ISPRS-Annals ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Annals ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9050 Copernicus Publications Göttingen, Germany 10.5194/isprs-annals-V-1-2020-395-2020 DERIVING EXCLUSION MAPS FROM C-BAND SAR TIME-SERIES: AN ADDITIONAL INFORMATION LAYER FOR SAR-BASED FLOOD EXTENT MAPPING Zhao J. https://orcid.org/0000-0002-9638-3792 1 2 Chini M. 1 Pelich R. 1 Matgen P. 1 Hostache R. https://orcid.org/0000-0002-8109-6010 1 Cao S. 2 Wagner W. https://orcid.org/0000-0001-7704-6857 2 Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, Luxembourg Research Group Remote Sensing, Department of Geodesy and Geoinformation, Vienna University of Technology, Austria 03 08 2020 V-1-2020 395 400 Copyright: © 2020 J. Zhao et al. 2020 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://isprs-annals.copernicus.org/articles/V-1-2020/395/2020/isprs-annals-V-1-2020-395-2020.html The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/V-1-2020/395/2020/isprs-annals-V-1-2020-395-2020.pdf

Change detection has been widely used in many flood-mapping algorithms using pairs of Synthetic Aperture Radar (SAR) intensity images as floodwater often leads to a substantial decrease of backscatter. However, limitations still exist in many areas, such as shadow, layover, urban areas and densely vegetated areas, where the SAR backscatter is not sufficiently impacted by floodwater-related surface changes. This study focuses on these so-called exclusion areas, i.e. areas where SAR does not allow detecting water based on change detection. Our approach considers both pixel-based time series analyses and object-based spatial analyses using 20m Sentinel-1 Interferometric Wide Swath data, including 922 Sentinel-1 tiles covering the River Severn basin (UK) and the Lake Maggiore area (Italy). The results show that our exclusion map presents a good agreement (∼63%) with reference data derived from different data sources and indicate that it may complement SAR-derived flood extent maps. Allowing to accurately identify potential misclassifications in flood extent mapping, our exclusion map provides valuable information for flood management and, in particular, flood forecasting and prediction.