[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-5488":3,"related-5488":81},{"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":18,"tags":20,"primary_topic":9,"secondary_topics":24,"classification":25,"search_phrases":54,"slug":57,"view_count":15,"doi":58,"paper":59,"created_at":80},5488,"Application of radar remote sensing for cyclone damage mapping in Bangladesh: a coherence-based approach","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fnhess-26-5103-2026","Abstract. Rapid and reliable assessment of cyclone-induced damage remains a major challenge in coastal regions where cloud cover and accessibility limit conventional approaches. This study presents a coherence-based Synthetic Aperture Radar (SAR) framework for identifying as well as quantifying cyclone-induced surface changes in coastal districts in Bangladesh. Multi-temporal Sentinel-1 data were analyzed using interferometric coherence to capture spatial and temporal variations associated with five major cyclones: Amphan (2020), Sitrang (2022), Mocha (2023), Hamoon (2023), and Remal (2024). A time-series approach incorporating multiple pre-, during-, and post-event image pairs was implemented to distinguish cyclone-driven changes from natural surface variability and to improve detection reliability. The results reveal a consistent decline in coherence during cyclone events followed by gradual recovery. Spatial analysis indicates that areas of significant coherence loss correspond to zones affected by flooding, vegetation damage, and structural disruption. Estimated damage extents varied across cyclones, with Remal (2024) showing the largest affected area (~601 km²), followed by Mocha (~474 km²), Amphan (~288 km²), Sitrang (~122 km²), and Hamoon (~117 km²). Validation using field observations and secondary data yielded an overall classification accuracy of 94 %, confirming the robustness of the coherence-based approach. Complementary inundation mapping further demonstrated that coherence captures a broader spectrum of cyclone impacts beyond flood extent alone, including wind-induced damage and geomorphic changes. This study establishes multi-temporal SAR coherence analysis as a scalable, cloud-independent, and operationally effective tool for rapid post-cyclone damage assessment. The proposed framework enhances the reliability of disaster monitoring in complex coastal environments and offers strong potential for integration into near-real-time disaster response systems. Future research should focus on integrating multi-sensor datasets and long-term coherence time series to further refine damage characterization and reduce uncertainty.","摘要：在云覆盖和可达性限制传统方法的沿海地区，快速可靠地评估气旋所致损害仍是一项重大挑战。本研究提出了一种基于相干性的合成孔径雷达（SAR）框架，用于识别并量化孟加拉国沿海地区气旋引起的地表变化。利用干涉相干性对多时相Sentinel-1数据进行分析，以捕捉与五次主要气旋相关的时间和空间变化：安潘（Amphan，2020年）、西特朗（Sitrang，2022年）、穆查（Mocha，2023年）、哈蒙（Hamoon，2023年）和雷马尔（Remal，2024年）。研究采用了一种整合多个事件前、事件期间和事件后影像对的时间序列方法，以将气旋驱动变化与自然地表的变异性区分开来，并提高检测可靠性。结果表明，气旋事件期间相干性持续下降，随后逐渐恢复。空间分析表明，相干性显著丧失的区域与受洪水、植被破坏和结构损毁影响的区域相对应。各气旋的估计受损范围有所不同，其中雷马尔（2024年）受影响面积最大（约601 km²），其次为穆查（约474 km²）、安潘（约288 km²）、西特朗（约122 km²）和哈蒙（约117 km²）。利用实地观测和二手数据进行的验证获得了94%的总体分类精度，证实了基于相干性方法的稳健性。补充的淹没制图进一步表明，相干性捕捉到了除洪水范围之外的更广泛的气旋影响，包括风致损害和地貌变化。本研究确立了多时相SAR相干性分析作为一种可扩展、不依赖云覆盖且业务上有效的工具，用于气旋后快速损害评估。所提出的框架提高了复杂沿海环境中灾害监测的可靠性，并具有将其集成到近实时灾害响应系统中的强大潜力。未来研究应侧重于整合多传感器数据集和长期相干性时间序列，以进一步完善损害表征并减少不确定性。",null,"Natural hazards and earth system sciences","2026-10-19T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该研究聚焦孟加拉国海岸带气旋灾害的SAR相干性制图，虽涉及遥感技术，但与三农、农业信息化、数字乡村等主题无直接关联，不宜进入每日精选。",[19],{"name":10,"url":6},[21,22,23],"SAR遥感","遥感监测","灾害评估",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":29},"needs_review","2026-10-22.2","rules",{"candidates":30,"agricultural_evidence":14,"reason":53},[31,39,47],{"code":32,"score":33,"supported":34,"title":35,"abstract":37,"tags":38},"I3",9,true,[36],"remote sensing",[],[22],{"code":40,"score":41,"supported":34,"title":42,"abstract":43,"tags":46},"I4",6,[],[44,45],"空间分析","spatial analysis",[],{"code":48,"score":49,"supported":14,"title":50,"abstract":51,"tags":52},"H7",1,[],[],[23],"农业相关性需要复核",[55,56],"Sentinel-1 气旋 灾害制图","雷达遥感 孟加拉湾 气旋","Sentinel-1气旋灾害制图-5488","10.5194\u002Fnhess-26-5103-2026",{"doi":58,"openalex_id":60,"authors":61,"venue":10,"cited_by_count":15,"oa_url":72,"card":73,"direction":77,"ingested_from":79},"W7160271999",[62,65,68,70],{"name":63,"orcid":64},"Shadmin Islam Prova","https:\u002F\u002Forcid.org\u002F0000-0001-8549-1758",{"name":66,"orcid":67},"Md. Shahoriar Sarker","https:\u002F\u002Forcid.org\u002F0009-0006-5131-1214",{"name":69,"orcid":9},"Rosdania Islam",{"name":71,"orcid":9},"Ridad Ibne Mahfuz","https:\u002F\u002Fnhess.copernicus.org\u002Farticles\u002F26\u002F5103\u002F2026\u002Fnhess-26-5103-2026.pdf",{"tldr":74,"method":75,"finding":76,"direction":77,"opportunity":78},"用Sentinel-1多时相干涉相干性识别并量化孟加拉湾五次气旋的地表破坏。","Sentinel-1多时相InSAR相干性时间序列，结合实地与二手数据验证。","气旋期间相干性显著下降后逐步恢复，分类精度94%，Remal受灾面积最大约601km²。","农业遥感与作物表型","可将相干性框架迁移至农田风灾与洪涝受损制图，融合多源SAR与长时序相干性降低不确定性。","openalex","2026-10-21T23:30:23.509482Z",{"total":41,"page":49,"page_size":41,"items":82},[83,151,226,300,379,462],{"id":84,"title":85,"url":86,"summary":87,"summary_zh":88,"content":9,"source_name":89,"source_url":86,"published_at":90,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":91,"score_detail":92,"sources":98,"tags":100,"primary_topic":9,"secondary_topics":104,"classification":105,"search_phrases":127,"slug":130,"view_count":15,"doi":131,"paper":132,"created_at":150},4823,"Comparing Sentinel-2 Spectral Indices for Mapping Forest Fire Damage in Pollino National Park, Italy","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fisprs-archives-xlviii-m-13-2026-1-2026","In recent years, climate change has significantly increased the severity and frequency of wildfires across Europe, with the 2025 season marking an unprecedented peak of one million hectares burned. Rapid and cost-effective mapping of these damaged areas is crucial for environmental recovery, making satellite remote sensing an indispensable tool. This study evaluates and compares the performance of four Sentinel-2 spectral burn indices for mapping forest fire damage within the Pollino National Park (Italy) occurred in September 2025, an area severely affected by the devastating summer fires of 2025. The analyzed indices include the Normalized Burn Ratio (NBR), Normalized Burn Ratio Plus (NBR+), Normalized Burn Ratio Short Wave Infrared (NBR-SWIR), and Normalized Difference Short Wave Infrared (ND-SWIR). An image differencing technique was applied to pre-fire (June 7, 2025) and post-fire (November 14, 2025) datasets, followed by a supervised Maximum Likelihood classification to map burned and unburned classes. Accuracy assessment via confusion matrices showed that NBR and NBR+ delivered the highest performance, achieving an Overall Accuracy (OA) of 0.976 and 0.974, respectively. ND-SWIR performed closely at 0.966, whereas NBR-SWIR yielded a lower OA of 0.873 due to the misclassification of bare soil transitions as burned areas. These findings highlight the critical role of specific SWIR-band combinations in optimizing automated wildfire monitoring systems.","近年来，气候变化显著加剧了欧洲野火的严重程度和发生频率，2025年火灾季烧毁面积达到一百万公顷，创下历史新高。快速且经济高效地绘制这些受损区域对于环境恢复至关重要，使卫星遥感成为不可或缺的工具。本研究评估并比较了四种哨兵2号（Sentinel-2）光谱燃烧指数在绘制2025年9月发生于意大利波利诺国家公园（Pollino National Park）的森林火灾损害中的表现，该地区受2025年夏季毁灭性火灾的严重影响。所分析的指数包括归一化燃烧比率（NBR）、归一化燃烧比率增强版（NBR+）、归一化燃烧比率短波红外（NBR-SWIR）以及归一化差值短波红外（ND-SWIR）。研究对火灾前（2025年6月7日）和火灾后（2025年11月14日）数据集应用了图像差值技术，随后采用监督最大似然分类法绘制燃烧与未燃烧类别。通过混淆矩阵进行的精度评估表明，NBR和NBR+表现最佳，总体精度（OA）分别达到0.976和0.974。ND-SWIR紧随其后，为0.966，而NBR-SWIR由于将裸土转变误分类为燃烧区域，总体精度较低，为0.873。这些发现凸显了特定短波红外波段组合在优化自动化野火监测系统中的关键作用。","˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences\u002FInternational archives of the photogrammetry, remote sensing and spatial information sciences","2026-10-12T00:00:00Z",74,{"impact":93,"substance":94,"depth":95,"authority":96,"freshness":33,"relevant":49,"comment":97},12,22,18,13,"方法对比扎实、结论明确，但属区域案例研究，对农业信息化有间接参考价值，可入精选但非必选。",[99],{"name":89,"url":86},[101,22,23,102,103],"Sentinel-2","森林火灾","植被指数",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":106},{"candidates":107,"agricultural_evidence":14,"reason":53},[108,113,120],{"code":32,"score":33,"supported":34,"title":109,"abstract":110,"tags":112},[],[111,36],"遥感",[101,103,22],{"code":48,"score":114,"supported":34,"title":115,"abstract":116,"tags":119},8,[],[117,118],"气候变化","climate change",[102,23],{"code":121,"score":122,"supported":34,"title":123,"abstract":124,"tags":126},"H2",3,[],[125],"soil",[],[128,129],"Sentinel-2 森林火灾 遥感","Pollino 国家公园 火烧迹地","Sentinel-2森林火灾遥感-4823","10.5194\u002Fisprs-archives-xlviii-m-13-2026-1-2026",{"doi":131,"openalex_id":133,"authors":134,"venue":89,"cited_by_count":15,"oa_url":144,"card":145,"direction":77,"ingested_from":79},"W7221528348",[135,137,139,142],{"name":136,"orcid":9},"Giuseppina Costanzo",{"name":138,"orcid":9},"Gianluigi Ferrara",{"name":140,"orcid":141},"Claudio Parente","https:\u002F\u002Forcid.org\u002F0000-0002-8328-9764",{"name":143,"orcid":9},"Vincenzo Verde","https:\u002F\u002Fisprs-archives.copernicus.org\u002Farticles\u002FXLVIII-M-13-2026\u002F1\u002F2026\u002Fisprs-archives-XLVIII-M-13-2026-1-2026.pdf",{"tldr":146,"method":147,"finding":148,"direction":77,"opportunity":149},"比较四种 Sentinel-2 光谱指数在意大利 Pollino 国家公园 2025 年林火损伤制图","Sentinel-2 火前火后影像差值 + 最大似然监督分类，用混淆矩阵评估四种","NBR 与 NBR+ 精度最高（OA 0.976、0.974），NBR-SWIR 因裸土误判仅 0.","可探索多指数融合与机器学习分类器，提升复杂地表下火烧迹地自动制图鲁棒性。","2026-10-13T23:30:23.838067Z",{"id":152,"title":153,"url":154,"summary":155,"summary_zh":156,"content":9,"source_name":157,"source_url":154,"published_at":158,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":159,"score_detail":160,"sources":162,"tags":164,"primary_topic":168,"secondary_topics":173,"classification":174,"search_phrases":202,"slug":205,"view_count":206,"doi":207,"paper":208,"created_at":225},4355,"Agricultural Flood Damage Assessment: A Systematic Review of Methods, Coverage, and Integration Gaps","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fegusphere-2026-3701","Abstract. Agricultural flooding causes tens of billions of dollars in annual losses globally, yet the methods used to assess these losses systematically capture only a fraction of their true economic scope. This systematic review synthesizes 65 peer-reviewed studies published between 1984 and 2025 to evaluate how agricultural flood damage is measured, what damage categories are covered, and where critical methodological gaps persist. We find a structural asymmetry across the reviewed literature – all 65 reviewed studies address direct immediate damages – primarily crop yield loss estimated through depth-damage functions or remote sensing – while direct induced effects appear in only 8 studies, indirect damages in 9, and intangible damages in fewer than 5. This asymmetry has persisted for four decades, through a major remote sensing revolution, because the dominant methods are structurally incapable of measuring damage categories beyond direct immediate losses. We introduce a Methods-by-Damage-Category Matrix that maps eight assessment methods against five damage categories, making the coverage gap visible and providing a diagnostic framework for method selection. Three post-2013 damage frontiers – long-term land productivity degradation, supply chain finance disruption, and farmer mental health – are identified as emerging categories warranting dedicated methodological development. Existing agricultural flood damage estimates used in benefit–cost analyses and disaster compensation are systematically downward-biased; closing this bias requires integrating remote sensing-based physical detection with economic valuation methods capable of capturing the full damage taxonomy.","摘要：农业洪水每年在全球造成数百亿美元损失，然而用于系统评估这些损失的方法仅能捕捉其真实经济影响的一小部分。本系统综述综合了1984年至2025年间发表的65项同行评审研究，评估农业洪水损失如何被测量、涵盖了哪些损失类别，以及关键方法论空白存在于何处。我们发现，所综述文献中存在结构性不对称——全部65项研究均涉及直接即时损失，主要是通过深度-损失函数或遥感估算的作物产量损失——而直接诱发效应仅出现在8项研究中，间接损失出现在9项研究中，无形损失则不足5项。这种不对称已持续四十年，历经遥感技术的重大革命，因为主流方法在结构上无法测量直接即时损失之外的损失类别。我们引入“方法-损失类别矩阵”，将八种评估方法与五类损失类别进行对应，使覆盖缺口清晰可见，并为方法选择提供诊断框架。2013年后的三个损失前沿——长期土地生产力退化、供应链金融中断和农民心理健康——被识别为值得专门方法论开发的新兴类别。现有用于成本效益分析和灾害补偿的农业洪水损失估算存在系统性低估；弥合这一偏差需要将基于遥感的物理检测与能够捕捉完整损失分类的经济估值方法相结合。","OpenAlex","2026-10-06T00:00:00Z",79,{"impact":95,"substance":94,"depth":95,"authority":96,"freshness":114,"relevant":49,"comment":161},"系统综述揭示农业洪灾损失评估长期偏低估的方法学缺口，提出方法-损失类别矩阵，对灾害补偿与成本收益分析有实质参考价值。",[163],{"name":157,"url":154},[165,166,167,22,23],"农业信息化","粮食安全","农业保险",{"code":32,"slug":169,"name":170,"path":171,"parent_code":172},"remote-sensing","遥感与农情监测","\u002Ftopic\u002Fdigital-agriculture\u002Fremote-sensing","I",[],{"status":175,"locked":14,"version":27,"method":28,"evidence":176},"classified",{"candidates":177,"agricultural_evidence":34},[178,183,188,193,197],{"code":32,"score":179,"supported":34,"title":180,"abstract":181,"tags":182},7,[],[111,36],[22],{"code":184,"score":49,"supported":14,"title":185,"abstract":186,"tags":187},"A8",[],[],[166],{"code":189,"score":49,"supported":14,"title":190,"abstract":191,"tags":192},"G3",[],[],[167],{"code":48,"score":49,"supported":14,"title":194,"abstract":195,"tags":196},[],[],[23],{"code":198,"score":49,"supported":14,"title":199,"abstract":200,"tags":201},"I1",[],[],[165],[203,204],"农业洪涝灾害 损失评估","遥感 农作物 灾害损失","农业洪涝灾害损失评估-4355",2,"10.5194\u002Fegusphere-2026-3701",{"doi":207,"openalex_id":209,"authors":210,"venue":9,"cited_by_count":15,"oa_url":154,"card":220,"direction":77,"ingested_from":79},"W7220668753",[211,214,217],{"name":212,"orcid":213},"Shokhrukh–Mirzo Jalilov","https:\u002F\u002Forcid.org\u002F0000-0002-2428-9094",{"name":215,"orcid":216},"Haluk Gedikoğlu","https:\u002F\u002Forcid.org\u002F0000-0002-0158-2597",{"name":218,"orcid":219},"Robert Maltsbarger","https:\u002F\u002Forcid.org\u002F0009-0003-7801-8390",{"tldr":221,"method":222,"finding":223,"direction":77,"opportunity":224},"系统综述65项农业洪水损失评估研究，揭示方法仅覆盖直接即时损失的结构性偏差。","系统综述1984-2025年65篇文献，构建方法-损失类别矩阵。","所有研究仅测直接即时损失，间接、诱导及无形损失严重缺失，致损失估计系统性偏低。","可开发融合遥感与经济学估值的方法，量化长期土地退化、供应链金融与农户心理健康等新兴损失类别。","2026-10-07T23:30:25.887527Z",{"id":227,"title":228,"url":229,"summary":230,"summary_zh":231,"content":9,"source_name":232,"source_url":229,"published_at":233,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":234,"sources":236,"tags":238,"primary_topic":9,"secondary_topics":242,"classification":243,"search_phrases":266,"slug":269,"view_count":270,"doi":271,"paper":272,"created_at":299},3840,"Open-Source GIS Applications for Flood and Landslide Assessment: Comparative Cases from Poland and Malaysia","https:\u002F\u002Fdoi.org\u002F10.36777\u002Fjag2026.5.2.6","Research on natural disasters requires analytical procedures that are rapid, reproducible, and based on sound scientific principles. Such procedures should also be accessible to institutions responsible for environmental monitoring, land-use planning, and disaster risk reduction. This study evaluated the practical use of publicly available geospatial data and open-source GIS tools for the preliminary assessment of two contrasting natural hazards: the September 2024 flood in Lower Silesia, Poland, with particular focus on the urban floodplain of Wrocław, and the December 2022 landslide in Batang Kali, Selangor, Malaysia. The study utilised Copernicus Sentinel-2 MSI Level-2A satellite imagery, digital elevation model (DEM) data from the Copernicus programme, OpenStreetMap vector layers, and spatial processing in QGIS. The methodology employed a pre- and post-event change-detection approach based on spectral indices. The Normalized Difference Water Index (NDWI) was used to map the extent of flooding, while the Normalized Difference Vegetation Index (NDVI) was used to identify vegetation disturbances associated with the landslide. Raster classification, elevation analysis, vector-layer overlay, and thematic mapping were subsequently used to delineate disaster-affected areas and examine their spatial relationships with built-up areas, hydrographic features, and terrain morphology. The results show that the Copernicus Data Space Ecosystem and QGIS provide a transparent and cost-effective analytical environment for the preliminary assessment of natural disaster impacts. In the Wrocław case, the NDWI helped identify flooded areas and infrastructure potentially exposed to flooding. In the Batang Kali case, differences in NDVI helped identify patterns of vegetation disturbance associated with the landslide-affected area. The study demonstrates that open-source geospatial tools can support repeatable natural disaster analysis, geospatial education, and early-stage decision support for disaster risk reduction.","自然灾害研究需要快速、可重复且基于可靠科学原理的分析程序。此类程序还应能为负责环境监测、土地利用规划和灾害风险减少的机构所使用。本研究评估了公开地理空间数据和开源GIS工具在两类不同自然灾害初步评估中的实际应用：2024年9月波兰下西里西亚洪水，重点关注弗罗茨瓦夫的城市洪泛区；以及2022年12月马来西亚雪兰莪州巴当加里滑坡。研究使用了哥白尼Sentinel-2 MSI Level-2A卫星影像、哥白尼计划的数字高程模型（DEM）数据、OpenStreetMap矢量图层，并在QGIS中进行空间处理。方法采用基于光谱指数的灾前灾后变化检测方法。归一化差异水体指数（NDWI）用于制图洪水范围，归一化差异植被指数（NDVI）用于识别与滑坡相关的植被扰动。随后利用栅格分类、高程分析、矢量图层叠加和专题制图来圈定受灾区域，并考察其与建成区、水系特征和地形形态的空间关系。结果表明，哥白尼数据空间生态系统和QGIS为自然灾害影响的初步评估提供了透明且具有成本效益的分析环境。在弗罗茨瓦夫案例中，NDWI有助于识别淹没区和可能受洪水影响的基础设施。在巴当加里案例中，NDVI差异有助于识别与滑坡影响区相关的植被扰动格局。研究表明，开源地理空间工具能够支持可重复的自然灾害分析、地理空间教育以及灾害风险减少的早期决策支持。","Journal of Asian Geography","2026-09-29T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":235},"该论文聚焦开源GIS与遥感在洪涝滑坡灾害评估中的应用，属地理信息与灾害风险领域，与三农、农业信息化、智慧农业无直接关联，故不进入每日精选。",[237],{"name":232,"url":229},[239,22,23,240,241],"NDVI","NDWI","开源GIS",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":244},{"candidates":245,"agricultural_evidence":14,"reason":53},[246,252,258,262],{"code":40,"score":247,"supported":34,"title":248,"abstract":250,"tags":251},11,[249],"GIS",[249],[],{"code":253,"score":122,"supported":34,"title":254,"abstract":255,"tags":257},"I2",[],[256],"decision support",[],{"code":32,"score":206,"supported":14,"title":259,"abstract":260,"tags":261},[],[],[239,22],{"code":48,"score":49,"supported":14,"title":263,"abstract":264,"tags":265},[],[],[23],[267,268],"QGIS 洪水 滑坡 评估","Sentinel-2 灾害 遥感","QGIS洪水滑坡评估-3840",4,"10.36777\u002Fjag2026.5.2.6",{"doi":271,"openalex_id":273,"authors":274,"venue":232,"cited_by_count":15,"oa_url":293,"card":294,"direction":77,"ingested_from":79},"W7214781133",[275,277,279,281,283,285,288,290],{"name":276,"orcid":9},"Oliwia Szweda",{"name":278,"orcid":9},"Wazif Akmal Bin Hassdi",{"name":280,"orcid":9},"Muhammad Naqib Akmal Bin Hasbullah",{"name":282,"orcid":9},"Kacper Kaczmarski",{"name":284,"orcid":9},"Divbya A.P. Lachimanan",{"name":286,"orcid":287},"K. Tomiczek","https:\u002F\u002Forcid.org\u002F0000-0001-9227-310X",{"name":289,"orcid":9},"Hareyani Zabidi",{"name":291,"orcid":292},"Monika Żogała","https:\u002F\u002Forcid.org\u002F0000-0002-2309-6493","https:\u002F\u002Fejournal.usm.my\u002Fjag\u002Farticle\u002Fdownload\u002F6257\u002F9385",{"tldr":295,"method":296,"finding":297,"direction":77,"opportunity":298},"用开源GIS与Sentinel-2数据对比评估波兰洪水与马来西亚滑坡灾害影响。","Sentinel-2影像、DEM、OpenStreetMap与QGIS，NDWI","开源工具可低成本、可重复地识别洪水范围与滑坡植被扰动，支持早期决策。","可将该开源遥感流程迁移至农田洪涝与滑坡风险监测，结合作物损失评估与预警。","2026-09-30T23:30:28.033994Z",{"id":301,"title":302,"url":303,"summary":304,"summary_zh":305,"content":9,"source_name":306,"source_url":303,"published_at":307,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":308,"score_detail":309,"sources":312,"tags":314,"primary_topic":9,"secondary_topics":319,"classification":320,"search_phrases":349,"slug":352,"view_count":15,"doi":353,"paper":354,"created_at":378},5577,"Assessing Land Use and Land Cover Change in the Jamanxim River Region (Brazilian Amazon) from 2015 to 2025 Using CBERS-4\u002FPAN Imagery","https:\u002F\u002Fdoi.org\u002F10.29150\u002Fjhrs.v16i4.269068","Land use and land cover (LULC) changes in the Amazon are among the main drivers of biodiversity loss, ecosystem degradation, and the intensification of climate change. This study aimed to analyze the multitemporal dynamics of LULC around the Jamanxim River, Pará, Brazilian Amazon, between 2015 and 2025, using high-resolution imagery from the CBERS-4\u002FPAN satellite. The study area covers 492.74 km², including part of the Jamanxim National Forest, a conservation unit under strong pressure from agricultural expansion and logging activities. The methodology included geometric correction of the images, Gram–Schmidt pansharpening, and supervised classification with the Random Forest algorithm, validated with historical imagery from Google Earth Pro. Thematic maps of land use and cover were generated, and performance metrics such as overall accuracy, omission and commission errors, and F1-scores were assessed. The results indicated a significant reduction in forest cover, from 412.28 km² in 2015 to 355.47 km² in 2025 (–13.78%). Non-vegetated areas increased by 132.47%, while agricultural areas expanded by 54.97%. The forest and water body classes showed high accuracy (F1-score > 0.95), while confusion persisted between agricultural and bare soil classes. Overall accuracy remained above 90% across all years, with the highest performance recorded in 2020 (96.31%). These results highlight the potential of CBERS-4\u002FPAN imagery for monitoring multitemporal changes in tropical forest landscapes. At the same time, they reveal the intensification of deforestation and the growing threats to conservation in the Amazon, reinforcing the importance of remote sensing for environmental management and policy support.","亚马逊地区的土地利用与土地覆盖（LULC）变化是生物多样性丧失、生态系统退化以及气候变化加剧的主要驱动因素之一。本研究旨在利用CBERS-4\u002FPAN卫星的高分辨率影像，分析2015年至2025年间巴西亚马孙州雅曼辛河（Jamanxim River）周边土地利用与土地覆盖的多时相动态。研究区面积为492.74 km²，包括雅曼辛国家森林（Jamanxim National Forest）的一部分，该保护区正面临农业扩张和采伐活动的强烈压力。研究方法包括影像几何校正、Gram–Schmidt全色锐化以及基于随机森林（Random Forest）算法的监督分类，并利用Google Earth Pro的历史影像进行验证。研究生成了土地利用与覆盖专题图，并评估了总体精度、漏分误差与错分误差以及F1分数等性能指标。结果表明，森林覆盖显著减少，从2015年的412.28 km²降至2025年的355.47 km²（–13.78%）。无植被区域增加了132.47%，农业区域扩张了54.97%。森林和水体类别表现出较高精度（F1分数 > 0.95），而农业类别与裸土类别之间仍存在混淆。各年份总体精度均保持在90%以上，其中2020年性能最高（96.31%）。这些结果凸显了CBERS-4\u002FPAN影像在监测热带森林景观多时相变化方面的潜力，同时揭示了亚马逊地区森林砍伐的加剧以及保护面临的日益增长的威胁，进一步强调了遥感在环境管理和政策支持中的重要性。","Journal of Hyperspectral Remote Sensing","2026-10-20T00:00:00Z",78,{"impact":95,"substance":94,"depth":310,"authority":93,"freshness":33,"relevant":49,"comment":311},17,"该研究利用CBERS-4\u002FPAN影像量化亚马逊保护区十年间森林减少13.78%，方法规范、结论可靠，对遥感监测与生态保护有参考价值，但地域性强、与国内三农直接关联有限。",[313],{"name":306,"url":303},[22,315,316,317,318],"土地利用","森林保护","亚马逊","CBERS-4",[],{"status":26,"locked":14,"version":27,"method":28,"evidence":321},{"candidates":322,"agricultural_evidence":34,"reason":348},[323,330,334,338,342],{"code":324,"score":179,"supported":34,"title":325,"abstract":326,"tags":329},"H6",[],[327,328],"生物多样性","biodiversity",[315],{"code":32,"score":179,"supported":34,"title":331,"abstract":332,"tags":333},[],[111,36],[22],{"code":48,"score":41,"supported":34,"title":335,"abstract":336,"tags":337},[],[117,118],[],{"code":121,"score":122,"supported":34,"title":339,"abstract":340,"tags":341},[],[125],[],{"code":343,"score":122,"supported":34,"title":344,"abstract":345,"tags":347},"I7",[],[346],"研究方法",[],"多个产业证据相当，需要确认主归属",[350,351],"CBERS-4 亚马逊 土地利用","Jamanxim 森林覆盖 遥感","CBERS-4亚马逊土地利用-5577","10.29150\u002Fjhrs.v16i4.269068",{"doi":353,"openalex_id":355,"authors":356,"venue":306,"cited_by_count":15,"oa_url":303,"card":373,"direction":77,"ingested_from":79},"W7223141286",[357,360,362,365,368,371],{"name":358,"orcid":359},"Ubiratan Joaquim da Silva","https:\u002F\u002Forcid.org\u002F0000-0001-7995-6416",{"name":361,"orcid":9},"Gabriel Henrique Santos Silva",{"name":363,"orcid":364},"Juarez Antonio da Silva","https:\u002F\u002Forcid.org\u002F0000-0002-2898-0309",{"name":366,"orcid":367},"Anderson Luiz Ribeiro de Paiva","https:\u002F\u002Forcid.org\u002F0000-0003-3475-1454",{"name":369,"orcid":370},"Leidjane Maria Maciel de Oliveira","https:\u002F\u002Forcid.org\u002F0000-0003-1251-6998",{"name":372,"orcid":9},"Sylvana Melo dos Santos",{"tldr":374,"method":375,"finding":376,"direction":77,"opportunity":377},"用CBERS-4\u002FPAN影像分析亚马逊Jamanxim河流域2015-2025年土地利用变化。","几何校正、Gram-Schmidt融合、随机森林监督分类，Google Eart","森林覆盖减少13.78%，农业扩张54.97%，裸地增132.47%，总体精度超90%。","可探索中巴地球资源卫星在热带森林退化监测中的业务化应用与多源数据融合。","2026-10-22T11:20:42.901761Z",{"id":380,"title":381,"url":382,"summary":383,"summary_zh":384,"content":9,"source_name":385,"source_url":382,"published_at":307,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":159,"score_detail":386,"sources":390,"tags":392,"primary_topic":397,"secondary_topics":401,"classification":402,"search_phrases":424,"slug":427,"view_count":15,"doi":428,"paper":429,"created_at":461},5576,"Land cover change and soil salinization in Mozambique: A counterfactual analysis over two decades (2001−2022)","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.catena.2026.110691","Soil salinization is a major issue that constrains the sustainable development of agriculture in arid, semi-arid, and coastal lowland areas. It is of great importance for regional land management and climate adaptation to clarify the influence of land cover change on soil salinization. This study aims to quantitatively assess the contribution of land cover change to soil salinization in Mozambique, where both rapid land cover transformation and salinization issues are evident. Firstly, we integrated soil profile electrical conductivity (EC) data, Landsat time-series remote sensing imagery, TerraClimate meteorological data, and the 30 m resolution land cover data, to construct a remote sensing-based EC inversion model for Mozambique. Secondly, we applied a spatially and environmentally constrained counterfactual matching method to quantitatively identify the contributions of different land cover changes on soil salinization trends. Our results reveal that: (1) the spatial distribution of soil salinization in Mozambique exhibits distinct a clear association with proximity to water bodies, with high EC areas primarily concentrated around Lake Malawi in the north and in the coastal regions of Greater Maputo in the south. (2) 26.98% of Mozambique's territory showed a trend of intensifying soil salinization, while 10.88% exhibited a decreasing trend. Areas with intensifying trends are primarily concentrated in the central alluvial plains, localized agricultural development zones, and coastal lowlands. (3) Urbanization was significantly associated with an increasing salinization trend after false discovery rate correction, suggesting that the expansion of impervious surfaces, changes in drainage patterns, and soil compaction may exacerbate localized salt accumulation. Agricultural expansion showed a negative trend difference, consistent with the potential influence of crop cover, tillage, and wet-season leaching, although this association was not significant after false discovery rate correction. The effects of ecological restoration and other factors were not statistically significant. In addition to elucidating the heterogeneous impacts of land cover changes in Mozambique on soil salinization trends, this study also provides methodological guidance and a scientific basis for monitoring\u002Fmanaging soil salinity risks in other coastal lowlands.","土壤盐渍化是制约干旱、半干旱及沿海低地地区农业可持续发展的主要问题。阐明土地覆盖变化对土壤盐渍化的影响，对区域土地管理和气候适应具有重要意义。本研究旨在定量评估土地覆盖变化对莫桑比克土壤盐渍化的贡献，该国土地覆盖转型迅速且盐渍化问题突出。首先，我们整合了土壤剖面电导率（EC）数据、Landsat时间序列遥感影像、TerraClimate气象数据以及30 m分辨率土地覆盖数据，构建了基于遥感的莫桑比克EC反演模型。其次，我们采用空间与环境约束的反事实匹配方法，定量识别不同土地覆盖变化对土壤盐渍化趋势的贡献。研究结果表明：（1）莫桑比克土壤盐渍化的空间分布与水体邻近性呈现明显的关联，高EC区域主要集中于北部的马拉维湖周边以及南部大马普托沿海地区。（2）莫桑比克26.98%的国土面积呈现土壤盐渍化加剧趋势，而10.88%呈现减轻趋势。加剧趋势区域主要集中于中部冲积平原、局部农业开发区及沿海低地。（3）经错误发现率校正后，城市化与盐渍化加剧趋势显著相关，表明不透水面扩张、排水格局改变及土壤压实可能加剧局部盐分累积。农业扩张呈现负向趋势差异，与作物覆盖、耕作及湿季淋洗的潜在影响一致，但该关联经错误发现率校正后不显著。生态恢复及其他因素的影响在统计上不显著。本研究不仅阐明了莫桑比克土地覆盖变化对土壤盐渍化趋势的异质性影响，还为其他沿海低地土壤盐渍化风险的监测与管理提供了方法学指导和科学依据。","CATENA",{"impact":387,"substance":94,"depth":95,"authority":388,"freshness":33,"relevant":49,"comment":389},16,14,"该研究基于遥感与反事实匹配方法，定量评估土地覆盖变化对盐渍化的贡献，方法新颖、结论可靠，对沿海低地盐渍化监测具有参考价值，但属境外区域研究，国内政策与产业影响有限。",[391],{"name":385,"url":382},[22,393,394,395,396],"莫桑比克","土壤盐渍化","土地覆盖变化","盐分反演",{"code":121,"slug":125,"name":398,"path":399,"parent_code":400},"土壤健康与改良","\u002Ftopic\u002Fenvironment\u002Fsoil","H",[],{"status":175,"locked":14,"version":27,"method":28,"evidence":403},{"candidates":404,"agricultural_evidence":34},[405,410,414,420],{"code":121,"score":388,"supported":34,"title":406,"abstract":407,"tags":409},[125],[408,125],"土壤",[],{"code":32,"score":179,"supported":34,"title":411,"abstract":412,"tags":413},[],[111,36],[22],{"code":48,"score":41,"supported":34,"title":415,"abstract":416,"tags":419},[],[417,418],"气候适应","干旱",[],{"code":324,"score":49,"supported":14,"title":421,"abstract":422,"tags":423},[],[],[395],[425,426],"莫桑比克 土壤盐渍化 遥感","土地覆盖变化 盐渍化 反事实分析","莫桑比克土壤盐渍化遥感-5576","10.1016\u002Fj.catena.2026.110691",{"doi":428,"openalex_id":430,"authors":431,"venue":385,"cited_by_count":15,"oa_url":382,"card":456,"direction":77,"ingested_from":79},"W7223069171",[432,434,436,438,441,443,446,449,451,453],{"name":433,"orcid":9},"Yue Li",{"name":435,"orcid":9},"Mengfei Shi",{"name":437,"orcid":9},"Fei Zhang",{"name":439,"orcid":440},"Brian Alan Johnson","https:\u002F\u002Forcid.org\u002F0000-0003-1911-3585",{"name":442,"orcid":9},"Gowhar Meraj",{"name":444,"orcid":445},"Jaime Carlos Macuácua","https:\u002F\u002Forcid.org\u002F0000-0002-4822-6098",{"name":447,"orcid":448},"Pankaj Kumar","https:\u002F\u002Forcid.org\u002F0000-0002-5264-3951",{"name":450,"orcid":9},"Yuanfang Chai",{"name":452,"orcid":9},"Hongtao Xu",{"name":454,"orcid":455},"Xu Ma","https:\u002F\u002Forcid.org\u002F0000-0003-0644-7498",{"tldr":457,"method":458,"finding":459,"direction":77,"opportunity":460},"量化莫桑比克2001-2022年土地覆盖变化对土壤盐渍化的贡献。","融合EC剖面、Landsat时序与气候数据反演EC，并用空间环境约束的反事实匹配","26.98%区域盐渍化加剧；城市化显著关联盐渍化上升，农业扩张关联不显著。","可将反事实匹配框架迁移至其他滨海低地，并引入作物类型与灌溉制度细化农业扩张的盐渍化效应。","2026-10-22T11:20:42.713789Z",{"id":463,"title":464,"url":465,"summary":466,"summary_zh":467,"content":9,"source_name":468,"source_url":465,"published_at":469,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":159,"score_detail":470,"sources":472,"tags":474,"primary_topic":479,"secondary_topics":485,"classification":486,"search_phrases":502,"slug":505,"view_count":15,"doi":506,"paper":507,"created_at":518},5565,"A Unified Survival-Based Energy Framework Linking Plant Color, Stress, and Productivity","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23540961","Plant coloration, expressed through leaf greenness, floral pigmentation, and fruit color intensity, reflects the integrated outcome of pigment biosynthesis, optical absorption, metabolic regulation, and energy–mass exchange with the environment. While the biochemical pathways governing the synthesis and degradation of major pigment classes—including chlorophylls, carotenoids, and anthocyanins—are well established, existing models largely interpret color expression as a localized biochemical phenomenon. Such approaches do not explicitly account for whole-plant energy balance, transpiration-driven losses, or thermodynamic constraints, limiting their ability to explain widely observed patterns of color saturation, stress-induced fading, and species-specific stability across environmental gradients. Here we develop a unified framework for plant color generation and stability that treats pigmentation as a survival-limited energetic process embedded within the broader dynamics of absorption, transport, metabolism, and entropy production. Central to the framework is a dimensionless energy survival factor, Ψ=AE\u002FTE+ε where AE represents absorbed and retained energetic and elemental resources relevant to pigment formation, TE denotes transpiration-linked, metabolic, and environmental dissipation losses, and ε captures irreducible entropy-producing degradation inherent to non-equilibrium biological systems. By construction, 0\u003CΨ\u003C1, ensuring full compliance with the second law of thermodynamics. When combined with pigment-specific optical absorption coefficients and physiological limitation functions, the framework yields a physically interpretable description of both pigment concentration and color stability. Empirical ranges for absorbed photosynthetically active radiation (≈45–70%), excitation survival (≈85–95%), and respiratory and transpiration losses (≈30–60% of assimilated resources) naturally constrain Ψ, predicting observed limits on sustained pigment accumulation without invoking biochemical inefficiency or ad hoc correction factors. The analysis demonstrates that increased light availability or enhanced biosynthetic capacity alone does not intensify coloration unless absorbed resources survive transport and loss processes. Stress-induced chlorosis, transient anthocyanin accumulation, and saturation of greenness under high irradiance emerge as direct consequences of reduced energy survival rather than impaired pigment synthesis. By explicitly separating survival from synthesis, the framework reconciles molecular-scale pigment biochemistry with whole-plant and ecosystem-scale color dynamics. This survival-based formulation provides a unified physical basis for interpreting plant color variation across species and environments and offers a scalable foundation for crop stress diagnostics, remote-sensing interpretation, and comparative plant phenotyping. More broadly, it extends survival-limited energy principles to visible plant traits, advancing plant science beyond isolated biochemical descriptions toward a systems-level understanding of how energy governs phenotypic expression.","植物色泽通过叶片绿色度、花色苷着色和果实颜色强度体现，反映了色素生物合成、光学吸收、代谢调控以及与环境的能量-物质交换的综合结果。尽管主要色素类别——包括叶绿素、类胡萝卜素和花青素——的合成与降解生化途径已较为明确，但现有模型大多将颜色表达解释为局部生化现象。此类方法未明确考虑整株植物能量平衡、蒸腾驱动的损耗或热力学约束，限制了其解释广泛观察到的颜色饱和度、胁迫诱导褪色以及跨环境梯度的物种特异性稳定性等模式的能力。本文构建了一个统一的植物颜色生成与稳定性框架，将色素沉着视为一种受生存限制的能量过程，并将其嵌入吸收、运输、代谢和熵产生的更广泛动力学之中。该框架的核心是一个无量纲能量生存因子Ψ=AE\u002FTE+ε，其中AE代表与色素形成相关的被吸收并保留的能量和元素资源，TE表示与蒸腾相关的、代谢的和环境的耗散损失，ε则捕捉非平衡生物系统固有的不可约熵产生降解。根据构建方式，0\u003CΨ\u003C1，确保完全符合热力学第二定律。当与色素特异性光学吸收系数和生理限制函数相结合时，该框架可对色素浓度和颜色稳定性给出具有物理可解释性的描述。吸收性光合有效辐射（约45–70%）、激发能存活率（约85–95%）以及呼吸和蒸腾损失（约占同化资源的30–60%）的经验范围自然约束了Ψ，从而预测出所观察到的持续色素积累限度，而无需引入生化低效性或特设校正因子。分析表明，仅增加光照可用性或增强生物合成能力并不会加深颜色，除非被吸收的资源能够在运输和损失过程中存活下来。胁迫诱导的黄化、瞬时花青素积累以及高辐照下绿色度饱和，均表现为能量生存率降低而非色素合成受损的直接后果。通过明确分离生存","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z",{"impact":95,"substance":94,"depth":95,"authority":93,"freshness":33,"relevant":49,"comment":471},"提出以能量生存因子统一解释植物颜色与胁迫的物理框架，方法新颖且对遥感解译和作物诊断有潜在价值，但属预印本理论模型，尚缺田间验证。",[473],{"name":468,"url":465},[475,22,476,477,478],"智慧农业","植物表型","作物胁迫诊断","能量平衡",{"code":480,"slug":481,"name":482,"path":483,"parent_code":484},"B1","vegetables","蔬菜","\u002Ftopic\u002Fhorticulture\u002Fvegetables","B",[],{"status":175,"locked":14,"version":27,"method":28,"evidence":487},{"candidates":488,"agricultural_evidence":34},[489,494,498],{"code":480,"score":122,"supported":34,"title":490,"abstract":491,"tags":493},[],[492],"萝卜",[],{"code":198,"score":49,"supported":14,"title":495,"abstract":496,"tags":497},[],[],[475],{"code":32,"score":49,"supported":14,"title":499,"abstract":500,"tags":501},[],[],[22],[503,504],"植物颜色 能量生存因子","作物胁迫 遥感诊断","植物颜色能量生存因子-5565","10.5281\u002Fzenodo.23540961",{"doi":506,"openalex_id":508,"authors":509,"venue":468,"cited_by_count":15,"oa_url":465,"card":513,"direction":77,"ingested_from":79},"W7223098474",[510],{"name":511,"orcid":512},"Mokhdum Azam Mashrafi","https:\u002F\u002Forcid.org\u002F0009-0002-1801-1130",{"tldr":514,"method":515,"finding":516,"direction":77,"opportunity":517},"提出基于生存的能量框架，用能量存活因子解释植物颜色生成与稳定性。","构建无量纲能量存活因子Ψ=AE\u002F(TE+ε)，结合色素吸收系数与生理限制函数。","颜色深浅取决于吸收资源经运输损耗后的存活率，而非单纯合成能力。","可将Ψ因子与冠层光谱\u002F表型遥感结合，发展胁迫早期诊断与生产力预测模型。","2026-10-22T11:20:31.195819Z"]