A reliable yet inexpensive tool for the estimation of flood water spread is
conducive for efficient disaster management. The application of optical and SAR
imagery in tandem provides a means of extended availability and enhanced
reliability of flood mapping. We propose a methodology to merge these two types
of imagery into a common data space and demonstrate its use in the
identification of affected populations and infrastructure for the 2022 floods
in Pakistan. The merging of optical and SAR data provides us with improved
observations in cloud-prone regions; that is then used to gain additional
insights into flood mapping applications. The use of open source datasets from
WorldPop and OSM for population and roads respectively makes the exercise
globally replicable. The integration of flood maps with spatial data on
population and infrastructure facilitates informed policy design. We have shown
that within the top five flood-affected districts in Sindh province, Pakistan,
the affected population accounts for 31 %, while the length of affected roads
measures 1410.25 km out of a total of 7537.96 km.

本文提出了一种将光学和 SAR 遥感图像融合到共同数据空间中的方法，并在巴基斯坦 2022 年洪水中进行实证研究，揭示了洪水泛滥对地区人口和基础设施的影响。

利用 Sentinel-1、Sentinel-2 和 Landsat-9 图像融合改进洪水制图以识别受洪灾影响的人口和基础设施以实现高效政策设计

Improved flood mapping for efficient policy design by fusion of  Sentinel-1, Sentinel-2, and Landsat-9 imagery to identify population and  infrastructure exposed to floods