一个基于卫星图像的框架,用于在洪水场景中快速分配资源,以提高损失和损害基金的有效性
Jeremy Eudaric1,2, Heidi Kreibich3, Andrés Camero4
1Chair of Data Science in Earth Observation, Department of Aerospace and Geodesy, Technical University of Munich, 80333, Munich, Germany. jeremy.eudaric@dlr.de.
Scientific reports
|August 20, 2024
概括
一个新的框架使用遥感和地理空间数据快速分配资源用于洪水恢复. 它确定了最需要的地区,比如希腊的帕拉马斯,帮助洪水后的重建工作.
科学领域:
- 环境科学 环境科学
- 地理空间分析的研究.
- 灾害管理 灾害管理
背景情况:
- 气候变化和城市化加剧了全球的洪水风险.
- 损失和损害基金旨在帮助气候脆弱的国家,但恢复资源的分配是复杂的.
- 有限的数据和工具阻碍了洪水后有效的重建和补偿.
研究的目的:
- 提出一个新的资源分配框架,用于洪水后的恢复.
- 利用遥感和地理空间数据进行快速需求评估.
- 支持灾难管理中的及时决策.
主要方法:
- 使用Sentinel-1合成孔径雷达 (SAR) 数据评估洪水前后的洪水范围.
- 开发基于建筑物和人口数据的暴露指数.
- 整合洪水危险,建筑物和人口暴露驱动因素来分配资源.
主要成果:
- 该框架有效量化了资源分配需求.
- 塞萨利地区的洪水分析发现,帕拉马斯市拥有最高的资源分配需求 (暴露指数为5/8).
- 证明了框架对快速洪水后评估的能力.
结论:
- 拟议的框架为政府提供了一个全面的工具,以加快洪水后的恢复.
- 遥感和地理空间数据对于高效的灾害资源管理至关重要.
- 该框架使数据驱动的决策能够实现公平的资源分配.
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