[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2785":3},{"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,"view_count":32,"doi":33,"paper":34,"created_at":58},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",0,"10.3390\u002Fsu18189542",{"doi":33,"openalex_id":35,"authors":36,"venue":10,"cited_by_count":32,"oa_url":6,"card":51,"direction":55,"ingested_from":57},"W7213443483",[37,40,43,45,48],{"name":38,"orcid":39},"Mikhaïl Jean De Dieu Dotou Padonou","https:\u002F\u002Forcid.org\u002F0009-0006-8295-4984",{"name":41,"orcid":42},"Antoine Denis","https:\u002F\u002Forcid.org\u002F0000-0002-3245-7131",{"name":44,"orcid":9},"Yvon-Carmen Hountondji",{"name":46,"orcid":47},"Bernard Tychon","https:\u002F\u002Forcid.org\u002F0000-0002-9367-7306",{"name":49,"orcid":50},"Gérard Nounagnon Gouwakinnou","https:\u002F\u002Forcid.org\u002F0000-0002-3595-9831",{"tldr":52,"method":53,"finding":54,"direction":55,"opportunity":56},"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"]