[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2658":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":23,"tags":25,"view_count":31,"doi":32,"paper":33,"created_at":63},2658,"A remote sensing–based approach to the regionalization of socioeconomic indicators in an agricultural headwater catchment in Northern Benin","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fpiahs-389-45-2026","The agroecosystems of the rural continuum of the Sudano-Sahelian region of the Volta River Basin are undergoing severe degradation, resulting in serious declines in ecosystem service capacities and weakening community livelihoods, as agriculture remains the primary source of income in the region. This degradation is mainly driven by poor management of hydroclimatic risks, non-adapted agricultural practices characterized by intensive use of chemical fertilizers and pesticides, and insufficient consideration of spatial heterogeneity in decision-making processes. The objectives of this study are (i) to identify a Network of 30 m resolution Grid Cells (NGC) representative of the spatial heterogeneity of the studied agroecosystem – the Dassari headwater catchment (550 km 2 ), a tributary of the Volta River in northern Benin – and (ii) to regionalize plot-scale socioeconomic data to support improved decision-making. The NGC was derived by combining iterative principal component analysis (IPCA) with a Conditioned Latin Hypercube Sampling (CLHS) approach using 37 satellite-derived variables (e.g. Normalized Difference Vegetation Index, saturation index, coloration index), resulting in the selection of 150 grid cells. Field and laboratory investigations provided soil properties (e.g. texture, carbon, field capacity, nitrogen content) and socioeconomic data (e.g. harvest quantity, input costs, total production cost, and gross income), which were standardized and analyzed for major crops (millet, sorghum, maize, and cotton). Results show that natural spatial disparities among NGC cells translate into additional labor and input costs that may be unsustainable for farmers. Multiple linear regression models were developed to relate socioeconomic indicators to soil and remote sensing variables for each crop type, and the resulting regional models proved robust, with predicted and observed values closely aligned within the 95 % confidence interval, coefficients of determination exceeding 70 %, and p -values below 0.01.","沃尔特河流域苏丹-萨赫勒地区农村连续体的农业生态系统正在经历严重退化，导致生态系统服务能力严重下降，社区生计日益脆弱，而农业仍是该地区的主要收入来源。这种退化主要由水文气候风险管理不善、以大量使用化肥和农药为特征的非适应性农业实践，以及决策过程中对空间异质性考虑不足所驱动。本研究的目标是：(i) 识别一个30米分辨率网格单元网络（Network of 30 m resolution Grid Cells, NGC），以代表所研究农业生态系统的空间异质性——达萨里源头集水区（550平方公里），位于贝宁北部沃尔特河的一条支流；以及 (ii) 将地块尺度的社会经济数据进行区域化，以支持改进决策。NGC通过将迭代主成分分析（Iterative Principal Component Analysis, IPCA）与条件拉丁超立方采样（Conditioned Latin Hypercube Sampling, CLHS）方法相结合，利用37个卫星衍生变量（如归一化植被指数、饱和度指数、着色指数）得出，最终选取了150个网格单元。实地和实验室调查提供了土壤属性（如质地、碳、田间持水量、氮含量）和社会经济数据（如收获量、投入成本、总生产成本和总收入），这些数据经过标准化处理，并针对主要作物（小米、高粱、玉米和棉花）进行了分析。结果表明，NGC网格单元之间的自然空间差异转化为额外的劳动力和投入成本，对农民而言可能难以承受。研究针对每种作物类型建立了多元线性回归模型，将社会经济指标与土壤和遥感变量相关联，所得区域模型表现稳健，预测值与观测值在95%置信区间内高度吻合，决定系数超过70%，p值低于0.01。",null,"Proceedings of the International Association of Hydrological Sciences","2026-09-16T00:00:00Z","论文",10,false,68,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":13,"relevant":21,"comment":22},8,20,17,13,1,"该研究以30米分辨率遥感变量结合IPCA与CLHS抽样构建代表性网格，将地块尺度社会经济指标区域化，模型R²超70%，方法新颖、数据扎实，对农业信息化与精准决策有参考价值，但研究对象为贝宁流域，国内落地相关性有限，属细分领域学术进展。",[24],{"name":10,"url":6},[26,27,28,29,30],"农业遥感","空间异质性","遥感","西非农业","小农户生计",0,"10.5194\u002Fpiahs-389-45-2026",{"doi":32,"openalex_id":34,"authors":35,"venue":10,"cited_by_count":31,"oa_url":6,"card":56,"direction":60,"ingested_from":62},"W7213239844",[36,38,40,43,46,48,51,53],{"name":37,"orcid":9},"Yaovi Aymar Bossa",{"name":39,"orcid":9},"Adjo Brigitte Bossa",{"name":41,"orcid":42},"Yacouba Yira","https:\u002F\u002Forcid.org\u002F0000-0003-3879-8153",{"name":44,"orcid":45},"Ozias Hounkpatin","https:\u002F\u002Forcid.org\u002F0000-0003-1105-8649",{"name":47,"orcid":9},"Octave Djangni",{"name":49,"orcid":50},"Jean Hounkpè","https:\u002F\u002Forcid.org\u002F0000-0002-5521-9339",{"name":52,"orcid":9},"Hélyette Arielle Odoumbourou",{"name":54,"orcid":55},"Ernest Amoussou","https:\u002F\u002Forcid.org\u002F0000-0002-9402-4446",{"tldr":57,"method":58,"finding":59,"direction":60,"opportunity":61},"结合遥感与采样方法，将地块级社会经济指标区域化到贝宁北部农业流域。","迭代主成分分析与条件拉丁超立方采样，结合37个遥感变量和多元线性回归。","区域模型稳健，决定系数超70%，p值小于0.01，可预测作物社会经济指标。","农业遥感与作物表型","可探索将遥感区域化社会经济指标方法迁移至其他流域，并耦合农户决策行为模型。","openalex","2026-09-16T23:30:28.573293Z"]