Unveiling Flooded Areas With Sentinel-1 (SAR) Imagery

How to quickly delineate flooded areas through Sentinel-1 imagery the from Microsoft Planetary Computer using the “Sentinel-1 Flood Finder” package

This post is also freely available on geocorner.net: https://www.geocorner.net/post/unlocking-geopandas-efficiency-6-tips-to-boost-geopandas-analysis-performance

Introduction

Floods, among the most devastating natural hazards, impact the lives of millions each year, causing tragic losses and widespread destruction. Timely forecasts and alert systems are crucial to minimizing deaths and damage, and obtaining accurate floodwater extent measurements is vital for effective emergency response. While traditional field surveys can be costly and impractical, remote sensing may offer a powerful solution.

However, conventional water detection techniques relying on optical satellite imagery often face limitations during floods. Intense cloud cover can obscure the ground, rendering optical sensors ineffective. In such scenarios, radar technology (i.e., Synthetic Aperture Radar, SAR) offers a critical advantage, being able to penetrate clouds and capture valuable data, even during extreme weather conditions. However, water mapping using SAR imagery is not straightforward and requires specialized techniques and tools.

S1FloodFinder: A User-Friendly Solution for Flood Mapping

During the past few months, I’ve been conducting a research on automating the delineation of flooded regions in Brazilian municipalities. After initial tests, it was clear the difficulty to perform such a study with optical imagery due to cloud cover, especially during these rainy events. Objectively, radar Sentinel-1 can be twice more effective than Sentinel-2 (58% vs. 28%) in detecting flood events, according to an assessment performed over Europe (Tarpanelli et al., 2022)[1].

The downside is that water detection through SAR can be overwhelming, often requiring advanced statistics or change detection approaches. There are no water indices, such as the NDWI, and simple thresholding, such as OTSU, does not deliver accurate results…