_topic":245,"secondary_topics":249,"classification":256,"search_phrases":272,"slug":275,"view_count":15,"doi":276,"paper":277,"created_at":289},5326,"Flood Hazard and Vulnerability Assessment of Chitrakoot District, Uttar Pradesh: An Integrated Geographical, GIS and Remote Sensing Approach","https:\u002F\u002Fdoi.org\u002F10.36948\u002Fijfmr.2026.v08i05.89708","Flood is one of the most important hydro-meteorological hazards affecting human settlements, agriculture, infrastructure and regional economies. Chitrakoot district of Uttar Pradesh presents a distinctive case of hydro-climatic vulnerability because it belongs to the drought-prone Bundelkhand region but simultaneously experiences recurrent riverine and flash-flood conditions during intense monsoon rainfall. The present study assesses the spatial characteristics and determinants of flood hazard and vulnerability in Chitrakoot district using an integrated geographical, GIS and remote sensing approach. The analysis incorporates the Digital Elevation Model (DEM), drainage network, physiography, river proximity, historical flood information, satellite-based flood observations and socio-economic exposure. The district's DEM indicates a marked elevation gradient, approximately from 66 m to 451 m, with relatively higher terrain in the southern part and lower terrain towards the northern Yamuna valley. This topographic configuration facilitates rapid surface runoff from elevated southern terrain towards comparatively low-lying riverine areas. The drainage system is dominated by the Yamuna and Mandakini\u002FPaisuni systems along with Baghain, Gunta, Bardaha and smaller tributaries. The Uttar Pradesh Flood Hazard Atlas identifies 5,114 ha of flood-hazard area in Chitrakoot for 1998–2020, of which 4,129 ha (81%) falls in the very-low hazard category and 985 ha (19%) in the low-hazard category. However, the historical classification does not fully represent the potential consequences of extreme rainfall events. The August 2026 flood provides compelling evidence: the Mandakini at Chitrakoot reached a reported new high flood level of 145.60 m on 29 August 2026, approximately 2.95 m above the previous reported high level, while the water level rose by about 7.5 m within six hours. The study concludes that flood risk in Chitrakoot is spatially concentrated around river corridors, low-elevation areas, floodplains, agricultural land, settlements and tourism infrastructure. A shift from conventional relief-oriented flood management towards integrated floodplain regulation, watershed management, GIS-based risk zonation, real-time monitoring and community-based preparedness is therefore essential.","洪水是影响人类住区、农业、基础设施和区域经济的最重要的水文气象灾害之一。北方邦吉德古德（Chitrakoot）县在水文气候脆弱性方面呈现出独特案例，因为它属于易受干旱影响的本德尔坎德（Bundelkhand）地区，但同时在强季风降雨期间反复遭遇河流洪水和山洪状况。本研究采用地理学、地理信息系统（GIS）和遥感相结合的综合方法，评估吉德古德县洪水灾害与脆弱性的空间特征及其决定因素。分析纳入了数字高程模型（DEM）、河网、地貌、距河流远近、历史洪水信息、基于卫星的洪水观测以及社会经济暴露度。该县的DEM显示出明显的高程梯度，大约从66米到451米，南部地形相对较高，向北部的亚穆纳（Yamuna）河谷地势降低。这种地形格局促使地表径流从较高的南部地形快速流向相对低洼的河流区域。排水系统以亚穆纳河和曼达基尼\u002F派苏尼（Mandakini\u002FPaisuni）水系为主，另有巴盖恩（Baghain）、贡塔（Gunta）、巴尔达哈（Bardaha）及较小支流。北方邦洪水灾害图集确认，1998—2020年吉德古德县洪水灾害面积为5，114公顷，其中4，129公顷（81%）属于极低灾害类别，985公顷（19%）属于低灾害类别。然而，历史分类并不能充分反映极端降雨事件的潜在后果。2026年8月的洪水提供了有力证据：据报道，2026年8月29日吉德古德的曼达基尼河达到145.60米的新高洪水位，比此前报告的高水位高出约2.95米，而水位在六小时内上升了约7.5米。研究得出结论，吉德古德的洪水风险在空间上集中于河流廊道、低海拔地区、洪泛平原、农业用地、住区和旅游基础设施周围。因此，必须从传统的以救济为导向的洪水管理转向洪泛平原综合调控、流域管理、基于GIS的风险区划、实时监测和社区为基础的备灾。","International Journal For Multidisciplinary Research","2026-10-17T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":238},"该研究聚焦印度北方邦的洪水灾害评估，虽涉及GIS与遥感方法，但与三农、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。",[240],{"name":235,"url":232},[242,176,243,244],"防灾减灾","洪水风险评估","GIS应用",{"code":45,"slug":246,"name":247,"path":248,"parent_code":27},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing",[250,251],{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},{"code":60,"slug":252,"name":253,"path":254,"parent_code":255},"climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"status":30,"locked":14,"version":31,"method":32,"evidence":257},{"candidates":258,"agricultural_evidence":37},[259,263,267],{"code":45,"score":189,"supported":37,"title":260,"abstract":261,"tags":262},[50],[49,50],[176],{"code":23,"score":100,"supported":37,"title":264,"abstract":265,"tags":266},[41],[117,41],[],{"code":60,"score":98,"supported":37,"title":268,"abstract":269,"tags":271},[],[63,270],"drought",[243,242],[273,274],"Chitrakoot 洪水风险 GIS","Yamuna 洪水脆弱性 遥感","Chitrakoot洪水风险GIS-5326","10.36948\u002Fijfmr.2026.v08i05.89708",{"doi":276,"openalex_id":278,"authors":279,"venue":235,"cited_by_count":15,"oa_url":283,"card":284,"direction":83,"ingested_from":84},"W7222885988",[280],{"name":281,"orcid":282},"Birendra Yadav","https:\u002F\u002Forcid.org\u002F0009-0007-0864-474X","https:\u002F\u002Fwww.ijfmr.com\u002Fpapers\u002F2026\u002F5\u002F89708.pdf",{"tldr":285,"method":286,"finding":287,"direction":83,"opportunity":288},"用GIS与遥感综合评估Chitrakoot区洪水灾害与脆弱性空间分布。","DEM、河网、历史洪水与卫星观测及社会经济数据叠加分析。","洪水风险集中于河谷低地、农田与居民点，历史分级低估极端降雨风险。","可结合时序遥感与水文模型，构建极端降雨情景下的农田洪涝风险动态制图与预警。","2026-10-19T23:30:24.356743Z",{"id":291,"title":292,"url":293,"summary":294,"summary_zh":295,"content":9,"source_name":296,"source_url":293,"published_at":236,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":297,"score_detail":298,"sources":300,"tags":302,"primary_topic":305,"secondary_topics":306,"classification":307,"search_phrases":322,"slug":325,"view_count":15,"doi":326,"paper":327,"created_at":345},5323,"Impact of Land Use and Land Cover Change on Vegetation Cover Loss in Rwanda: Evidence from Muhoza Sector, Musanze District (2015–2025)","https:\u002F\u002Fdoi.org\u002F10.38124\u002Fijisrt\u002F26oct696","This study analyzed the impact of land use and land cover (LULC) change on vegetation cover loss in Muhoza Sector, Musanze District, Rwanda, between 2015 and 2025. A quantitative geospatial research design was adopted using multi-temporal Landsat and Sentinel-2 satellite imagery, field-based GPS validation, Geographic Information Systems, and Normalized Difference Vegetation Index (NDVI) analysis. Six land-cover classes—forestland, grassland, cropland, urbanized land, wetland, and water bodies—were mapped using supervised classification and post-classification change detection.","本研究分析了2015年至2025年间卢旺达穆桑泽区穆霍扎地区土地利用与土地覆盖（LULC）变化对植被覆盖丧失的影响。研究采用定量地理空间研究设计，运用多时相Landsat和Sentinel-2卫星影像、基于实地GPS验证、地理信息系统以及归一化植被指数（NDVI）分析。通过监督分类和分类后变化检测，对林地、草地、耕地、城市化用地、湿地和水体六类土地覆盖类型进行了制图。","International Journal of Innovative Science and Research Technology (IJISRT)",55,{"impact":98,"substance":99,"depth":100,"authority":46,"freshness":36,"relevant":67,"comment":299},"基于Landsat与Sentinel-2多时相影像的卢旺达局部土地利用变化与植被损失实证研究，方法规范但属区域案例，国际参考价值有限。",[301],{"name":296,"url":293},[176,106,303,304],"植被覆盖","卢旺达农业",{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},[],{"status":30,"locked":14,"version":31,"method":32,"evidence":308},{"candidates":309,"agricultural_evidence":37},[310,314,318],{"code":23,"score":46,"supported":37,"title":311,"abstract":312,"tags":313},[],[117,118],[],{"code":45,"score":139,"supported":14,"title":315,"abstract":316,"tags":317},[],[],[303,176],{"code":138,"score":67,"supported":14,"title":319,"abstract":320,"tags":321},[],[],[106],[323,324],"Muhoza Sector 土地利用","卢旺达 NDVI 植被覆盖","MuhozaSector土地利用-5323","10.38124\u002Fijisrt\u002F26oct696",{"doi":326,"openalex_id":328,"authors":329,"venue":296,"cited_by_count":15,"oa_url":339,"card":340,"direction":83,"ingested_from":84},"W7222817253",[330,332,334,336],{"name":331,"orcid":9},"Vincent Hategekimana",{"name":333,"orcid":9},"Richard Mind J. E.",{"name":335,"orcid":9},"Aboubakar Gasirabo",{"name":337,"orcid":338},"Didier Ntwali","https:\u002F\u002Forcid.org\u002F0000-0002-6914-6652","https:\u002F\u002Fwww.ijisrt.com\u002Fassets\u002Fupload\u002Ffiles\u002FIJISRT26OCT696.pdf",{"tldr":341,"method":342,"finding":343,"direction":83,"opportunity":344},"分析卢旺达Muhoza地区2015–2025年土地利用变化对植被覆盖丧失的影响。","多时相Landsat与Sentinel-2影像、GPS实地验证、GIS与NDVI","六类地物制图揭示建设用地扩张等LULC变化是植被覆盖减少的主要驱动。","可结合高分辨率时序遥感与驱动因子模型，量化小农户尺度城镇化对耕地与植被的胁迫。","2026-10-19T23:30:23.040351Z",{"id":347,"title":348,"url":349,"summary":350,"summary_zh":351,"content":9,"source_name":352,"source_url":349,"published_at":353,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":354,"score_detail":355,"sources":357,"tags":359,"primary_topic":363,"secondary_topics":364,"classification":366,"search_phrases":395,"slug":398,"view_count":15,"doi":399,"paper":400,"created_at":418},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":98,"substance":99,"depth":189,"authority":13,"freshness":36,"relevant":67,"comment":356},"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。",[358],{"name":352,"url":349},[49,41,360,361,362],"农用地适宜性","土地覆被","孟加拉农业",{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},[365],{"code":45,"slug":246,"name":247,"path":248,"parent_code":27},{"status":30,"locked":14,"version":31,"method":32,"evidence":367},{"candidates":368,"agricultural_evidence":37},[369,373,377,384,391],{"code":23,"score":99,"supported":37,"title":370,"abstract":371,"tags":372},[41],[117,41,118],[41],{"code":45,"score":189,"supported":37,"title":374,"abstract":375,"tags":376},[50],[49,50],[49],{"code":378,"score":46,"supported":37,"title":379,"abstract":380,"tags":383},"A1",[],[381,382],"稻米","rice",[],{"code":385,"score":46,"supported":37,"title":386,"abstract":387,"tags":390},"G",[],[388,389],"农村发展","rural development",[],{"code":126,"score":46,"supported":37,"title":392,"abstract":393,"tags":394},[],[129,130],[],[396,397],"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":399,"openalex_id":401,"authors":402,"venue":412,"cited_by_count":15,"oa_url":349,"card":413,"direction":83,"ingested_from":84},"W7222895468",[403,405,407,409],{"name":404,"orcid":9},"Raju Ahmed",{"name":406,"orcid":9},"Shaikh Mehdee Mohammad",{"name":408,"orcid":9},"Ummul Momanin Coalee",{"name":410,"orcid":411},"Khandakar Hasan Mahmud","https:\u002F\u002Forcid.org\u002F0000-0003-1222-0791","The Bangladesh Rural Development Studies",{"tldr":414,"method":415,"finding":416,"direction":83,"opportunity":417},"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":420,"title":421,"url":422,"summary":423,"summary_zh":424,"content":9,"source_name":425,"source_url":422,"published_at":426,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":427,"score_detail":428,"sources":432,"tags":434,"primary_topic":439,"secondary_topics":443,"classification":445,"search_phrases":467,"slug":470,"view_count":15,"doi":471,"paper":472,"created_at":493},5096,"Land Cover Change, Ecosystem Service Implications, and Economy–Land Use Decoupling:","https:\u002F\u002Fdoi.org\u002F10.14246\u002Firspsd.14.4_186","Land cover change plays a critical role in shaping watershed ecological conditions and supporting regional economic activities. This study analyzes land cover dynamics in the Tiworo Watershed, Southeast Sulawesi, Indonesia, for 2014, 2019, and 2024, and examines their relationship with sectoral economic growth. Remote sensing and GIS were used to map and quantify land cover changes, while sectoral Gross Regional Domestic Product (GRDP) data for agriculture, forestry, and fisheries represented economic performance. Economy–land use interactions were assessed using the Tapio decoupling elasticity index. Economy–land use interactions were assessed using the Tapio decoupling elasticity index as a retrospective empirical measure based on observed changes in land cover and sectoral GRDP over the study periods. The results show increasing sectoral GRDP accompanied by relatively limited changes in dominant land cover classes. Absolute decoupling was observed during 2014–2019, relative decoupling during 2019–2024, and overall absolute decoupling for 2014–2024, indicating that economic growth was not proportionally associated with large-scale land conversion. Spatial analysis reveals localized landscape transformations, including mangrove degradation, settlement expansion, and plantation growth, which signal emerging pressures on environmentally sensitive areas. Although ecosystem services are not directly valued, land cover change is interpreted as an indicator of ecological pressure with implications for provisioning ecosystem services. These findings highlight the importance of integrating land-use monitoring and economic indicators to support adaptive watershed management, spatial planning, and sustainable development.","土地覆盖变化在塑造流域生态状况和支撑区域经济活动方面发挥着关键作用。本研究分析了印度尼西亚东南苏拉威西省蒂沃罗流域（Tiworo Watershed）2014年、2019年和2024年的土地覆盖动态，并考察其与部门经济增长的关系。研究采用遥感和地理信息系统（GIS）对土地覆盖变化进行制图和量化，同时以农业、林业和渔业的部门地区生产总值（GRDP）数据表征经济表现。经济与土地利用的相互作用采用Tapio脱钩弹性指数进行评估，该指数作为基于研究期内观测到的土地覆盖变化和部门GRDP变化的回顾性经验测度。结果表明，部门GRDP持续增长，而主导土地覆盖类型的变化相对有限。2014—2019年呈现绝对脱钩，2019—2024年呈现相对脱钩，2014—2024年整体呈现绝对脱钩，表明经济增长与大规模土地转换之间不存在比例关联。空间分析揭示了局部景观转型，包括红树林退化、居民点扩张和种植园增长，这些信号表明环境敏感区域正面临新兴压力。尽管生态系统服务未被直接估值，但土地覆盖变化被解释为生态压力的指标，并对供给型生态系统服务具有潜在影响。这些发现凸显了整合土地利用监测与经济指标的重要性，以支持适应性流域管理、空间规划和可持续发展。","International Review for Spatial Planning and Sustainable Development","2026-10-14T00:00:00Z",63,{"impact":98,"substance":99,"depth":429,"authority":430,"freshness":98,"relevant":67,"comment":431},16,13,"基于遥感与GIS的流域土地利用变化与经济增长脱钩研究，方法规范但属区域案例，对国内三农信息化参考价值有限。",[433],{"name":425,"url":422},[176,435,436,437,438],"土地利用变化","流域管理","生态系统服务","空间规划",{"code":138,"slug":440,"name":441,"path":442,"parent_code":255},"biodiversity","生态保护与生物多样性","\u002Ftopic\u002Fenvironment\u002Fbiodiversity",[444],{"code":23,"slug":24,"name":25,"path":26,"parent_code":27},{"status":30,"locked":14,"version":31,"method":32,"evidence":446},{"candidates":447,"agricultural_evidence":37},[448,453,457,461],{"code":138,"score":430,"supported":37,"title":449,"abstract":451,"tags":452},[450],"ecosystem service",[437],[435,437],{"code":23,"score":13,"supported":37,"title":454,"abstract":455,"tags":456},[],[117,40,41,42],[438],{"code":45,"score":121,"supported":37,"title":458,"abstract":459,"tags":460},[],[49,50],[176],{"code":462,"score":54,"supported":37,"title":463,"abstract":464,"tags":466},"D",[],[465],"渔业",[],[468,469],"Tiworo流域 土地利用 遥感","Tapio脱钩 农业经济 土地覆盖","Tiworo流域土地利用遥感-5096","10.14246\u002Firspsd.14.4_186",{"doi":471,"openalex_id":473,"authors":474,"venue":425,"cited_by_count":15,"oa_url":487,"card":488,"direction":83,"ingested_from":84},"W7221789653",[475,478,481,484],{"name":476,"orcid":477},"Safril Kasim","https:\u002F\u002Forcid.org\u002F0009-0009-4679-4233",{"name":479,"orcid":480},"Hasddin Hasddin","https:\u002F\u002Forcid.org\u002F0000-0002-0114-5274",{"name":482,"orcid":483},"La Fariki","https:\u002F\u002Forcid.org\u002F0009-0003-7870-9028",{"name":485,"orcid":486},"Abhishek Agarwal","https:\u002F\u002Forcid.org\u002F0000-0002-0900-6383","https:\u002F\u002Fwww.jstage.jst.go.jp\u002Farticle\u002Firspsd\u002F14\u002F4\u002F14_9\u002F_pdf",{"tldr":489,"method":490,"finding":491,"direction":83,"opportunity":492},"分析印尼Tiworo流域2014-2024年土地覆盖变化与部门经济增长的脱钩关系。","遥感与GIS制图，结合GRDP数据和Tapio脱钩弹性指数。","经济持续增长但土地覆盖变化有限，整体呈绝对脱钩，局部红树林退化等生态压力显现。","可将脱钩指数与生态系统服务价值核算结合，量化流域生态压力并支撑空间规划。","2026-10-16T23:30:28.687070Z"]