Flood mapping by SAR: Possible approaches to mitigate errors due to ambiguous radar signatures

The latest generation of synthetic aperture radar (SAR) systems allows providing emergency managers with near real time flood maps characterized by a very high spatial resolution. Near real time flood detection algorithms generally search for regions of low backscatter, thus assuming that floodwater appears dark in a SAR image. It is well known that this assumption is not always valid. For instance, in urban areas, the double bounce backscattering involving ground and vertical walls produce high radar return that can be further increased by the presence of the highly reflective floodwater. In addition, even mapping bare or scarcely vegetated inundated terrains, or crops totally submerged by water can turn out to be a difficult task. In fact, in the presence of significant wind that roughens the water surface, floodwater can appear bright in SAR images. This paper proposes possible strategies to cope with flood mapping using SAR data in urban areas and in the presence of significant wind. In particular, the use of the interferometric coherence for floodwater detection in urban areas and the use of an electromagnetic model able to simulate the radar return from shallow water as function of the wind field are proposed.

[1]  Nazzareno Pierdicca,et al.  Flood monitoring using multi-temporal COSMO-SkyMed data: Image segmentation and signature interpretation , 2011 .

[2]  Nazzareno Pierdicca,et al.  Monitoring Flood Evolution in Vegetated Areas Using COSMO-SkyMed Data: The Tuscany 2009 Case Study , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  L. Guerriero,et al.  Natural Hazards and Earth System Sciences An algorithm for operational flood mapping from Synthetic Aperture Radar ( SAR ) data using fuzzy logic , 2011 .

[4]  Nazzareno Pierdicca,et al.  Analysis and Interpretation of the COSMO-SkyMed Observations of the 2011 Japan Tsunami , 2012, IEEE Geoscience and Remote Sensing Letters.

[5]  W. Rosenthal,et al.  Similarity of the wind wave spectrum in finite depth water: 1. Spectral form , 1985 .

[6]  Laura Candela,et al.  Observing floods from space: Experience gained from COSMO-SkyMed observations , 2013 .

[7]  Nazzareno Pierdicca,et al.  Comparing Scatterometric and Radiometric Simulations With Geophysical Model Functions to Tune a Sea Wave Spectrum Model , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Nazzareno Pierdicca,et al.  An algorithm for operational flood mapping from Synthetic Aperture Radar (SAR) data using fuzzy logic , 2011 .

[9]  K. Katsaros,et al.  A Unified Directional Spectrum for Long and Short Wind-Driven Waves , 1997 .

[10]  Frank S. Marzano,et al.  Discrimination of Water Surfaces, Heavy Rainfall, and Wet Snow Using COSMO-SkyMed Observations of Severe Weather Events , 2014, IEEE Transactions on Geoscience and Remote Sensing.