[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3676":3,"related-3676":106},{"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":77,"slug":80,"view_count":81,"doi":82,"paper":83,"created_at":105},3676,"Assessing Land Use, Land Cover Changes, and Urbanization Impacts on Water Stress in West African Watersheds: A Systematic Methodological Review","https:\u002F\u002Fdoi.org\u002F10.3791\u002F72287","Water stress is one of the major environmental and socio-economic constraints in West Africa, where population growth, agricultural expansion, soil sealing, hydroclimatic variability, and rising pressure on surface water and groundwater rapidly transform watershed functioning. Evaluating the impacts of land use and land cover (LULC) changes and urbanization requires methodological approaches that link the spatial dynamics of landscapes to observed or simulated hydrological responses. This review provides a comparative and critical analysis of the main techniques used in the region: instrumented watersheds and in situ observations, controlled field and laboratory experiments, satellite remote sensing and multi-temporal analysis, groundwater-oriented methods, conceptual, semi-distributed, physically based, and integrated surface-subsurface hydrological modeling, statistical and machine-learning approaches, and hybrid methods coupling land-use and climate scenarios. The search and selection process followed a transparent, PRISMA-based protocol and yielded 51 included records, of which 35 are anchored in West Africa. Hydrological modeling driven by remote sensing dominates the corpus, accounting for 15 of the 35 West African records (43%), particularly with SWAT, ACRU, WaSiM, CEQUEAU, SHETRAN, HydroGeoSphere, and ParFlow-CLM; reported Nash-Sutcliffe efficiency (NSE), Kling-Gupta efficiency (KGE), and coefficient of determination generally range from about 0.6 to 0.9, which is satisfactory to very good against standard evaluation guidelines. Statistical and machine-learning studies account for 8 of 35 records, whereas urban- and groundwater-focused studies remain scarce. Moreover, 8 of 35 records originate from a single research network, so several regional conclusions rest on a narrow and partly non-independent evidence base. In situ networks remain essential for process understanding but are constrained by cost and low density; purely satellite-based approaches suffer from cloud cover and spectral confusion in subhumid zones. The most promising advances lie in multi-source, multi-scale frameworks combining targeted instrumentation, satellite time series, integrated hydrological modeling, territorial scenarios, systematic uncertainty analyses, and co-construction with water-management and planning actors.","水资源压力是西非主要的环境和社会经济制约因素之一。在该地区，人口增长、农业扩张、土壤封闭、水文气候变率以及地表水和地下水压力的不断上升，正迅速改变着流域功能。评估土地利用与土地覆盖（LULC）变化及城市化带来的影响，需要将景观的空间动态与观测或模拟的水文响应相联系的方法学途径。本综述对该地区所采用的主要技术进行了比较性和批判性分析：受控流域与实地观测、受控野外与实验室实验、卫星遥感与多时相分析、面向地下水的方法、概念性、半分布式、基于物理过程及地表-地下耦合的综合水文模型、统计与机器学习方法，以及耦合土地利用与气候情景的混合方法。检索与筛选过程遵循透明、基于PRISMA的协议，最终纳入51篇文献，其中35篇以西非为研究区。由遥感驱动的水文建模在文献主体中占主导地位，在35篇西非文献中占15篇（43%），尤以SWAT、ACRU、WaSiM、CEQUEAU、SHETRAN、HydroGeoSphere和ParFlow-CLM为主；所报告的纳什-萨特克利夫效率（NSE）、克林-古普塔效率（KGE）和决定系数通常约在0.6至0.9之间，对照标准评价指南属于满意至很好水平。统计与机器学习研究在35篇文献中占8篇，而聚焦城市和地下水的研究仍然稀少。此外，35篇文献中有8篇来自同一研究网络，因此若干区域性结论建立在狭窄且部分非独立的证据基础之上。实地观测网络对于过程理解仍然不可或缺，但受成本和低密度制约；纯卫星方法在半湿润区则受云覆盖和光谱混淆的影响。最有前景的进展在于多源、多尺度框架，其结合了针对性观测、卫星时间序列、综合水文建模、区域情景、系统不确定性分析，以及与水资源管理和规划主体的共同构建。",null,"Journal of Visualized Experiments","2026-09-25T00:00:00Z","论文",10,false,66,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":17,"relevant":21,"comment":22},8,20,17,13,1,"系统综述方法学扎实、数据翔实，但聚焦西非流域且与国内农业信息化关联较弱，仅具方法参考价值。",[24],{"name":10,"url":6},[26,27,28,29,30],"机器学习","遥感监测","土地利用","水文模型","西非流域",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":39,"locked":14,"version":40,"method":41,"evidence":42},"classified","2026-10-22.2","rules",{"candidates":43,"agricultural_evidence":46},[44,52,60,67,72],{"code":32,"score":45,"supported":46,"title":47,"abstract":48,"tags":51},7,true,[],[49,50],"遥感","remote sensing",[27],{"code":53,"score":54,"supported":46,"title":55,"abstract":56,"tags":59},"H2",6,[],[57,58],"土壤","soil",[],{"code":61,"score":62,"supported":46,"title":63,"abstract":64,"tags":66},"H3",4,[],[65],"水资源",[29],{"code":68,"score":62,"supported":46,"title":69,"abstract":70,"tags":71},"I2",[],[26],[26],{"code":73,"score":21,"supported":14,"title":74,"abstract":75,"tags":76},"H6",[],[],[28],[78,79],"西非流域 土地利用 水文模型","SWAT 遥感 水资源压力","西非流域土地利用水文模型-3676",3,"10.3791\u002F72287",{"doi":82,"openalex_id":84,"authors":85,"venue":10,"cited_by_count":97,"oa_url":9,"card":98,"direction":102,"ingested_from":104},"W7214394296",[86,88,91,93,95],{"name":87,"orcid":9},"Valère-Carin Jofack Sokeng",{"name":89,"orcid":90},"Nakouana Timité","https:\u002F\u002Forcid.org\u002F0000-0002-3894-1450",{"name":92,"orcid":9},"Toto Marc Zahui",{"name":94,"orcid":9},"Kouamé Koffi Fernand",{"name":96,"orcid":9},"Koné Tiémoman",0,{"tldr":99,"method":100,"finding":101,"direction":102,"opportunity":103},"系统综述西非流域土地利用变化与城市化对水资源压力的评估方法。","PRISMA系统综述，纳入51篇文献，比较遥感、水文模型与机器学习等方法。","遥感驱动水文模型占主导（43%），城市与地下水研究稀缺，证据基础偏窄。","农业遥感与作物表型","可构建多源多尺度框架，融合实地观测、遥感时序与集成水文模型，并开展不确定性分析与利益相关者协同。","openalex","2026-09-28T23:30:31.949583Z",{"total":54,"page":21,"page_size":54,"items":107},[108,182,253,298,347,412],{"id":109,"title":110,"url":111,"summary":112,"summary_zh":113,"content":9,"source_name":114,"source_url":111,"published_at":115,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":97,"score_detail":116,"sources":118,"tags":120,"primary_topic":123,"secondary_topics":124,"classification":125,"search_phrases":148,"slug":151,"view_count":97,"doi":152,"paper":153,"created_at":181},5390,"Land use and socio-economic changes caused by riverbank erosion - case study: Obrenovac municipality, Serbia","https:\u002F\u002Fdoi.org\u002F10.59954\u002Fstnv.797","Lateral bank erosion of meandering rivers represents a significant geomorphological process in the lower part of the Kolubara River Basin in Serbia. This process directly impacts land-use and agricultural productivity and lead to broader environmental, socioeconomic, and demographic changes. Historically, the Kolubara riverbanks have been intensively used for agriculture. Today, lateral channel migration and riverbank erosion, driven by the interaction between natural process and human activities, directly threaten traditionally active land plots along the river. This study investigates the long-term dynamics of riverbank erosion along the four active meanders of the Kolubara River in Obrenovac Municipality over a 97-year period (1930–2026). Main tasks include quantification of lateral channel migration and land loss rates, analysis of land-use changes within the endangered plots, and an investigation of socioeconomic consequences and demographic dynamics in affected settlements. The methodological framework integrates cadastral maps analysis, remote sensing techniques (UAVs), and GIS software, with analysis of demographic and land-use data. The results indicate that maximum lateral channel migration reached 259.3 m during the observed period, while the total land loss amounted to 17.6 ha, consisting mostly of arable land. This reduction has directly affected the local agricultural sector, resulting in an estimated land loss value of approximately 24,122 USD. Demographic analysis reveals population decline exceeding 40% in the analysed settlements (Draževac, Konatice and Poljane) between 1961 and 2022, from over 90% of the economically active population in 1961 to less than 2% in 2022. Ultimately, by highlighting the socioeconomic impacts of riverbank erosion such as irreversible agricultural land loss and rural livelihood disruption, these findings offer valuable insights for spatial planning and sustainable land management.","蜿蜒河流的侧向河岸侵蚀是塞尔维亚科卢巴拉河（Kolubara River）流域下游一个重要的地貌过程。该过程直接影响土地利用和农业生产力，并引发更广泛的环境、社会经济和人口变化。历史上，科卢巴拉河岸曾被密集用于农业生产。如今，在自然过程与人类活动相互作用驱动下的侧向河道迁移和河岸侵蚀，直接威胁着沿河传统上活跃的地块。本研究考察了奥布雷诺瓦茨市（Obrenovac Municipality）科卢巴拉河四个活跃曲流段在97年期间（1930—2026年）河岸侵蚀的长期动态。主要任务包括：量化侧向河道迁移和土地流失速率，分析受威胁地块内的土地利用变化，以及调查受影响居民点的社会经济后果和人口动态。方法框架整合了地籍图分析、遥感技术（无人机，UAVs）和GIS软件，并结合人口与土地利用数据分析。结果表明，在观测期内侧向河道迁移最大距离达259.3 m，土地流失总量为17.6 ha，其中大部分为耕地。这一减少直接影响了当地农业部门，估计土地流失价值约为24,122美元。人口分析显示，1961年至2022年间，所分析居民点（Draževac、Konatice和Poljane）的人口下降幅度超过40%，经济活动人口比例从1961年的超过90%降至2022年的不足2%。最终，通过突出河岸侵蚀的社会经济影响，如不可逆的农业土地流失和农村生计破坏，这些发现为空间规划和可持续土地管理提供了有价值的见解。","Stanovnistvo","2026-10-19T00:00:00Z",{"impact":97,"substance":97,"depth":97,"authority":97,"freshness":97,"relevant":97,"comment":117},"塞尔维亚河岸侵蚀案例研究，属地理与土地利用领域，与三农及农业信息化主题关联弱，不建议进入每日精选。",[119],{"name":114,"url":111},[27,28,121,122],"土壤侵蚀","乡村人口",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":126},{"candidates":127,"agricultural_evidence":46},[128,132,138,144],{"code":32,"score":45,"supported":46,"title":129,"abstract":130,"tags":131},[],[49,50],[27],{"code":133,"score":81,"supported":46,"title":134,"abstract":135,"tags":137},"I4",[],[136],"GIS",[],{"code":139,"score":81,"supported":46,"title":140,"abstract":141,"tags":143},"I7",[],[142],"methodological framework",[],{"code":73,"score":21,"supported":14,"title":145,"abstract":146,"tags":147},[],[],[28],[149,150],"Kolubara 河岸侵蚀","Obrenovac 土地利用","Kolubara河岸侵蚀-5390","10.59954\u002Fstnv.797",{"doi":152,"openalex_id":154,"authors":155,"venue":114,"cited_by_count":97,"oa_url":111,"card":175,"direction":102,"ingested_from":104},"W7222945959",[156,159,162,164,167,170,173],{"name":157,"orcid":158},"Slavoljub Dragićević","https:\u002F\u002Forcid.org\u002F0000-0002-1417-5405",{"name":160,"orcid":161},"Marko Langović","https:\u002F\u002Forcid.org\u002F0000-0002-4614-7265",{"name":163,"orcid":9},"Милан Радовић",{"name":165,"orcid":166},"Radislav Tošić","https:\u002F\u002Forcid.org\u002F0000-0002-3994-125X",{"name":168,"orcid":169},"Milica Langović","https:\u002F\u002Forcid.org\u002F0000-0002-6979-377X",{"name":171,"orcid":172},"Novica Lovrić","https:\u002F\u002Forcid.org\u002F0009-0006-0838-4370",{"name":174,"orcid":9},"Manojlović Stefan",{"tldr":176,"method":177,"finding":178,"direction":179,"opportunity":180},"研究塞尔维亚Kolubara河岸侵蚀97年间的河道迁移、耕地损失及社会经济影响。","结合地籍图、UAV遥感、GIS与人口土地利用数据分析四条曲流。","最大侧向迁移259.3米，损失17.6公顷耕地约2.4万美元，村落人口降超40%。","其他","可将河岸侵蚀遥感监测与农户生计、土地价值评估耦合，构建侵蚀风险预警与补偿决策模型。","2026-10-20T23:30:18.982943Z",{"id":183,"title":184,"url":185,"summary":186,"summary_zh":187,"content":9,"source_name":188,"source_url":185,"published_at":189,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":190,"score_detail":191,"sources":196,"tags":198,"primary_topic":201,"secondary_topics":202,"classification":203,"search_phrases":214,"slug":217,"view_count":21,"doi":218,"paper":219,"created_at":252},5170,"Tree cover increases on agricultural land amid continued landscape-level deforestation: a case study from eastern Afghanistan","https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10661-026-16018-1","Understanding changes in tree cover within agricultural landscapes is critical for assessing the resilience of rural communities and consequent land use dynamics in conflict-affected regions. This study examines spatiotemporal land use and tree cover changes across four districts of Nangarhar Province in eastern Afghanistan using high-resolution (3 m\u002Fpixel) satellite imagery. The temporal window examined for this study (2016-2024) spans a period of significant geopolitical upheaval in Afghanistan, including the collapse of the republican government in 2021 and the resulting shift in political power and governance dynamics. An object-based image analysis framework combined with a support vector machine classifier was applied to map five land use classes within settlement areas: tree cover, cropland, water, built-up areas, and barren land. Classification accuracy was assessed using stratified random sampling and Cohen's kappa coefficient, with all maps achieving κ values above 0.80. Post-classification change detection and transition matrices were used to quantify class-to-class conversions in hectares, while Sankey diagrams were employed to visualise the magnitude and direction of land use transitions. The results reveal varying patterns of tree cover change across the study districts, with evidence of both tree cover gains linked to expansion of agroforestry and on-farm tree retention, and losses driven by agricultural expansion and development. These changes may influence local livelihoods, as trees on farms provide important resources such as fruit, fuelwood, and shade. The findings demonstrate the effectiveness of integrating high-resolution remote sensing, object-based classification, and Sankey-based visualisation for analysing complex land use dynamics.","理解冲突影响地区农业景观中树木覆盖的变化，对于评估农村社区的韧性及由此产生的土地利用动态至关重要。本研究利用高分辨率（3米\u002F像素）卫星影像，考察了阿富汗东部楠格哈尔省四个县的时空土地利用与树木覆盖变化。研究的时间窗口（2016—2024年）跨越了阿富汗地缘政治剧烈动荡的时期，包括2021年共和政府的崩溃以及随之而来的政治权力与治理格局的转变。研究采用基于对象的影像分析框架结合支持向量机分类器，对定居点区域内的五类土地利用类型进行制图：树木覆盖、耕地、水体、建成区和裸地。分类精度通过分层随机抽样和Cohen's kappa系数进行评估，所有制图结果的κ值均高于0.80。研究采用分类后变化检测和转移矩阵量化各地类之间的转换面积（以公顷计），并运用桑基图（Sankey diagram）可视化土地利用转移的幅度与方向。结果表明，各研究县的树木覆盖变化呈现不同模式，既有与农林业扩张和农田树木保留相关的树木覆盖增加，也有由农业扩张和开发驱动的树木覆盖减少。这些变化可能影响当地生计，因为农田中的树木提供水果、薪材和遮荫等重要资源。研究结果证明了整合高分辨率遥感、基于对象的分类和桑基图可视化方法在分析复杂土地利用动态方面的有效性。","Environmental Monitoring and Assessment","2026-10-16T00:00:00Z",64,{"impact":17,"substance":192,"depth":193,"authority":20,"freshness":194,"relevant":21,"comment":195},18,16,9,"基于3米高分辨率遥感与面向对象分类的阿富汗东部案例研究，方法扎实、数据新颖，但属区域案例，公共影响有限，适合作为方法参考而非每日精选头条。",[197],{"name":188,"url":185},[27,28,199,200],"农林复合","阿富汗农业",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":204},{"candidates":205,"agricultural_evidence":46},[206,210],{"code":32,"score":45,"supported":46,"title":207,"abstract":208,"tags":209},[],[49,50],[27],{"code":73,"score":21,"supported":14,"title":211,"abstract":212,"tags":213},[],[],[28],[215,216],"楠格哈尔省 遥感 树冠覆盖","阿富汗 农林复合 土地利用","楠格哈尔省遥感树冠覆盖-5170","10.1007\u002Fs10661-026-16018-1",{"doi":218,"openalex_id":220,"authors":221,"venue":188,"cited_by_count":97,"oa_url":246,"card":247,"direction":102,"ingested_from":104},"W7222759855",[222,225,228,231,234,237,240,243],{"name":223,"orcid":224},"Farzaneh Razmju","https:\u002F\u002Forcid.org\u002F0009-0008-2445-7714",{"name":226,"orcid":227},"Baoling Gui","https:\u002F\u002Forcid.org\u002F0009-0004-8167-3860",{"name":229,"orcid":230},"Lydia Sam","https:\u002F\u002Forcid.org\u002F0000-0003-3181-2960",{"name":232,"orcid":233},"Anshuman Bhardwaj","https:\u002F\u002Forcid.org\u002F0000-0002-2502-6384",{"name":235,"orcid":236},"Mohammad Waris Haider","https:\u002F\u002Forcid.org\u002F0000-0002-2871-5740",{"name":238,"orcid":239},"Safiullah Khurram","https:\u002F\u002Forcid.org\u002F0000-0002-3278-3463",{"name":241,"orcid":242},"John W. Groninger","https:\u002F\u002Forcid.org\u002F0000-0001-6705-1978",{"name":244,"orcid":245},"David F. R. P. Burslem","https:\u002F\u002Forcid.org\u002F0000-0001-6033-0990","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1007\u002Fs10661-026-16018-1.pdf",{"tldr":248,"method":249,"finding":250,"direction":102,"opportunity":251},"用3米遥感影像分析阿富汗东部四区2016-2024年农地树木覆盖与土地利用变化。","3米高分辨率影像、面向对象分类+SVM、变化检测与桑基图。","农地树木覆盖有增有减，农林复合扩张带来增益，农业扩张与开发导致损失。","冲突地区农地树木覆盖动态与生计韧性关系尚缺长时序、多区域对比研究。","2026-10-17T23:30:28.623928Z",{"id":254,"title":255,"url":256,"summary":257,"summary_zh":258,"content":9,"source_name":259,"source_url":256,"published_at":260,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":97,"score_detail":261,"sources":263,"tags":265,"primary_topic":267,"secondary_topics":268,"classification":269,"search_phrases":280,"slug":283,"view_count":97,"doi":284,"paper":285,"created_at":297},5094,"An Investigation of Built-up Area Expansion in the Syrian Coastal Mountain Environment","https:\u002F\u002Fdoi.org\u002F10.14246\u002Firspsd.14.4_109","As built-up expansion in the Syrian coastal mountainous areas intensifies, its environmental impacts are becoming increasingly severe. Existing research, however, offers limited quantitative evidence to elucidate the dynamics of this phenomenon. This study addresses this gap by employing mixed-method techniques at the district level of Safita. Landsat satellite imagery, remote sensing, and ArcGIS software were used to classify and analyze geospatial data from 2010 to 2020. Statistical methodologies were then applied to investigate spatio-temporal built-up growth, identify the drivers of expansion, and evaluate resultant spatial patterns. The analysis reveals accelerated built-up expansion, with the most dramatic growth occurring in southern peripheral zones, recording increases of 150-169%. The study identifies a persistent trend of low-density, dispersed sprawl following a non-linear trajectory, evidenced by Shannon's entropy increasing steadily to 0.89 by 2020. Analysis of Urban Expansion Rate and Intensity indices shows a distinct shift from moderate, semi-efficient growth (2010–2015) to rapid and extensive sprawl (2015–2020). Furthermore, the Built-up Expansion Index demonstrates an evolution from initial economically driven leapfrog expansion through conflict-induced infilling consolidation to a final hybrid pattern combining edge-expansion and ribbon development. Kernel Density Estimation reveals a fundamental spatial transformation from semi-concentrated hotspots to widespread medium-density sprawl, strongly constrained by physical factors. Specifically, 93% of built-up areas concentrated on gentle slopes (0-15%), and 68% were located within 200 meters of road networks. These findings underscore the urgent need for planning decision-makers to implement strict regulatory measures that curb built-up sprawl, protect agricultural lands and natural resources, and guide growth through updated master plans to achieve sustainable development.","随着叙利亚沿海山区建成区扩张不断加剧，其环境影响日益严重。然而，现有研究在阐明这一现象的动态方面提供的定量证据有限。本研究通过在萨菲塔区级层面采用混合方法技术来填补这一空白。利用Landsat卫星影像、遥感技术和ArcGIS软件对2010年至2020年的地理空间数据进行分类和分析。随后应用统计方法研究建成区的时空增长，识别扩张的驱动因素，并评估由此产生的空间格局。分析揭示了建成区扩张的加速，最显著的增长发生在南部边缘地带，增幅达150%至169%。研究识别出低密度、分散式蔓延的持续趋势，呈非线性轨迹，香农熵（Shannon's entropy）到2020年稳步上升至0.89即为明证。城市扩张速率和强度指数的分析显示，从2010至2015年的温和、半高效增长明显转向2015至2020年的快速、广泛蔓延。此外，建成区扩张指数（Built-up Expansion Index）表明，扩张从最初经济驱动的跳跃式扩展，经过冲突引发的填充式整合，演变为边缘扩展与带状发展相结合的最终混合模式。核密度估计（Kernel Density Estimation）揭示了从半集中热点向广泛中密度蔓延的根本性空间转变，且受自然因素的强烈制约。具体而言，93%的建成区集中在缓坡（0-15%）上，68%位于道路网络200米范围内。这些发现凸显了规划决策者迫切需要实施严格的监管措施，以遏制建成区蔓延，保护农田和自然资源，并通过更新总体规划引导增长，以实现可持续发展。","International Review for Spatial Planning and Sustainable Development","2026-10-14T00:00:00Z",{"impact":97,"substance":97,"depth":97,"authority":97,"freshness":97,"relevant":97,"comment":262},"研究叙利亚沿海山区建成区扩张，属城市规划与环境领域，与三农、农业信息化、数字乡村无关。",[264],{"name":259,"url":256},[27,28,266],"城市扩张",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":270},{"candidates":271,"agricultural_evidence":46},[272,276],{"code":32,"score":45,"supported":46,"title":273,"abstract":274,"tags":275},[],[49,50],[27],{"code":73,"score":21,"supported":14,"title":277,"abstract":278,"tags":279},[],[],[28],[281,282],"叙利亚沿海山区 建成区扩张","Safita 遥感 土地利用","叙利亚沿海山区建成区扩张-5094","10.14246\u002Firspsd.14.4_109",{"doi":284,"openalex_id":286,"authors":287,"venue":259,"cited_by_count":97,"oa_url":291,"card":292,"direction":102,"ingested_from":104},"W7221786958",[288],{"name":289,"orcid":290},"Tarek Rahmoun","https:\u002F\u002Forcid.org\u002F0000-0001-5112-2487","https:\u002F\u002Fwww.jstage.jst.go.jp\u002Farticle\u002Firspsd\u002F14\u002F4\u002F14_6\u002F_pdf",{"tldr":293,"method":294,"finding":295,"direction":102,"opportunity":296},"研究叙利亚沿海山区萨菲塔地区2010-2020年建设用地扩张动态、驱动因素与空间格局。","Landsat影像、遥感与ArcGIS分类，结合统计方法分析时空扩张。","建设用地加速低密度蔓延，93%集中于缓坡、68%靠近道路，熵值升至0.89。","可结合遥感与机器学习，量化山区建设用地扩张对农地流失和生态的长期影响。","2026-10-16T23:30:28.556800Z",{"id":299,"title":300,"url":301,"summary":302,"summary_zh":303,"content":9,"source_name":304,"source_url":301,"published_at":305,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":97,"score_detail":306,"sources":308,"tags":310,"primary_topic":311,"secondary_topics":312,"classification":313,"search_phrases":329,"slug":332,"view_count":21,"doi":333,"paper":334,"created_at":346},4679,"Spatio-temporal variation of urban sprawl in Tura town using the Shannon entropy model","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23277607","Abstract Urbanization is driving substantial transformation of cities worldwide, with unmanaged expansion often resulting in urban sprawl and the loss of agricultural land, forests, and environmentally sensitive areas. Tura Town, headquarters of West Garo Hills District, has experienced steady urban growth over the past two decades, yet few studies have examined its expansion pattern. This study aims to analyse the spatio-temporal variation and assessing the degree and directional patterns of urban sprawl from 2006 to 2026 using Remote Sensing, GIS, and Shannon's Entropy Index. Landsat imagery was classified into LULC categories, with accuracy validated through a confusion matrix, achieving satisfactory results (77–81%). Built-up area increased from 10 km² to 17 km²—a 70% rise, with faster growth occurring during 2006–2016 (40%) than 2016–2026 (21.4%). Shannon's Entropy Index revealed the compactness or dispersal of growth, while buffer and directional analyses identified expansion patterns. The findings offer valuable insights for sustainable urban planning and land-use management in Tura Town. Keyword: Urban sprawl, Urbanization, Land use\u002Fland cover (LULC), Remote Sensing, GIS, Shannon's Entropy Index, Built-up area, Tura Town, Spatio-temporal analysis, Sustainable urban planning","摘要 城市化正推动全球城市发生深刻转型，而无序扩张往往导致城市蔓延以及农田、森林和环境敏感区域的丧失。作为西加罗丘陵县首府的图拉镇，过去二十年经历了稳定的城市增长，但对其扩张模式的研究却很少。本研究旨在利用遥感、地理信息系统和香农熵指数，分析2006年至2026年城市蔓延的时空变化，并评估其程度与方向性模式。研究将Landsat影像分类为土地利用\u002F土地覆盖（LULC）类别，并通过混淆矩阵验证精度，取得了令人满意的结果（77%–81%）。建成区面积从10平方公里增至17平方公里，增长了70%，其中2006—2016年（40%）的增长快于2016—2026年（21.4%）。香农熵指数揭示了增长的紧凑或分散特征，而缓冲区和方向性分析则识别了扩张模式。研究结果为图拉镇的可持续城市规划和土地利用管理提供了有价值的见解。关键词：城市蔓延，城市化，土地利用\u002F土地覆盖（LULC），遥感，地理信息系统，香农熵指数，建成区，图拉镇，时空分析，可持续城市规划","Zenodo (CERN European Organization for Nuclear Research)","2026-10-10T00:00:00Z",{"impact":97,"substance":97,"depth":97,"authority":97,"freshness":97,"relevant":97,"comment":307},"该论文研究印度图拉镇城市扩张的遥感与熵模型分析，属城市地理与土地利用范畴，与三农、农业信息化、智慧农业无直接关联，不建议进入每日精选。",[309],{"name":304,"url":301},[27,28,266],{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":314},{"candidates":315,"agricultural_evidence":46},[316,320,325],{"code":32,"score":45,"supported":46,"title":317,"abstract":318,"tags":319},[],[49,50],[27],{"code":133,"score":54,"supported":46,"title":321,"abstract":322,"tags":324},[],[323,136],"地理信息",[],{"code":73,"score":21,"supported":14,"title":326,"abstract":327,"tags":328},[],[],[28],[330,331],"土地利用 城市扩张 遥感监测","土地利用 城市扩张","土地利用城市扩张遥感监测-4679","10.5281\u002Fzenodo.23277607",{"doi":333,"openalex_id":335,"authors":336,"venue":304,"cited_by_count":97,"oa_url":301,"card":341,"direction":102,"ingested_from":104},"W7221355035",[337,339],{"name":338,"orcid":9},"Kambai Ch. Marak",{"name":340,"orcid":9},"Bring Blessing L Ryntathiang",{"tldr":342,"method":343,"finding":344,"direction":102,"opportunity":345},"用遥感、GIS和香农熵分析印度图拉镇2006-2026年城市蔓延的时空变化。","Landsat影像分类LULC，混淆矩阵验证精度77-81%，结合香农熵、缓冲与","建成区从10增至17平方公里（增70%），2006-2016年增长快于2016-2026年，熵值揭示","可结合耕地流失与农业用地破碎化，评估城市蔓延对农业生态系统的长期影响。","2026-10-11T23:30:30.230545Z",{"id":348,"title":349,"url":350,"summary":351,"summary_zh":352,"content":9,"source_name":353,"source_url":350,"published_at":305,"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":365,"search_phrases":387,"slug":390,"view_count":21,"doi":391,"paper":392,"created_at":411},4678,"Remote Sensing-based Integration of Land Use\u002FLand Cover, Vegetation Cover, and Land Surface Temperature with Hydrological Implications in Tikrit City, Iraq","https:\u002F\u002Fdoi.org\u002F10.14445\u002F23488352\u002Fijce-v13i9p115","This study examines the integrated relationship among Land Use\u002FLand Cover (LULC), Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST), with hydrological implications, in Tikrit City, Iraq, using Landsat data acquired in 2017 and 2025. LULC, NDVI, and LST layers were prepared using the same spatial boundary, and 4124 paired sample points were extracted from identical locations to support temporal and statistical comparison. The LULC results showed a clear reduction in Soil from 70.52% in 2017 to 49.88% in 2025, whereas Vegetation increased from 25.49% to 44.12%. Built Area also increased from 3.08% to 4.90%, indicating moderate urban expansion. The dominant land-cover transition was from Soil to Vegetation, covering 66,014.66 ha. Mean NDVI increased significantly from 0.061 to 0.075, while mean LST remained statistically stable, changing only from 41.992°C to 42.031°C. However, non-parametric tests indicated that the spatial distribution of LST changed significantly. The NDVI–LST relationship was positive in both years, with Pearson correlation increasing from 0.670 in 2017 to 0.709 in 2025. Regression analysis showed that NDVI explained 44.9% and 50.2% of LST variation in 2017 and 2025, respectively. Class-based analysis indicated that the dominant heat-contributing class shifted from Soil in 2017 to Built Area in 2025. These findings show that surface thermal behavior in Tikrit City cannot be explained by vegetation cover alone, but depends on land-cover composition, mixed pixels, agricultural activity, soil exposure, surface moisture, and seasonal conditions. From a hydrological perspective, the reduction of exposed soil, expansion of vegetation, and growth of built-up areas have implications for infiltration opportunity, runoff potential, evapotranspiration tendency, and surface moisture retention.","本研究利用2017年和2025年获取的Landsat数据，考察了伊拉克提克里特市土地利用\u002F土地覆盖（LULC）、归一化植被指数（NDVI）和地表温度（LST）之间的综合关系及其水文意义。LULC、NDVI和LST图层采用相同的空间边界制备，并从相同位置提取了4124对样本点，以支持时间与统计比较。LULC结果显示，土壤占比从2017年的70.52%明显下降至2025年的49.88%，而植被占比从25.49%上升至44.12%。建成区面积也从3.08%增至4.90%，表明存在中等程度的城市扩张。主导性土地覆盖转变为由土壤转为植被，覆盖面积达66,014.66公顷。平均NDVI从0.061显著增至0.075，而平均LST在统计上保持稳定，仅从41.992°C变为42.031°C。然而，非参数检验表明LST的空间分布发生了显著变化。NDVI与LST的关系在两年中均为正相关，Pearson相关系数从2017年的0.670增至2025年的0.709。回归分析表明，NDVI在2017年和2025年分别解释了LST变异的44.9%和50.2%。基于类别的分析表明，主要的热贡献类别从2017年的土壤转变为2025年的建成区。这些发现表明，提克里特市的地表热行为不能仅由植被覆盖来解释，而是取决于土地覆盖组成、混合像元、农业活动、土壤裸露、地表湿度和季节条件。从水文角度看，裸露土壤减少、植被扩张和建成区增长对下渗机会、径流潜力、蒸散发趋势和地表水分保持具有影响。","International Journal of Civil Engineering",68,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":13,"relevant":21,"comment":356},"基于Landsat双期影像量化伊拉克提克里特市土地利用、植被与地表温度耦合关系及其水文效应，数据扎实、结论明确，对农业遥感与土地变化研究有参考价值，但地域性强、国内关联度有限。",[358],{"name":353,"url":350},[27,28,360,361,362],"地表温度","植被覆盖","水文响应",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[],{"status":39,"locked":14,"version":40,"method":41,"evidence":366},{"candidates":367,"agricultural_evidence":46},[368,373,377,383],{"code":32,"score":369,"supported":46,"title":370,"abstract":371,"tags":372},11,[50],[],[360,361,27],{"code":53,"score":54,"supported":46,"title":374,"abstract":375,"tags":376},[],[57,58],[],{"code":61,"score":54,"supported":46,"title":378,"abstract":379,"tags":382},[],[380,381],"蒸散发","evapotranspiration",[],{"code":73,"score":21,"supported":14,"title":384,"abstract":385,"tags":386},[],[],[28],[388,389],"Landsat 土地利用 植被覆盖 地表温度","土地利用 地表温度 植被覆盖 水文响应","Landsat土地利用植被覆盖地表温度-4678","10.14445\u002F23488352\u002Fijce-v13i9p115",{"doi":391,"openalex_id":393,"authors":394,"venue":353,"cited_by_count":97,"oa_url":405,"card":406,"direction":102,"ingested_from":104},"W7221352158",[395,397,399,402],{"name":396,"orcid":9},"Omar Taher Nafe'e",{"name":398,"orcid":9},"Dalia Shaker Mahdi",{"name":400,"orcid":401},"Lubna B. Mahmood","https:\u002F\u002Forcid.org\u002F0009-0000-4428-4891",{"name":403,"orcid":404},"Asmaa Abdul Jabbar Jamel","https:\u002F\u002Forcid.org\u002F0000-0001-7602-3426","https:\u002F\u002Fwww.internationaljournalssrg.org\u002F..\u002FIJCE\u002F2026\u002FVolume13-Issue9\u002FIJCE-V13I9P115.pdf",{"tldr":407,"method":408,"finding":409,"direction":102,"opportunity":410},"基于Landsat 2017与2025年数据，分析伊拉克提克里特市LULC、NDVI与LST的耦合关","Landsat影像、4124个配对样点、NDVI与LST反演、相关与回归分析。","植被增加、裸土减少，LST均值稳定但空间分布显著变化，NDVI-LST正相关增强，主导热贡献由裸土转","可结合土壤湿度与蒸散数据，探究NDVI-LST正相关机制及混合像元对城市农业水文过程的影响。","2026-10-11T23:30:30.165387Z",{"id":413,"title":414,"url":415,"summary":416,"summary_zh":417,"content":9,"source_name":418,"source_url":415,"published_at":419,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":420,"score_detail":421,"sources":426,"tags":428,"primary_topic":432,"secondary_topics":433,"classification":444,"search_phrases":492,"slug":495,"view_count":496,"doi":497,"paper":498,"created_at":517},4575,"A review of remote sensing for agricultural drought: technologies, indices, modelling advances and future prospects","https:\u002F\u002Fdoi.org\u002F10.1080\u002F15481603.2026.2738981","Agricultural drought is a complex hazard that jeopardises food security and progress toward the Sustainable Development Goals. We systematically reviewed peer-reviewed English-language literature published between 2015 and 2025, focusing on Remote Sensing (RS)-driven agricultural drought monitoring and prediction. Eligible studies were identified from the Web of Science and Scopus databases (last searched in August 2025); review articles, duplicates, and irrelevant studies were excluded, resulting in 181 articles. This review critically examined the evolution of sensors, drought indices, modelling approaches, and emerging technologies used to assess agricultural drought across diverse agro-ecological regions. Specifically, we (1) systematically evaluated the use of optical, thermal, and microwave RS platforms, along with satellite-based, model-based, and reanalysis products for agricultural drought monitoring; (2) reviewed widely used RS-based drought indices, including single indices grouped into nine categories, as well as composite indices; (3) reviewed software or programming languages applied; (4) assessed the progression of modelling approaches from traditional statistical and time-series methods to machine learning (ML) and deep learning (DL) frameworks; and (5) examined validation strategies applied to agricultural drought assessment. The analysis reveals a growing research interest in this topic, with a strong geographic concentration in Asia, particularly China. Optical and thermal platforms (e.g. MODIS and Landsat) dominate the literature (~54%) due to their accessibility, followed by satellite-derived precipitation products (17%), while microwave soil-moisture missions remain underutilized (~7%). Regarding RS-based indices, most studies employed more than one index: 44% analysed multiple individual indices, 51% used composite indices (either alone or in combination with individual indices), and only 5% relied on a single index. Vegetation indices, such as NDVI, remain workhorses; however, their sensitivity to soil background effects and canopy saturation has driven increased adoption of thermal composites (e.g. VHI), as well as adaptive weighting schemes and principal component analysis-based approaches. Moreover, computational tools used in drought research can be broadly grouped into geospatial and RS platforms for large-scale data processing and analysis (e.g. QGIS, GEE), and general-purpose programming languages (e.g. R, Python) for model development and advanced analytics. Regarding the methodology, statistical and time-series approaches account for 64% of the reviewed studies, followed by ML models (20%) and DL methods (15%), while explainable artificial intelligence (XAI) remains nascent. Techniques, such as random forests, support vector machines, and CNN and LSTM architectures, generally outperform traditional models but require large training datasets and raise concerns related to interpretability and ethics. In terms of validation, hydro-climatic indices such as SPI and SPEI are most commonly used (32%), followed by crop yield and yield anomaly data (19%). This review further identifies key research gaps across sensors, indices, and modelling approaches and proposes a roadmap for developing equitable, interpretable, and resilient agricultural drought monitoring systems. Emerging opportunities include context-aware and interpretable AI, multi-sensor and multi-scale data fusion across optical, thermal, and microwave domains, integration of physiologically meaningful indicators such as sun-induced chlorophyll fluorescence (SIF), robust uncertainty quantification, and the development of hybrid and physics-informed modelling frameworks.","农业干旱是一种复杂的灾害，威胁粮食安全和可持续发展目标的实现。我们系统综述了2015年至2025年间发表的同行评议英文文献，聚焦于遥感（RS）驱动的农业干旱监测与预测。符合条件的研究通过Web of Science和Scopus数据库检索确定（最后检索时间为2025年8月）；综述文章、重复文献及不相关研究被排除，最终纳入181篇文献。本综述批判性地审视了用于评估不同农业生态区农业干旱的传感器、干旱指数、建模方法及新兴技术的演变。具体而言，我们（1）系统评估了光学、热红外和微波遥感平台，以及基于卫星、基于模型和再分析产品在农业干旱监测中的应用；（2）综述了广泛使用的基于遥感的干旱指数，包括归为九类的单一指数以及复合指数；（3）综述了所应用的软件或编程语言；（4）评估了建模方法从传统统计和时间序列方法向机器学习（ML）和深度学习（DL）框架的演进；（5）考察了应用于农业干旱评估的验证策略。分析显示，该主题的研究兴趣日益增长，地理上高度集中于亚洲，尤其是中国。光学和热红外平台（如MODIS和Landsat）因其可获取性在文献中占主导地位（约54%），其次是卫星降水产品（17%），而微波土壤水分任务仍未得到充分利用（约7%）。在基于遥感的指数方面，大多数研究采用了不止一种指数：44%分析了多个单一指数，51%使用了复合指数（单独使用或与单一指数结合使用），仅5%依赖单一指数。植被指数（如NDVI）仍是主力工具；然而，其对土壤背景效应和冠层饱和的敏感性推动了热红外复合指数（如VHI）以及自适应权重方案和基于主成分分析的方法得到更多采用。此外，干旱研究中使用的计算工具可大致分为用于大规模数据处理和分析的地理空间与遥感平台（如QGIS、GEE），以及用于模型开发的通用编程语言（如R、Python）。","GIScience & Remote Sensing","2026-10-08T00:00:00Z",81,{"impact":192,"substance":422,"depth":423,"authority":424,"freshness":17,"relevant":21,"comment":425},22,19,14,"系统综述181篇文献，梳理遥感干旱监测的传感器、指数与建模进展，方法学价值高，但属学术综述，产业落地影响有限。",[427],{"name":418,"url":415},[429,430,26,27,431],"智慧农业","粮食安全","农业干旱",{"code":32,"slug":33,"name":34,"path":35,"parent_code":36},[434,440],{"code":435,"slug":436,"name":437,"path":438,"parent_code":439},"H7","climate","气候适应与防灾减灾","\u002Ftopic\u002Fenvironment\u002Fclimate","H",{"code":68,"slug":441,"name":442,"path":443,"parent_code":36},"agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai",{"status":39,"locked":14,"version":40,"method":41,"evidence":445},{"candidates":446,"agricultural_evidence":46},[447,452,458,466,472,476,482,487],{"code":32,"score":448,"supported":46,"title":449,"abstract":450,"tags":451},15,[50],[49,50],[27],{"code":435,"score":424,"supported":46,"title":453,"abstract":455,"tags":457},[454],"drought",[456,454],"干旱",[],{"code":68,"score":13,"supported":46,"title":459,"abstract":460,"tags":465},[],[461,26,462,463,464],"深度学习","machine learning","deep learning","artificial intelligence",[26],{"code":467,"score":45,"supported":46,"title":468,"abstract":469,"tags":471},"A8",[],[430,470],"food security",[430],{"code":53,"score":54,"supported":46,"title":473,"abstract":474,"tags":475},[],[57,58],[],{"code":477,"score":81,"supported":46,"title":478,"abstract":479,"tags":481},"D",[],[480],"水产",[],{"code":73,"score":81,"supported":46,"title":483,"abstract":484,"tags":486},[],[485],"农业生态",[],{"code":488,"score":21,"supported":14,"title":489,"abstract":490,"tags":491},"I1",[],[],[429],[493,494],"遥感 农业干旱 监测","GIScience Remote Sensing 干旱指数","遥感农业干旱监测-4575",2,"10.1080\u002F15481603.2026.2738981",{"doi":497,"openalex_id":499,"authors":500,"venue":418,"cited_by_count":97,"oa_url":510,"card":511,"direction":516,"ingested_from":104},"W7221081979",[501,504,507],{"name":502,"orcid":503},"Fatemeh Saba","https:\u002F\u002Forcid.org\u002F0000-0001-6171-155X",{"name":505,"orcid":506},"Nima Ahmadian","https:\u002F\u002Forcid.org\u002F0000-0003-3676-1840",{"name":508,"orcid":509},"Olena Dubovyk","https:\u002F\u002Forcid.org\u002F0000-0002-7338-3167","https:\u002F\u002Fwww.tandfonline.com\u002Fdoi\u002Fpdf\u002F10.1080\u002F15481603.2026.2738981?needAccess=true",{"tldr":512,"method":513,"finding":514,"direction":102,"opportunity":515},"系统综述2015-2025年遥感农业干旱监测与预测的传感器、指数、建模及验证进展。","基于Web of Science与Scopus的181篇文献系统综述，涵盖光学\u002F","光学热红外平台占主导，微波土壤水分利用不足；复合指数与机器学习建模成为趋势。","微波土壤水分数据融合与深度学习干旱预测模型在数据稀缺区验证是潜在研究空白。","智慧农业 \u002F 农业物联网","2026-10-10T23:30:14.933078Z"]