[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3166":3,"related-3166":67},{"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,"search_phrases":32,"slug":35,"view_count":36,"doi":37,"paper":38,"created_at":66},3166,"Case Studies of Environmental Monitoring Based on the Integrated Use of Bioindicators and Remote Sensing","https:\u002F\u002Fdoi.org\u002F10.3390\u002Frs18183227","This narrative review examines how plant bioindication can be integrated with remote sensing to support the preliminary screening of soil contamination, framed as an environmental situational awareness problem addressed through multi-scale imagery and field validation. Seven case studies—illegal waste deposits, pipeline leaks, landfill impacts, industrial areas, agrochemical drift, oil-spills in coastal wetlands, and acid mine drainage—were selected based on joint documentation of a contamination source or exposure condition, a measurable plant response, and a remotely detected signal related to vegetation stress. This synthesis clarifies how vegetation response can serve as a proxy for large-scale contamination screening. A common contamination–vegetation–remote sensing logic emerges across the cases examined, linking contamination drivers and exposure pathways to canopy responses detectable as spectral, thermal, spatial, or temporal anomalies. Recurring spatial patterns of vegetation anomalies are identified as first-order interpretive cues rather than diagnostic signatures. Vegetation stress responses lack spectral specificity, making spectral equifinality the primary operational challenge for vegetation-based biomonitoring. Future workflows should integrate spectral, spatial, temporal, multi-sensor, and ancillary data validated against ground-truth. Future research should expand the evidence base through formal literature searches, multi-site validation, standardized protocols, and infrastructures integrating plant phenotyping and remote sensing to support quantitatively validated screening approaches.","本叙述性综述探讨了如何将植物生物指示与遥感相结合，以支持土壤污染的初步筛查，并将其构建为一个通过多尺度影像和实地验证来解决的环境态势感知问题。基于对污染源或暴露条件的联合记录、可测量的植物响应以及与植被胁迫相关的遥感信号，选取了七个案例研究——非法废物堆放、管道泄漏、垃圾填埋场影响、工业区、农用化学品飘移、沿海湿地溢油和酸性矿山排水。本综述阐明了植被响应如何能够作为大规模污染筛查的替代指标。在所考察的案例中，浮现出一种共同的污染—植被—遥感逻辑，将污染驱动因素和暴露途径与可被检测为光谱、热、空间或时间异常的冠层响应联系起来。植被异常的重复性空间格局被识别为一级解释线索，而非诊断性特征。植被胁迫响应缺乏光谱特异性，使得光谱等终性成为基于植被的生物监测面临的首要操作挑战。未来的工作流程应整合光谱、空间、时间、多传感器和辅助数据，并以地面真值进行验证。未来研究应通过正式文献检索、多站点验证、标准化协议以及整合植物表型分析与遥感的基础设施来扩展证据基础，以支持经过定量验证的筛查方法。",null,"Remote Sensing","2026-09-19T00:00:00Z","论文",10,false,77,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},16,21,18,14,8,1,"综述性论文，系统梳理植被生物指示与遥感融合筛查土壤污染的七个案例，方法学与结论对农业环境遥感监测有参考价值，但非全国性政策或突破性成果。",[25],{"name":10,"url":6},[27,28,29,30,31],"农业遥感","遥感","环境监测","植被监测","土壤污染",[33,34],"植被生物指示 遥感 土壤污染","Remote Sensing 植被胁迫 遥感监测","植被生物指示遥感土壤污染-3166",0,"10.3390\u002Frs18183227",{"doi":37,"openalex_id":39,"authors":40,"venue":10,"cited_by_count":36,"oa_url":6,"card":59,"direction":63,"ingested_from":65},"W7213930509",[41,44,47,50,53,56],{"name":42,"orcid":43},"Marco De Mizio","https:\u002F\u002Forcid.org\u002F0009-0009-6556-2606",{"name":45,"orcid":46},"Donato Amitrano","https:\u002F\u002Forcid.org\u002F0000-0002-2355-4503",{"name":48,"orcid":49},"Massimiliano Gargiulo","https:\u002F\u002Forcid.org\u002F0000-0002-6783-366X",{"name":51,"orcid":52},"Sara Parrilli","https:\u002F\u002Forcid.org\u002F0000-0002-7225-1269",{"name":54,"orcid":55},"Claudia Savarese","https:\u002F\u002Forcid.org\u002F0000-0003-0161-2407",{"name":57,"orcid":58},"Massimiliano Lega","https:\u002F\u002Forcid.org\u002F0000-0002-4842-6049",{"tldr":60,"method":61,"finding":62,"direction":63,"opportunity":64},"综述植物生物指示与遥感结合用于土壤污染初步筛查的七个案例，提出污染-植被-遥感逻辑。","叙事性综述，选取七类污染案例，整合多尺度影像与地面验证。","植被胁迫光谱缺乏特异性，光谱等终性是植被生物监测的主要操作挑战。","农业遥感与作物表型","可构建标准化植物表型-遥感集成平台，开展多站点验证以量化污染筛查。","openalex","2026-09-22T23:30:20.917796Z",{"total":68,"page":22,"page_size":68,"items":69},6,[70,113,155,226,275,308],{"id":71,"title":72,"url":73,"summary":74,"summary_zh":75,"content":9,"source_name":76,"source_url":73,"published_at":77,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":78,"score_detail":79,"sources":84,"tags":86,"search_phrases":90,"slug":93,"view_count":36,"doi":94,"paper":95,"created_at":112},3191,"Spatial prediction of soil organic carbon stocks in Sudanese clay soils using regression kriging","https:\u002F\u002Fdoi.org\u002F10.3389\u002Fsjss.2026.16733","Soil organic carbon (SOC) stocks are a critical component of terrestrial carbon pools, influencing soil quality, agricultural productivity, and climate change mitigation. This study aimed to map and improve spatial estimation of SOC stocks in Sudan’s Blue Nile clay soils using regression kriging (RK). The model integrated 554 spatially unique soil profiles with nine environmental covariates: precipitation, temperature, relative humidity, normalized difference vegetation index (NDVI), land use\u002Fcover, bare soil index (BSI), digital elevation model (DEM), LS-factor, and aspect. Spectral indices were derived from Landsat 9 imagery (April 2024), while climate and terrain data were obtained from CHIRPS\u002FWorldClim and SRTM (30 m). RK performance was robust, with spatial cross-validation R 2 = 0.72, RMSE = 8.4 Mg C ha −1 (29% of mean observed stock), and mean bias = −0.8 Mg C ha −1 . Predicted SOC stocks (0–30 cm) ranged from 12.4 to 51.2 Mg C ha −1 (mean 28.6 Mg C ha −1 ). NDVI, clay content, and topographic wetness index were the most influential predictors. Agricultural lands exhibited the highest stocks (51.2 Mg C ha −1 ), while bare lands had the lowest (14.2 Mg C ha −1 ). This study (1) applies spatially explicit validation for SOC mapping in Sudan’s Blue Nile region, (2) harmonizes legacy and contemporary soil data using equivalent soil mass correction, and (3) provides high-resolution SOC maps for climate-resilient agricultural planning. Findings support soil carbon management and climate mitigation in semi-arid regions.","土壤有机碳（SOC）储量是陆地碳库的重要组成部分，影响土壤质量、农业生产力及气候变化减缓。本研究旨在利用回归克里金（RK）方法对苏丹青尼罗河黏土区SOC储量进行制图并改进其空间估算。该模型整合了554个空间独立土壤剖面与9个环境协变量：降水、温度、相对湿度、归一化植被指数（NDVI）、土地利用\u002F覆盖、裸土指数（BSI）、数字高程模型（DEM）、LS因子和坡向。光谱指数源自Landsat 9影像（2024年4月），气候与地形数据分别来自CHIRPS\u002FWorldClim和SRTM（30 m）。RK表现稳健，空间交叉验证R²=0.72，RMSE=8.4 Mg C ha⁻¹（为实测储量均值的29%），平均偏差=−0.8 Mg C ha⁻¹。预测SOC储量（0–30 cm）范围为12.4–51.2 Mg C ha⁻¹（均值28.6 Mg C ha⁻¹）。NDVI、黏粒含量和地形湿度指数是最具影响力的预测因子。农地储量最高（51.2 Mg C ha⁻¹），裸地最低（14.2 Mg C ha⁻¹）。本研究（1）对苏丹青尼罗河地区SOC制图采用空间显式验证，（2）利用等效土壤质量校正协调历史与当代土壤数据，（3）为气候韧性农业规划提供高分辨率SOC图。研究结果支持半干旱地区的土壤碳管理与气候减缓。","Spanish Journal of Soil Science","2026-09-22T00:00:00Z",68,{"impact":21,"substance":18,"depth":80,"authority":81,"freshness":82,"relevant":22,"comment":83},17,13,9,"基于554个土壤剖面与多源遥感协变量的回归克里金制图研究，方法规范、验证充分，对半干旱区土壤碳管理与气候适应型农业规划有参考价值，但属区域性学术成果，公共影响有限。",[85],{"name":76,"url":73},[27,87,28,88,89],"气候变化","土壤碳汇","数字土壤制图",[91,92],"苏丹青尼罗河 土壤有机碳 回归克里金","Landsat 9 土壤有机碳 空间预测","苏丹青尼罗河土壤有机碳回归克里金-3191","10.3389\u002Fsjss.2026.16733",{"doi":94,"openalex_id":96,"authors":97,"venue":76,"cited_by_count":36,"oa_url":73,"card":106,"direction":111,"ingested_from":65},"W7213971196",[98,100,102,104],{"name":99,"orcid":9},"Faroug A.H. Jadalla",{"name":101,"orcid":9},"Kolapo O. Oluwasemire",{"name":103,"orcid":9},"Abd Elmagid A. Elmobarak",{"name":105,"orcid":9},"Mohammed A. M. Mohammed Zein",{"tldr":107,"method":108,"finding":109,"direction":63,"opportunity":110},"用回归克里金结合多源环境协变量预测苏丹青尼罗河粘土区土壤有机碳储量。","554个土壤剖面与9个环境协变量，Landsat 9、CHIRPS\u002FWorldC","模型R²=0.72，NDVI、粘土含量和地形湿度指数影响最大，农地碳储量最高。","可引入时序遥感与机器学习提升半干旱区SOC动态预测，并耦合农业管理措施评估固碳潜力。","数字乡村与农业信息化","2026-09-22T23:30:31.028178Z",{"id":114,"title":115,"url":116,"summary":117,"summary_zh":118,"content":9,"source_name":119,"source_url":116,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":120,"score_detail":121,"sources":125,"tags":127,"search_phrases":131,"slug":134,"view_count":36,"doi":135,"paper":136,"created_at":154},3060,"Geospatial Intelligence for Peri-Urban Land-Use Conflicts: Evaluating Agricultural Suitability against Rapid Urbanisation using the Analytical Hierarchy Process and Cloud Computing","https:\u002F\u002Fdoi.org\u002F10.59543\u002F6mpcwr41","This paper presents a geospatial multi-criteria evaluation of agricultural potential in the suburban region of Bapatla using eight physical and land-use characteristics: elevation, slope, road accessibility, proximity to water bodies, Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), Land Use\u002FLand Cover (LULC), and soil texture, processed using Google Earth Engine. The Analytic Hierarchy Process (AHP) was used to determine the relative weights of each criterion. NDVI received the highest weight (26.33%), followed by LST, slope, and proximity to water bodies (14.96% each), while elevation received the lowest weight (4.6%) due to the region's flat terrain. Weighted overlay analysis classified the 142.25 km² study area into Suitable (108.90 km²; 76.55%), Not Suitable (32.60 km²; 22.92%), and Highly Suitable (0.75 km²; 0.53%) categories. Suitable areas are mainly distributed across the southern and peripheral agricultural zones, whereas unsuitable areas are concentrated within Bapatla Urban and its surroundings. The limited extent of highly suitable land highlights the scarcity of optimal agricultural sites. The results reveal land-use conflicts driven primarily by urbanisation rather than environmental constraints. The AHP-weighted suitability map provides an evidence-based tool for agricultural land conservation, water-resource management, and sustainable urban expansion.","本文基于八项自然与土地利用特征，对巴帕特拉（Bapatla）郊区农业潜力进行了地理空间多准则评价，这些特征包括：海拔、坡度、道路可达性、距水体远近、地表温度（LST）、归一化植被指数（NDVI）、土地利用\u002F土地覆盖（LULC）以及土壤质地，并利用Google Earth Engine进行处理。采用层次分析法（AHP）确定各准则的相对权重。NDVI权重最高（26.33%），其次为LST、坡度和距水体远近（均为14.96%），而海拔因该地区地形平坦权重最低（4.6%）。加权叠加分析将142.25 km²的研究区划分为适宜（108.90 km²；76.55%）、不适宜（32.60 km²；22.92%）和高适宜（0.75 km²；0.53%）三类。适宜区主要分布于南部及外围农业区，而不适宜区集中于巴帕特拉城区及其周边。高适宜土地面积有限，凸显了优质农业用地的稀缺性。结果表明，土地利用冲突主要由城市化驱动，而非环境限制。基于AHP的适宜性地图为农业用地保护、水资源管理和可持续城市扩张提供了循证工具。","Journal of Urban Intelligence and Smart Systems",70,{"impact":122,"substance":123,"depth":80,"authority":81,"freshness":21,"relevant":22,"comment":124},12,20,"该论文利用遥感与AHP方法评估城郊农业用地冲突，方法新颖、数据详实，对农业土地保护有参考价值，但属细分领域研究，影响范围有限。",[126],{"name":119,"url":116},[128,27,129,28,130],"智慧农业","农业信息化","土地利用",[132,133],"Bapatla 农业用地 城市化","Google Earth Engine 农业适宜性","Bapatla农业用地城市化-3060","10.59543\u002F6mpcwr41",{"doi":135,"openalex_id":137,"authors":138,"venue":119,"cited_by_count":36,"oa_url":147,"card":148,"direction":153,"ingested_from":65},"W7213644047",[139,141,143,145],{"name":140,"orcid":9},"Sreerama Naik Naik S R",{"name":142,"orcid":9},"T K Prasad",{"name":144,"orcid":9},"Feba Jose Jasmine",{"name":146,"orcid":9},"Jayapal G","https:\u002F\u002Fjuiss.org\u002Findex.php\u002Fjuiss\u002Farticle\u002Fdownload\u002F366\u002F231",{"tldr":149,"method":150,"finding":151,"direction":63,"opportunity":152},"用AHP与云平台评估印度Bapatla城郊农业适宜性，揭示城市化引发的土地利用冲突。","Google Earth Engine处理8个因子，AHP加权叠加分析142.2","76.55%区域适宜农业，但高度适宜仅0.53%，冲突主因是城市化而非环境限制。","可引入时序遥感与动态城市扩张模拟，构建城郊农业保护与城市增长协同优化模型。","智慧农业 \u002F 农业物联网","2026-09-21T23:30:09.448414Z",{"id":156,"title":157,"url":158,"summary":159,"summary_zh":160,"content":9,"source_name":161,"source_url":158,"published_at":162,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":163,"score_detail":164,"sources":168,"tags":170,"search_phrases":175,"slug":178,"view_count":36,"doi":179,"paper":180,"created_at":225},2797,"Generation of representative datasets of future Copernicus Sentinel Expansion Mission Data (hyperspectral, thermal and L-band) as basis for innovative agricultural products","https:\u002F\u002Fdoi.org\u002F10.62880\u002Frars26005","The Copernicus Sentinel Expansion Missions will provide new and unique remote sensing data. To enable rapid use of real data as soon as it becomes available, it is essential to generate comparable synthetic data in advance. This study proposes a novel data set for three of the upcoming sensors. CHIME hyperspectral data are generated by inverting multispectral reflectance data from Sentinel-2 time series by radiative transfer modelling to retrieve land surface parameters and subsequently forward-simulating bottom-of-atmosphere reflectance using expected CHIME sensor characteristics. Future LSTM land surface temperature data are derived from Sentinel-3 and Sentinel-2 data using the Sen-ET workflow with spatial data mining sharpening. L-band backscatter and coherence data for ROSE-L are simulated using SAOCOM-1 data, which are transformed to match the expected spatial and radiometric characteristics. The novel data set is available for three areas of interest (AOIs) defined by Sentinel-2 tiles located in Germany, Belgium, and Estonia. A validation of simulated CHIME data using existing comparable sensor data from EnMAP showed a high spectral correlation with an average RMSE of 6.154 [%] and a correlation of 0.924 for the German AOI in 2024. This publicly available, unique and well validated dataset already enables the preparation and development of future products and services across a wide range of application areas based on data from the Sentinel Expansion Mission. Due to the high data availability resulting from extensive two-year time series, as well as the various AOIs, future products can already be tested for their temporal and spatial transferability.","哥白尼哨兵扩展任务将提供新的独特遥感数据。为了在真实数据可用时尽快加以利用，必须提前生成可比的合成数据。本研究为其中三个即将发射的传感器提出了一个新的数据集。CHIME高光谱数据通过辐射传输建模对来自Sentinel-2时间序列的多光谱反射率数据进行反演，以获取地表参数，随后利用预期的CHIME传感器特征正向模拟大气底层反射率来生成。未来的LSTM地表温度数据利用Sen-ET工作流结合空间数据挖掘锐化方法，从Sentinel-3和Sentinel-2数据中导出。ROSE-L的L波段后向散射和相干性数据使用SAOCOM-1数据进行模拟，并将其转换为符合预期空间和辐射特征的形式。该新数据集可用于三个感兴趣区域（AOIs），分别位于德国、比利时和爱沙尼亚的Sentinel-2瓦片范围内。利用EnMAP现有可比传感器数据对模拟CHIME数据进行的验证表明，2024年德国AOI的光谱相关性较高，平均RMSE为6.154 [%]，相关系数为0.924。这一公开可用、独特且经过充分验证的数据集，已经能够支持基于哨兵扩展任务数据在广泛的应用领域中准备和开发未来产品与服务。由于两年广泛时间序列所带来的高数据可用性以及多个AOIs，未来产品已经可以测试其时间和空间可迁移性。","Recent advances in remote sensing.","2026-09-16T00:00:00Z",81,{"impact":19,"substance":165,"depth":166,"authority":81,"freshness":82,"relevant":22,"comment":167},22,19,"面向未来Sentinel扩展任务的高光谱、热红外与L波段合成数据集研究，方法新颖、验证充分且公开可用，对农业遥感产品预研具有实质价值，值得进入每日精选。",[169],{"name":161,"url":158},[27,171,28,172,173,174],"高光谱","地表温度","哥白尼计划","合成数据",[176,177],"哥白尼计划 农业遥感 合成数据 地表温度","哥白尼计划 农业遥感","哥白尼计划农业遥感合成数据地表温度-2797","10.62880\u002Frars26005",{"doi":179,"openalex_id":181,"authors":182,"venue":161,"cited_by_count":36,"oa_url":158,"card":220,"direction":63,"ingested_from":65},"W7213413531",[183,185,187,190,193,196,199,202,204,207,209,211,213,215,218],{"name":184,"orcid":9},"Christian Miesgang",{"name":186,"orcid":9},"Sandra Dotzler",{"name":188,"orcid":189},"Anusha Sanmathi Sathyaniranjan","https:\u002F\u002Forcid.org\u002F0009-0009-8710-4622",{"name":191,"orcid":192},"Silke Migdall","https:\u002F\u002Forcid.org\u002F0000-0001-9089-6274",{"name":194,"orcid":195},"Heike Bach","https:\u002F\u002Forcid.org\u002F0000-0001-8060-2498",{"name":197,"orcid":198},"J. A. D. L. Blommaert","https:\u002F\u002Forcid.org\u002F0000-0002-5797-2439",{"name":200,"orcid":201},"Astrid Vannoppen","https:\u002F\u002Forcid.org\u002F0000-0001-5140-832X",{"name":203,"orcid":9},"Louis Snyders",{"name":205,"orcid":206},"Mihkel Veske","https:\u002F\u002Forcid.org\u002F0000-0003-2367-9215",{"name":208,"orcid":9},"Sven Kautlenbach",{"name":210,"orcid":9},"Catherine Odera",{"name":212,"orcid":9},"Tetiana Shtym",{"name":214,"orcid":9},"Tanel Tamm",{"name":216,"orcid":217},"Anke Schickling","https:\u002F\u002Forcid.org\u002F0000-0001-7446-7752",{"name":219,"orcid":9},"Melisa Soledad Heredia",{"tldr":221,"method":222,"finding":223,"direction":63,"opportunity":224},"生成CHIME高光谱、LSTM热红外和ROSE-L L波段模拟数据集，为未来Sentinel扩展任务","辐射传输模型反演、Sen-ET时空锐化、SAOCOM-1模拟，覆盖德比爱三区两年","模拟CHIME与EnMAP光谱相关性0.924，RMSE 6.154%，数据集公开且验证良好。","可基于该模拟数据集提前开发高光谱、热红外与L波段融合的作物监测和表型反演新算法。","2026-09-17T23:30:37.404847Z",{"id":227,"title":228,"url":229,"summary":230,"summary_zh":231,"content":9,"source_name":232,"source_url":229,"published_at":162,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":78,"score_detail":233,"sources":235,"tags":237,"search_phrases":241,"slug":244,"view_count":36,"doi":245,"paper":246,"created_at":274},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。","Proceedings of the International Association of Hydrological Sciences",{"impact":21,"substance":123,"depth":80,"authority":81,"freshness":13,"relevant":22,"comment":234},"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。",[236],{"name":232,"url":229},[27,238,28,239,240],"空间异质性","西非农业","小农户生计",[242,243],"小农户生计 空间异质性 农业遥感 西非农业","小农户生计 空间异质性","小农户生计空间异质性农业遥感西非农业-2658","10.5194\u002Fpiahs-389-45-2026",{"doi":245,"openalex_id":247,"authors":248,"venue":232,"cited_by_count":36,"oa_url":229,"card":269,"direction":63,"ingested_from":65},"W7213239844",[249,251,253,256,259,261,264,266],{"name":250,"orcid":9},"Yaovi Aymar Bossa",{"name":252,"orcid":9},"Adjo Brigitte Bossa",{"name":254,"orcid":255},"Yacouba Yira","https:\u002F\u002Forcid.org\u002F0000-0003-3879-8153",{"name":257,"orcid":258},"Ozias Hounkpatin","https:\u002F\u002Forcid.org\u002F0000-0003-1105-8649",{"name":260,"orcid":9},"Octave Djangni",{"name":262,"orcid":263},"Jean Hounkpè","https:\u002F\u002Forcid.org\u002F0000-0002-5521-9339",{"name":265,"orcid":9},"Hélyette Arielle Odoumbourou",{"name":267,"orcid":268},"Ernest Amoussou","https:\u002F\u002Forcid.org\u002F0000-0002-9402-4446",{"tldr":270,"method":271,"finding":272,"direction":63,"opportunity":273},"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。","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。","2026-09-16T23:30:28.573293Z",{"id":276,"title":277,"url":278,"summary":279,"summary_zh":280,"content":9,"source_name":281,"source_url":278,"published_at":282,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":283,"score_detail":284,"sources":286,"tags":288,"search_phrases":292,"slug":295,"view_count":36,"doi":296,"paper":297,"created_at":307},2057,"Federation Cannot Replace Stewardship: Governing the Calibration Chain in Continental-Scale Observation Networks","https:\u002F\u002Fdoi.org\u002F10.1175\u002Fbams-d-26-0091.1","Abstract Federated earth observation systems depend on calibration and validation infrastructure that most governance conversations treat as a technical detail rather than a foundational dependency. This essay argues that documentation and traceability, the technical core of the earth observation community’s own reference-measurement standards, are necessary but not sufficient. No amount of documentation substitutes for a named, accountable person empowered to act on it before a decision is made, and no amount of federation architecture compensates for an anchor point that is not physically grounded, named, and maintained by someone whose reputation is attached to it. The argument draws on operational experience across agricultural and wildland fire remote sensing, airborne collection during disaster response, and large-scale geospatial federation supporting hundreds of thousands of users across dozens of integrated system components. At continental scale, with sovereign and institutional boundaries cutting across shared data products, the calibration and validation work that anchors observation data to physical reality is not overhead. It is the reason these data are worth anything at all.","联邦地球观测系统依赖于定标与验证基础设施，而大多数治理讨论将其视为技术细节，而非基础性依赖。本文认为，文档化与可追溯性——地球观测界自身参考测量标准的技术核心——是必要的，但并不充分。再多的文档也无法替代一个在决策之前被赋予行动权力、具名且可问责的人；再多的联邦架构也无法弥补一个没有物理根基、没有具名、没有由声誉与之绑定的人维护的锚点。本论证基于农业与野火遥感、灾害响应中的机载数据采集，以及支持数十个集成系统组件、服务数十万用户的大规模地理空间联邦的运营经验。在大陆尺度上，当主权与制度边界横切共享数据产品时，将观测数据锚定于物理现实的定标与验证工作并非 overhead。它正是这些数据具有任何价值的原因所在。","Bulletin of the American Meteorological Society","2026-09-09T00:00:00Z",79,{"impact":19,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":285},"该论文从治理角度剖析大陆尺度观测网络的校准链条，强调可问责的锚点机制，对农业遥感数据可信度建设有实质参考价值，但偏学术理论、非政策落地，适合作为专业精选。",[287],{"name":281,"url":278},[27,289,28,290,291],"数据治理","观测网络","校准验证",[293,294],"农业遥感 数据治理 校准验证 观测网络","农业遥感 数据治理","农业遥感数据治理校准验证观测网络-2057","10.1175\u002Fbams-d-26-0091.1",{"doi":296,"openalex_id":298,"authors":299,"venue":281,"cited_by_count":36,"oa_url":9,"card":302,"direction":63,"ingested_from":65},"W7212000778",[300],{"name":301,"orcid":9},"Anthony Veltri",{"tldr":303,"method":304,"finding":305,"direction":63,"opportunity":306},"论文主张联邦架构无法替代有明确责任人的校准监管，强调校准链治理是大陆尺度观测网络的基础。","基于农业与野火遥感、灾害响应航空采集及大规模地理空间联邦的运营经验进行论证。","文档与可追溯性必要但不充分，必须有具名且被赋权的人在决策前行动，锚点需物理落地并有人维护。","可研究农业观测网络中校准责任人的制度设计、激励与问责机制，以及跨主权边界的校准链治理框架。","2026-09-10T23:30:27.747997Z",{"id":309,"title":310,"url":311,"summary":312,"summary_zh":313,"content":9,"source_name":314,"source_url":311,"published_at":315,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":316,"score_detail":317,"sources":320,"tags":322,"search_phrases":324,"slug":327,"view_count":36,"doi":328,"paper":329,"created_at":344},1740,"Spatio-Temporal Dynamics of Vegetation Response to Climatic Variability in Akinyele Local Government Area, Oyo State, Nigeria","https:\u002F\u002Fdoi.org\u002F10.33003\u002Ffjs-2026-1016-5660","Although vegetation is very sensitive to climatic variability, there is limited evidence on a local scale in many tropical areas. This study has evaluated the spatio-temporal variability of vegetation response to climatic variability in Akinyele Local Government Area, Oyo State, Nigeria using NDVI, Rainfall, LST data of multi-temporal satellite image for the years 2015, 2020 and 2025. Google Earth Engine was used to process the sentinel-2 imagery, CHIRPS rainfall data, and MODIS LST products. NDVI was categorized into 3 classes (sparse, moderate and dense vegetation). The data set consisted of 5,991 sample points with which statistical analyses (Pearson correlation, multiple linear regression, ANOVA) were carried out. Results indicated that from 2015 to 2020 the density of vegetation decreased by 126.45 km² but increased by 158.55 km² until 2025, in accordance with the climatic changes. Mean NDVI decreased from 0.629 in 2015 to 0.611 in 2020, then increased to 0.654 in 2025. LST had a consistently high negative correlation (r = -0.650 to -0.669, p \u003C 0.001) with NDVI, whereas there was a relatively weak positive correlation with rainfall (r = 0.291–0.336). Regression models accounted for 43%–45% of the variability in NDVI, with LST being the most significant predictor (p \u003C 0.001). The results provide a basis for understanding how temperature is the dominant climatic factor controlling vegetation in the study area, and its implications for land use planning, climate change adaptation, sustainable agriculture, and urban green infrastructure in the urbanising landscapes of Nigeria.","尽管植被对气候变率非常敏感，但在许多热带地区，关于局部尺度的证据仍然有限。本研究利用2015年、2020年和2025年的多时相卫星影像数据，包括归一化植被指数（NDVI）、降雨量和地表温度（LST），评估了尼日利亚奥约州阿基涅尔地方政府区域植被对气候变率的时空响应。研究采用谷歌地球引擎（Google Earth Engine）处理哨兵二号（Sentinel-2）影像、CHIRPS降雨数据和MODIS地表温度产品。NDVI被划分为三个等级（稀疏植被、中等植被和茂密植被）。数据集包含5，991个样本点，并据此进行了统计分析（皮尔逊相关分析、多元线性回归、方差分析）。结果表明，从2015年到2020年，植被密度减少了126.45平方公里，但到2025年又增加了158.55平方公里，这与气候变化相一致。平均NDVI从2015年的0.629降至2020年的0.611，随后在2025年上升至0.654。地表温度与NDVI始终呈高度负相关（r = -0.650至-0.669，p \u003C 0.001），而降雨量与NDVI呈相对较弱的正相关（r = 0.291–0.336）。回归模型解释了NDVI变异的43%–45%，其中地表温度是最显著的预测因子（p \u003C 0.001）。研究结果为理解温度作为控制研究区植被的主导气候因子提供了基础，并揭示了其对尼日利亚城市化景观中土地利用规划、气候变化适应、可持续农业和城市绿色基础设施建设的启示意义。","FUDMA Journal of Sciences","2026-09-03T00:00:00Z",57,{"impact":21,"substance":123,"depth":19,"authority":21,"freshness":318,"relevant":22,"comment":319},3,"地方尺度植被对气候响应的遥感研究，数据详实，但影响范围有限，时效性较低。",[321],{"name":314,"url":311},[27,87,323,30],"NDVI",[325,326],"农业遥感 植被监测 气候变化 NDVI","农业遥感 植被监测","农业遥感植被监测气候变化NDVI-1740","10.33003\u002Ffjs-2026-1016-5660",{"doi":328,"openalex_id":330,"authors":331,"venue":314,"cited_by_count":36,"oa_url":338,"card":339,"direction":63,"ingested_from":65},"W7207552979",[332,334,336],{"name":333,"orcid":9},"Monday Ghandi Daniel",{"name":335,"orcid":9},"Ojodugbowa Shedrach Omachoko",{"name":337,"orcid":9},"Iyam Ubi Effiom","https:\u002F\u002Ffjs.fudutsinma.edu.ng\u002Findex.php\u002Ffjs\u002Farticle\u002Fdownload\u002F5660\u002F3848",{"tldr":340,"method":341,"finding":342,"direction":63,"opportunity":343},"利用遥感数据评估尼日利亚某地植被对气候变化的时空响应。","GEE处理Sentinel-2、CHIRPS、MODIS数据，统计相关与回归分析","温度是主导因子，与NDVI强负相关，降雨弱正相关。","可延伸至热带城市化区域植被-气候耦合模型及适应性管理策略研究。","2026-09-05T23:30:27.920627Z"]