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。

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

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