The World Bank Group, Washington, DC, 20433, USA.
J Environ Manage. 2024 Oct;369:122326. doi: 10.1016/j.jenvman.2024.122326. Epub 2024 Aug 31.
Rapid flood impact assessment methods need complete and accurate flood maps to provide reliable information for disaster risk management, in particular for emergency response and recovery and reconstruction plans. With the aim of improving the rapid assessment of flood impacts, this work presents a new impact assessment method characterized by an enhanced satellite multi-sensor approach for flood mapping, which improves the characterization of the hazard. This includes a novel flood mapping method based on the new multi-temporal Modified Normalized Difference Water Index (MNDWI) that uses multi-temporal statistics computed on time-series of Sentinel-2 multi-spectral satellite images. The multi-temporal aspect of the MNDWI improves characterization of land cover over time and enhances the temporary flooded areas, which can be extracted through a thresholding technique, allowing the delineation of more precise and complete flood maps. The methodology, if implemented in cloud-based environments such as Google Earth Engine (GEE), is computationally light and robust, allowing the derivation of flood maps in matters of minutes, also for large areas. The flood mapping and impact assessment method has been applied to the seasonal flood occurred in South Sudan in 2020, using Sentinel-1, Sentinel-2 and PlanetScope satellite imagery. Flood impacts were assessed considering damages to buildings, roads, and cropland. The multi-sensor approach estimated an impact of 57.4 million USD (considering a middle-bound scenario), higher than what estimated by using Sentinel-1 data only, and Sentinel-2 data only (respectively 24% and 78% of the estimation resulting from the multi-sensor approach). This work highlights the effectiveness and importance of considering multi-source satellite data for flood mapping in a context of disaster risk management, to better inform disaster response, recovery and reconstruction plans.
快速洪水影响评估方法需要完整且准确的洪水图，为灾害风险管理，特别是应急响应和恢复以及重建计划提供可靠的信息。为了提高洪水影响的快速评估，本工作提出了一种新的影响评估方法，其特点是增强了卫星多传感器洪水制图方法，从而提高了灾害特征描述的准确性。这包括一种新的洪水制图方法，该方法基于新的多时相修正归一化差异水体指数（MNDWI），该方法利用多时相统计信息计算 Sentinel-2 多光谱卫星图像时间序列。MNDWI 的多时相特性可随时间改进对土地覆盖的特征描述，并增强临时洪水区域，可通过阈值技术提取临时洪水区域，从而能够绘制更精确和完整的洪水图。如果该方法在 Google Earth Engine（GEE）等基于云的环境中实施，该方法具有计算简便和鲁棒性强的特点，可在几分钟内，甚至是在大面积区域内生成洪水图。本洪水制图和影响评估方法已应用于 2020 年在南苏丹发生的季节性洪水，使用了 Sentinel-1、Sentinel-2 和 PlanetScope 卫星图像。考虑到建筑物、道路和耕地的损坏情况，评估了洪水的影响。多传感器方法估计的影响为 5740 万美元（考虑到中间情况），高于仅使用 Sentinel-1 数据和仅使用 Sentinel-2 数据的估计值（分别为多传感器方法估计值的 24%和 78%）。本工作强调了在灾害风险管理背景下考虑多源卫星数据进行洪水制图的有效性和重要性，以更好地为灾害应急响应、恢复和重建计划提供信息。
