[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2785":3,"related-2785":95},{"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":24,"tags":26,"primary_topic":32,"secondary_topics":38,"classification":39,"search_phrases":64,"slug":67,"view_count":22,"doi":68,"paper":69,"created_at":94},2785,"Remote Sensing-Based Assessment of Interannual Change of the Ecological Sustainability of Agricultural Landscapes in Northern Benin","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu18189542","Assessing ecological sustainability in agricultural landscapes requires approaches that integrate land-cover change, its ecological effects, and their spatial determinants. This study analysed changes between 2023 and 2024 across six agricultural landscapes in northern Benin using the Landscape Ecological Sustainability Index (LESI), calculated for 1 km2 landscape cells from Human Disturbance Coefficients (HDCs) assigned to satellite-derived land-cover classes. Interannual changes were assessed using ΔLESI, the Wilcoxon signed-rank test, Global Moran’s I, and the Local Indicators of Spatial Association (LISA). The contribution of land-cover transitions to HDC change was quantified and a Monte Carlo sensitivity analysis based on classification accuracy was additionally used to assess the robustness of the observed interannual changes to classification uncertainty, and complementary univariate and bivariate regression models examined the relationships between LESI variations and 11 biophysical and geographical variables, including their pairwise interactions. The interannual comparison between 2023 and 2024 showed a decrease in ecological sustainability in four sites, a slight increase in one, and relative stability in another. Significant spatial autocorrelation was detected in all sites (Moran’s I = 0.44–0.65; p \u003C 0.001). Some spatially limited transitions exerted important effects on HDC change. Sensitivity analysis confirmed that the direction of ΔHDC was robust to classification uncertainty in five of the six landscapes. The low explanatory power of the univariate models (R2 ≤ 0.081) indicates that no single variable independently explains the observed changes. The bivariate interaction analyses further showed that some associations were context-dependent, although their explanatory power remained limited, with the best-performing model accounting for only 10.9% of the variation in ΔLESI. This integrated framework provides a reproducible approach for assessing, mapping, and prioritising interannual change of ecological sustainability from remote sensing data to support evidence-based agricultural landscape planning and sustainable land management.","评估农业景观的生态可持续性，需要整合土地覆盖变化、其生态效应及其空间决定因素的方法。本研究利用景观生态可持续性指数（Landscape Ecological Sustainability Index, LESI），分析了贝宁北部六个农业景观在2023年至2024年间的变化。该指数基于分配给卫星衍生土地覆盖类别的人类干扰系数（Human Disturbance Coefficients, HDCs），以1 km²景观单元为尺度进行计算。年际变化通过ΔLESI、Wilcoxon符号秩检验、全局Moran's I和局部空间关联指标（Local Indicators of Spatial Association, LISA）进行评估。研究量化了土地覆盖转变对HDC变化的贡献，并额外采用基于分类精度的蒙特卡洛敏感性分析，以评估观测到的年际变化对分类不确定性的稳健性；同时，通过互补的单变量和双变量回归模型，检验了LESI变化与11个生物物理和地理变量之间的关系，包括其两两交互作用。2023年至2024年的年际比较显示，四个样点的生态可持续性下降，一个样点略有上升，另一个样点则相对稳定。所有样点均检测到显著的空间自相关（Moran's I = 0.44–0.65；p \u003C 0.001）。一些空间范围有限的转变对HDC变化产生了重要影响。敏感性分析证实，在六个景观中的五个，ΔHDC的方向对分类不确定性具有稳健性。单变量模型的解释力较低（R² ≤ 0.081），表明没有单一变量能独立解释观测到的变化。双变量交互分析进一步表明，一些关联具有情境依赖性，尽管其解释力仍然有限，表现最佳的模型仅解释了ΔLESI变异的10.9%。这一整合框架提供了一种可重复的方法，用于从遥感数据评估、制图和优先排序生态可持续性的年际变化，以支持基于证据的农业景观规划和可持续土地管理。",null,"Sustainability","2026-09-17T00:00:00Z","论文",10,false,67,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},8,20,17,13,9,1,"方法体系完整、结论稳健的遥感评估研究，但聚焦西非贝宁地方尺度，对国内三农实践的直接参考价值有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"可持续农业","农业生态","遥感监测","土地利用","贝宁",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},"I3","remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":40,"locked":14,"version":41,"method":42,"evidence":43},"classified","2026-10-22.2","rules",{"candidates":44,"agricultural_evidence":47},[45,53,59],{"code":33,"score":46,"supported":47,"title":48,"abstract":50,"tags":52},15,true,[49],"remote sensing",[51,49],"遥感",[29],{"code":54,"score":55,"supported":14,"title":56,"abstract":57,"tags":58},"H6",2,[],[],[28,30],{"code":60,"score":22,"supported":14,"title":61,"abstract":62,"tags":63},"H8",[],[],[27],[65,66],"可持续农业 农业生态 土地利用 遥感监测","可持续农业 农业生态","可持续农业农业生态土地利用遥感监测-2785","10.3390\u002Fsu18189542",{"doi":68,"openalex_id":70,"authors":71,"venue":10,"cited_by_count":86,"oa_url":6,"card":87,"direction":91,"ingested_from":93},"W7213443483",[72,75,78,80,83],{"name":73,"orcid":74},"Mikhaïl Jean De Dieu Dotou Padonou","https:\u002F\u002Forcid.org\u002F0009-0006-8295-4984",{"name":76,"orcid":77},"Antoine Denis","https:\u002F\u002Forcid.org\u002F0000-0002-3245-7131",{"name":79,"orcid":9},"Yvon-Carmen Hountondji",{"name":81,"orcid":82},"Bernard Tychon","https:\u002F\u002Forcid.org\u002F0000-0002-9367-7306",{"name":84,"orcid":85},"Gérard Nounagnon Gouwakinnou","https:\u002F\u002Forcid.org\u002F0000-0002-3595-9831",0,{"tldr":88,"method":89,"finding":90,"direction":91,"opportunity":92},"基于遥感与景观生态可持续性指数评估贝宁北部农业景观2023-2024年际生态可持续性变化。","用LISI指数、ΔLESI、空间自相关、蒙特卡洛敏感性分析及回归模型分析土地覆盖","四个景观生态可持续性下降，空间自相关显著，但单变量与双变量模型解释力均很低。","农业遥感与作物表型","可引入时序遥感与机器学习，探究多尺度驱动因子交互对农业景观可持续性年际变化的非线性影响。","openalex","2026-09-17T23:30:34.344705Z",{"total":96,"page":22,"page_size":96,"items":97},6,[98,174,244,289,338,407],{"id":99,"title":100,"url":101,"summary":102,"summary_zh":103,"content":9,"source_name":104,"source_url":101,"published_at":105,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":86,"score_detail":106,"sources":108,"tags":110,"primary_topic":113,"secondary_topics":114,"classification":115,"search_phrases":140,"slug":143,"view_count":86,"doi":144,"paper":145,"created_at":173},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":86,"substance":86,"depth":86,"authority":86,"freshness":86,"relevant":86,"comment":107},"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。",[109],{"name":104,"url":101},[29,30,111,112],"土壤侵蚀","乡村人口",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":116},{"candidates":117,"agricultural_evidence":47},[118,123,130,136],{"code":33,"score":119,"supported":47,"title":120,"abstract":121,"tags":122},7,[],[51,49],[29],{"code":124,"score":125,"supported":47,"title":126,"abstract":127,"tags":129},"I4",3,[],[128],"GIS",[],{"code":131,"score":125,"supported":47,"title":132,"abstract":133,"tags":135},"I7",[],[134],"methodological framework",[],{"code":54,"score":22,"supported":14,"title":137,"abstract":138,"tags":139},[],[],[30],[141,142],"Kolubara 河岸侵蚀","Obrenovac 土地利用","Kolubara河岸侵蚀-5390","10.59954\u002Fstnv.797",{"doi":144,"openalex_id":146,"authors":147,"venue":104,"cited_by_count":86,"oa_url":101,"card":167,"direction":91,"ingested_from":93},"W7222945959",[148,151,154,156,159,162,165],{"name":149,"orcid":150},"Slavoljub Dragićević","https:\u002F\u002Forcid.org\u002F0000-0002-1417-5405",{"name":152,"orcid":153},"Marko Langović","https:\u002F\u002Forcid.org\u002F0000-0002-4614-7265",{"name":155,"orcid":9},"Милан Радовић",{"name":157,"orcid":158},"Radislav Tošić","https:\u002F\u002Forcid.org\u002F0000-0002-3994-125X",{"name":160,"orcid":161},"Milica Langović","https:\u002F\u002Forcid.org\u002F0000-0002-6979-377X",{"name":163,"orcid":164},"Novica Lovrić","https:\u002F\u002Forcid.org\u002F0009-0006-0838-4370",{"name":166,"orcid":9},"Manojlović Stefan",{"tldr":168,"method":169,"finding":170,"direction":171,"opportunity":172},"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":175,"title":176,"url":177,"summary":178,"summary_zh":179,"content":9,"source_name":180,"source_url":177,"published_at":181,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":182,"score_detail":183,"sources":187,"tags":189,"primary_topic":192,"secondary_topics":193,"classification":194,"search_phrases":205,"slug":208,"view_count":22,"doi":209,"paper":210,"created_at":243},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":184,"depth":185,"authority":20,"freshness":21,"relevant":22,"comment":186},18,16,"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。",[188],{"name":180,"url":177},[29,30,190,191],"农林复合","阿富汗农业",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":195},{"candidates":196,"agricultural_evidence":47},[197,201],{"code":33,"score":119,"supported":47,"title":198,"abstract":199,"tags":200},[],[51,49],[29],{"code":54,"score":22,"supported":14,"title":202,"abstract":203,"tags":204},[],[],[30],[206,207],"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":209,"openalex_id":211,"authors":212,"venue":180,"cited_by_count":86,"oa_url":237,"card":238,"direction":91,"ingested_from":93},"W7222759855",[213,216,219,222,225,228,231,234],{"name":214,"orcid":215},"Farzaneh Razmju","https:\u002F\u002Forcid.org\u002F0009-0008-2445-7714",{"name":217,"orcid":218},"Baoling Gui","https:\u002F\u002Forcid.org\u002F0009-0004-8167-3860",{"name":220,"orcid":221},"Lydia Sam","https:\u002F\u002Forcid.org\u002F0000-0003-3181-2960",{"name":223,"orcid":224},"Anshuman Bhardwaj","https:\u002F\u002Forcid.org\u002F0000-0002-2502-6384",{"name":226,"orcid":227},"Mohammad Waris Haider","https:\u002F\u002Forcid.org\u002F0000-0002-2871-5740",{"name":229,"orcid":230},"Safiullah Khurram","https:\u002F\u002Forcid.org\u002F0000-0002-3278-3463",{"name":232,"orcid":233},"John W. Groninger","https:\u002F\u002Forcid.org\u002F0000-0001-6705-1978",{"name":235,"orcid":236},"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":239,"method":240,"finding":241,"direction":91,"opportunity":242},"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":245,"title":246,"url":247,"summary":248,"summary_zh":249,"content":9,"source_name":250,"source_url":247,"published_at":251,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":86,"score_detail":252,"sources":254,"tags":256,"primary_topic":258,"secondary_topics":259,"classification":260,"search_phrases":271,"slug":274,"view_count":86,"doi":275,"paper":276,"created_at":288},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":86,"substance":86,"depth":86,"authority":86,"freshness":86,"relevant":86,"comment":253},"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。",[255],{"name":250,"url":247},[29,30,257],"城市扩张",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":261},{"candidates":262,"agricultural_evidence":47},[263,267],{"code":33,"score":119,"supported":47,"title":264,"abstract":265,"tags":266},[],[51,49],[29],{"code":54,"score":22,"supported":14,"title":268,"abstract":269,"tags":270},[],[],[30],[272,273],"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":275,"openalex_id":277,"authors":278,"venue":250,"cited_by_count":86,"oa_url":282,"card":283,"direction":91,"ingested_from":93},"W7221786958",[279],{"name":280,"orcid":281},"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":284,"method":285,"finding":286,"direction":91,"opportunity":287},"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":290,"title":291,"url":292,"summary":293,"summary_zh":294,"content":9,"source_name":295,"source_url":292,"published_at":296,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":86,"score_detail":297,"sources":299,"tags":301,"primary_topic":302,"secondary_topics":303,"classification":304,"search_phrases":320,"slug":323,"view_count":22,"doi":324,"paper":325,"created_at":337},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":86,"substance":86,"depth":86,"authority":86,"freshness":86,"relevant":86,"comment":298},"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。",[300],{"name":295,"url":292},[29,30,257],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":305},{"candidates":306,"agricultural_evidence":47},[307,311,316],{"code":33,"score":119,"supported":47,"title":308,"abstract":309,"tags":310},[],[51,49],[29],{"code":124,"score":96,"supported":47,"title":312,"abstract":313,"tags":315},[],[314,128],"地理信息",[],{"code":54,"score":22,"supported":14,"title":317,"abstract":318,"tags":319},[],[],[30],[321,322],"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":324,"openalex_id":326,"authors":327,"venue":295,"cited_by_count":86,"oa_url":292,"card":332,"direction":91,"ingested_from":93},"W7221355035",[328,330],{"name":329,"orcid":9},"Kambai Ch. Marak",{"name":331,"orcid":9},"Bring Blessing L Ryntathiang",{"tldr":333,"method":334,"finding":335,"direction":91,"opportunity":336},"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":339,"title":340,"url":341,"summary":342,"summary_zh":343,"content":9,"source_name":344,"source_url":341,"published_at":296,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":345,"score_detail":346,"sources":348,"tags":350,"primary_topic":354,"secondary_topics":355,"classification":356,"search_phrases":382,"slug":385,"view_count":22,"doi":386,"paper":387,"created_at":406},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":22,"comment":347},"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。",[349],{"name":344,"url":341},[29,30,351,352,353],"地表温度","植被覆盖","水文响应",{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},[],{"status":40,"locked":14,"version":41,"method":42,"evidence":357},{"candidates":358,"agricultural_evidence":47},[359,364,371,378],{"code":33,"score":360,"supported":47,"title":361,"abstract":362,"tags":363},11,[49],[],[351,352,29],{"code":365,"score":96,"supported":47,"title":366,"abstract":367,"tags":370},"H2",[],[368,369],"土壤","soil",[],{"code":372,"score":96,"supported":47,"title":373,"abstract":374,"tags":377},"H3",[],[375,376],"蒸散发","evapotranspiration",[],{"code":54,"score":22,"supported":14,"title":379,"abstract":380,"tags":381},[],[],[30],[383,384],"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":386,"openalex_id":388,"authors":389,"venue":344,"cited_by_count":86,"oa_url":400,"card":401,"direction":91,"ingested_from":93},"W7221352158",[390,392,394,397],{"name":391,"orcid":9},"Omar Taher Nafe'e",{"name":393,"orcid":9},"Dalia Shaker Mahdi",{"name":395,"orcid":396},"Lubna B. Mahmood","https:\u002F\u002Forcid.org\u002F0009-0000-4428-4891",{"name":398,"orcid":399},"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":402,"method":403,"finding":404,"direction":91,"opportunity":405},"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":408,"title":409,"url":410,"summary":411,"summary_zh":412,"content":9,"source_name":413,"source_url":410,"published_at":414,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":415,"score_detail":416,"sources":420,"tags":422,"primary_topic":426,"secondary_topics":430,"classification":432,"search_phrases":452,"slug":455,"view_count":86,"doi":456,"paper":457,"created_at":492},4366,"Article topic: comprehensive assessment of soil and flora contamination by heavy metals in the zone of influence of the Nikolaevskaya enrichment plant","https:\u002F\u002Fdoi.org\u002F10.51886\u002F1999-740x_2026_3_46","Agricultural lands in East Kazakhstan region cover a significant area, with large portions of pasture and cropland situated in close proximity to operating industrial facilities. Despite this, no comprehensive integrated assessment combining remote sensing, ground-based soil monitoring, and flora survey had previously been conducted for the zone of influence of the Nikolaevskaya enrichment plant. This study aimed to fill that gap by a 40-year land cover analysis (1985-2024) using publicly available satellite data processed in Google Earth Engine with soil sampling and vegetation surveys across 17 sites. Soil analyses revealed not only elevated heavy metal concentrations but also a sharp pH decrease, conditions under which heavy metals become significantly more mobile and available for plant uptake. Technosol formation was observed at multiple sampling points, indicating a permanent transformation of the natural soil profile. The flora survey recorded 72 species from 62 genera, with ruderal and synanthropic species domina-ting disturbed habitats and native species persisting only at control points more distant from the facility. Taken together, these findings point to ongoing ecosystem degradation and raise concrete concerns for the regional food chain given the pastureland and cropland adjacent to the plant.","东哈萨克斯坦地区的农业用地面积广阔，其中大片牧场和农田与正在运营的工业设施相距不远。尽管如此，此前尚未针对尼古拉耶夫斯克选矿厂影响区域开展过将遥感、地面土壤监测与植物区系调查相结合的综合评估。本研究旨在填补这一空白，通过为期40年的土地覆盖分析（1985—2024年），利用Google Earth Engine处理的公开卫星数据，并结合17个样点的土壤采样与植被调查。土壤分析不仅揭示了重金属浓度升高，还发现pH值急剧下降，在这种条件下，重金属的迁移性和植物可利用性显著增强。在多个采样点观察到技术土（Technosol）的形成，表明自然土壤剖面发生了永久性改变。植物区系调查共记录到62属72种植物，其中扰动生境以杂草类和伴人植物物种为主，原生物种仅存于距设施较远的对照点。综合来看，这些发现表明生态系统正在持续退化，并且鉴于该厂邻近牧场和农田，对区域食物链构成了切实的担忧。","Pochvovedenie i agrokhimiya","2026-10-05T00:00:00Z",73,{"impact":417,"substance":418,"depth":184,"authority":20,"freshness":17,"relevant":22,"comment":419},12,22,"结合40年遥感与地面采样的重金属污染综合评估，方法扎实、结论具体，但属区域案例研究，公共影响有限。",[421],{"name":413,"url":410},[423,28,29,424,425],"耕地保护","Google Earth Engine","土壤重金属",{"code":365,"slug":369,"name":427,"path":428,"parent_code":429},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",[431],{"code":33,"slug":34,"name":35,"path":36,"parent_code":37},{"status":40,"locked":14,"version":41,"method":42,"evidence":433},{"candidates":434,"agricultural_evidence":47},[435,439,443,448],{"code":365,"score":46,"supported":47,"title":436,"abstract":437,"tags":438},[369],[368,369],[425],{"code":33,"score":17,"supported":47,"title":440,"abstract":441,"tags":442},[],[51,49],[424,29],{"code":444,"score":22,"supported":14,"title":445,"abstract":446,"tags":447},"H1",[],[],[423],{"code":54,"score":22,"supported":14,"title":449,"abstract":450,"tags":451},[],[],[28],[453,454],"Nikolaevskaya 选矿厂 土壤污染","东哈萨克斯坦 农田 重金属","Nikolaevskaya选矿厂土壤污染-4366","10.51886\u002F1999-740x_2026_3_46",{"doi":456,"openalex_id":458,"authors":459,"venue":413,"cited_by_count":86,"oa_url":485,"card":486,"direction":91,"ingested_from":93},"W7220713350",[460,463,465,468,471,474,477,480,483],{"name":461,"orcid":462},"Yuliya Tugunova","https:\u002F\u002Forcid.org\u002F0009-0006-1037-1480",{"name":464,"orcid":9},"M. Altynbayeva",{"name":466,"orcid":467},"Жанар Абилда","https:\u002F\u002Forcid.org\u002F0000-0001-8505-5243",{"name":469,"orcid":470},"Рахим Канат","https:\u002F\u002Forcid.org\u002F0009-0009-2418-5920",{"name":472,"orcid":473},"Abylay Begaly","https:\u002F\u002Forcid.org\u002F0009-0009-2848-336X",{"name":475,"orcid":476},"D. Kairkhanov","https:\u002F\u002Forcid.org\u002F0009-0006-1017-1980",{"name":478,"orcid":479},"Iskander Isgandarov","https:\u002F\u002Forcid.org\u002F0009-0001-4386-3303",{"name":481,"orcid":482},"ELENA A. ISAKOVA","https:\u002F\u002Forcid.org\u002F0000-0002-9056-6504",{"name":484,"orcid":9},"Kh. Choi","https:\u002F\u002Fjournal.soil.kz\u002Fjour\u002Farticle\u002Fdownload\u002F1135\u002F802",{"tldr":487,"method":488,"finding":489,"direction":490,"opportunity":491},"综合遥感、土壤采样与植被调查，评估哈萨克斯坦一选矿厂影响区40年重金属污染与生态退化。","Google Earth Engine处理1985-2024卫星数据，结合17个","土壤重金属升高且pH骤降，重金属迁移性增强，形成技术土，植被以杂草为主，威胁食物链。","农业绿色发展与碳","可延伸研究重金属活化与pH耦合机制，并构建污染区农田食物链风险预警模型。","2026-10-07T23:30:29.146414Z"]