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Open AccessArticle

Flood Mapping in a Complex Environment Using Bistatic TanDEM-X/TerraSAR-X InSAR Coherence

1
Higher School of Communications of Tunis COSIM Lab, University of Carthage, 2083 Tunis, Tunisia
2
Environmental Research and Innovation Department (ERIN), Luxembourg Institute of Science and Technology (LIST), L-4422, Belvaux, Luxembourg
3
Department of ITI, IMT-Atlantique Bretagne-Pays de la Loire, 29238 Brest cedex 03, France
4
Institut National de la Recherche Scientifique, Centre Eau Terre Environnement, 490 rue de la Couronne, Québec, QC G1K 9A9, Canada
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(12), 1873; https://doi.org/10.3390/rs10121873
Received: 12 September 2018 / Revised: 5 November 2018 / Accepted: 6 November 2018 / Published: 23 November 2018
(This article belongs to the Special Issue Remote Sensing for Flood Mapping and Monitoring of Flood Dynamics)
In this paper, we assess the flood mapping capabilities of the X-band Synthetic Aperture Radar (SAR) imagery acquired by the bistatic pair TanDEM-X/TerraSAR-X (TDX/TSX). The main objective is to investigate the added value of the bistatic TDX/TSX Interferometric Synthetic Aperture Radar (InSAR) coherence in addition to the SAR backscatter in the context of inundation mapping. As a classifier, we consider a Random Forest (RF) classification scheme using TDX/TSX SAR intensities and their bistatic InSAR coherence to extract the flood extent map. To evaluate the classification results and as no “ground truth” was available at the SAR data acquisition time, we set up a LISFLOOD-FP hydraulic model for simulating the temporal evolution of the flood water. The flood map simulated by the model shows good performances with an Overall Accuracy (OA) of 97.92 % and a Critical Success Index (CSI) of 94 . 01 % . The SAR-derived flood map is then compared to the LISFLOOD-FP extent map simulated at the SAR data acquisition time. As a test case, we consider the flooding event of the Richelieu River that occurred in the Montérégie region of Quebec (Canada) from April to June 2011. Experimental results highlight the potential of the bistatic InSAR coherence for more accurate flood mapping in a complex landscape with urban and vegetation areas. The classification results of the SAR-derived flood map with respect to the LISFLOOD-FP flood map reach an OA of 78.65 % and a Precision of 82.08 % when integrating the bistatic InSAR coherence. These classification OA and Precision values are 69.63 % and 64.52 % , respectively, using only the TDX/TSX SAR intensity. View Full-Text
Keywords: TanDEM-X; TerraSAR-X; bistatic SAR; bistatic InSAR coherence; Random Forest; flood mapping; hydraulic modelling; Richelieu River TanDEM-X; TerraSAR-X; bistatic SAR; bistatic InSAR coherence; Random Forest; flood mapping; hydraulic modelling; Richelieu River
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Chaabani, C.; Chini, M.; Abdelfattah, R.; Hostache, R.; Chokmani, K. Flood Mapping in a Complex Environment Using Bistatic TanDEM-X/TerraSAR-X InSAR Coherence. Remote Sens. 2018, 10, 1873.

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