[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4605":3,"related-4605":58},{"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":21,"classification":22,"search_phrases":38,"slug":39,"view_count":15,"doi":40,"paper":41,"created_at":57},4605,"Global disaster risk assessment from Emergency Events Database (2013–2023)","https:\u002F\u002Fdoi.org\u002F10.5194\u002Fnhess-26-4881-2026","Abstract. This paper defines an Accumulated Risk Index (ARI) to quantify regional risk levels in a global perspective utilizing Emergency Events Database (EM-DAT) from 2013 to 2023. Building on the World Risk Index (WRI) released from World Risk Report 2023, the ARI focuses more on major events caused by multiple natural hazards within 5°×5° latitude-longitude grids, and calculates their accumulative effects during the period. ARI results are presented in two forms including normalized global maps and index rankings of each grid to identify high-risk areas that warrant increased attention. To provide a data foundation for subsequent research at smaller scales, this paper integrates and supplements existing remote sensing images within high-risk areas, publishing them as an open-source 3H Dataset partitioned by grids after standardizing their formats. The unified imagery establishes a valuable resource for deeper insights and more precise analyses in future disaster risk research of developing countries.","摘要：本文定义了一个累积风险指数（ARI），利用2013年至2023年的紧急事件数据库（EM-DAT），从全球视角量化区域风险水平。基于《2023年世界风险报告》发布的世界风险指数（WRI），ARI更侧重于5°×5°经纬度网格内由多种自然灾害引发的重大事件，并计算其在研究时段内的累积效应。ARI结果以两种形式呈现，包括归一化的全球地图和各网格的指数排名，以识别需要重点关注的高风险区域。为后续更小尺度的研究提供数据基础，本文整合并补充了高风险区域内现有的遥感影像，在统一格式后，将其作为按网格划分的开源3H数据集发布。该统一影像资源为未来发展中国家灾害风险研究提供了宝贵基础，有助于获得更深入的见解和更精确的分析。",null,"Natural hazards and earth system sciences","2026-10-07T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该论文聚焦全球灾害风险评估与遥感数据集构建，未涉及三农、农业信息化或数字乡村主题，与平台定位不相关。",[19],{"name":10,"url":6},[12],[],{"status":23,"locked":14,"version":24,"method":25,"evidence":26},"needs_review","2026-10-22.2","rules",{"candidates":27,"agricultural_evidence":14,"reason":37},[28],{"code":29,"score":30,"supported":31,"title":32,"abstract":33,"tags":36},"I3",6,true,[],[34,35],"遥感","remote sensing",[],"农业相关性需要复核",[],"GlobaldisasterriskassessmentfromEmergenc-4605","10.5194\u002Fnhess-26-4881-2026",{"doi":40,"openalex_id":42,"authors":43,"venue":10,"cited_by_count":15,"oa_url":48,"card":49,"direction":55,"ingested_from":56},"W4411878616",[44,46],{"name":45,"orcid":9},"Quan Kong",{"name":47,"orcid":9},"Erqi Zhu","https:\u002F\u002Fnhess.copernicus.org\u002Farticles\u002F26\u002F4881\u002F2026\u002Fnhess-26-4881-2026.pdf",{"tldr":50,"method":51,"finding":52,"direction":53,"opportunity":54},"基于EM-DAT数据构建累积风险指数，评估2013-2023年全球灾害风险并发布高风险区遥感数据集。","利用EM-DAT灾害数据，在5°×5°网格上计算累积风险指数，整合遥感影像。","识别出全球高风险网格区域，并发布标准化的开源3H遥感数据集。","农业遥感与作物表型","可结合农业承灾体与作物遥感，在网格尺度上开展灾害风险对农业生产影响的精细评估。","数字乡村与农业信息化","openalex","2026-10-10T23:30:42.065079Z",{"total":15,"page":59,"page_size":59,"items":60},1,[]]