The Use of Sentinel-1 Time-Series Data to Improve Flood Monitoring in Arid Areas

Sandro Martinis,Simon Plank,Kamila Ćwik

doi:10.3390/rs10040583

Sandro Martinis, Simon Plank + Show 1 more

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https://doi.org/10.3390/rs10040583

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Abstract

Due to the similarity of the radar backscatter over open water and over sand surfaces a reliable near real-time flood mapping based on satellite radar sensors is usually not possible in arid areas. Within this study, an approach is presented to enhance the results of an automatic Sentinel-1 flood processing chain by removing overestimations of the water extent related to low-backscattering sand surfaces using a Sand Exclusion Layer (SEL) derived from time-series statistics of Sentinel-1 data sets. The methodology was tested and validated on a flood event in May 2016 at Webi Shabelle River, Somalia and Ethiopia, which has been covered by a time-series of 202 Sentinel-1 scenes within the period June 2014 to May 2017. The approach proved capable of significantly improving the classification accuracy of the Sentinel-1 flood service within this study site. The Overall Accuracy increased by ~5% to a value of 98.5% and the User’s Accuracy increased by 25.2% to a value of 96.0%. Experimental results have shown that the classification accuracy is influenced by several parameters such as the lengths of the time-series used for generating the SEL.

Highlights

There has been significant progress in near real-time (NRT) flood mapping based on Synthetic Aperture Radar (SAR) satellite data
An on-demand TerraSAR-X-based Flood Service (TFS) has been proposed by Martinis et al [5], which consists of a fully automatic processing chain for near real-time flood detection using TerraSAR-X data. This processing chain has been adapted by Twele et al [8] to C-band SAR data of the Sentinel-1 (S-1) mission, which is operated by the European Space Agency (ESA) in the frame of the European Union’s Copernicus Programme
Thhaveeaapproach proved capable of significantly improving the flood classification accuracy at this study site

Summary

Introduction

There has been significant progress in near real-time (NRT) flood mapping based on Synthetic Aperture Radar (SAR) satellite data. An on-demand TerraSAR-X-based Flood Service (TFS) has been proposed by Martinis et al [5], which consists of a fully automatic processing chain for near real-time flood detection using TerraSAR-X data. This processing chain has been adapted by Twele et al [8] to C-band SAR data of the Sentinel-1 (S-1) mission, which is operated by the European Space Agency (ESA) in the frame of the European Union’s Copernicus Programme. The application of the processing chains within rapid mapping activities significantly has helped to improve the delivery time of the crisis information to the users, for example, during flood-related activations within the frame of the International Charter ‘Space and Major Disasters’ [11,12]

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