遇见数据集

Extent of severe flooding events in the Elbe river, Germany (OAL-DE)

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Zenodo2021-08-31 更新2026-05-28 收录
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The ambition of H2020 OPERANDUM project is to develop and document Nature Based Solutions (NBS) to mitigate risks associated with hydro-meteorological (HM) hazards. NBS mitigate risks by reducing the vulnerability of a particular system. The aim of this work is to demonstrate the use of multisource remote sensing data in documenting the impact of extreme HM events to advance knowledge on vulnerability and exposure. In particular the focus is to document past impacts due to extreme events selected from a characterization of recent (30 years) HM events in 11 Open Air Laboratories (OALs) where co-design, co-development and deployment of NBS are taking place. The impacts were documented by applying a wide spectrum of satellite image data and other, close – range, remote sensing techniques. A better understanding of the consequences due to extreme HM events in a particular area (OALs) is essential to identify elements at risk and expected to provide a reference to evaluate the reduction of vulnerability and mitigation of risks past the completion of NBS. This dataset contains Remote Sensing observations for the OAL-Greece , notably: - Flood maps of the identified extreme flood events occurred in the Elbe river, Germany (OAL-DE) in the last 30 years derived by Space-borne Remote Sensing observations - Top and Bottom of Atmosphere reflectance, RS indicators and SAR backscatter used to derive the flood maps.

欧盟地平线2020(H2020)OPERANDUM项目的核心目标是开发并记录基于自然的解决方案(Nature Based Solutions, NBS),以缓解与水文气象(hydro-meteorological, HM)灾害相关的各类风险。基于自然的解决方案通过降低特定系统的脆弱性,实现风险的有效缓解。本研究旨在论证多源遥感数据在记录极端水文气象事件影响方面的应用价值,从而深化对灾害脆弱性与暴露水平的认知。具体而言,研究聚焦于记录11个露天实验室(Open Air Laboratories, OALs)近30年间发生的极端水文气象事件所造成的过往影响——这些实验室正在开展基于自然的解决方案的协同设计、协同开发与部署工作。研究团队通过广泛的卫星影像数据及其他近距离遥感技术,完成了上述影响的记录工作。深入理解特定区域(即各露天实验室)内极端水文气象事件所引发的后果,是识别风险要素的必要前提,同时也可为基于自然的解决方案完成建设后,评估其脆弱性降低与风险缓解效果提供基准参考。本数据集包含希腊露天实验室(OAL-Greece)的遥感观测数据,具体包括:- 基于星载遥感观测得到的、过去30年间德国易北河(OAL-DE)发生的已识别极端洪水事件的洪水淹没图;- 用于生成上述洪水淹没图的大气顶反射率、大气底反射率、遥感指标以及合成孔径雷达(Synthetic Aperture Radar, SAR)后向散射数据。

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Zenodo
创建时间:
2021-08-31
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