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Open AccessArticle

Automatic Surface Water Mapping Using Polarimetric SAR Data for Long-Term Change Detection

1
Department of Earth and Space Science and Engineering, York University, 4700 Keele St., Toronto, ON M3J 1P3, Canada
2
Wildlife Research and Monitoring Section, Ontario Ministry of Natural Resources & Forestry, Trent University, 2140 East Bank Drive, Peterborough, ON K9L 0G2, Canada
*
Author to whom correspondence should be addressed.
Water 2020, 12(3), 872; https://doi.org/10.3390/w12030872
Received: 31 January 2020 / Revised: 11 March 2020 / Accepted: 13 March 2020 / Published: 20 March 2020
(This article belongs to the Section Water Quality and Ecosystems)
Mapping the distribution and persistence of surface water in a timely fashion has broad value for tracking dynamic events like flooding, and for monitoring the effects of climate and human activities on natural resource values and biodiversity. Traditionally, surface water is mapped from optical imagery using semi-automatic approaches. However, this process is time-consuming and the accuracy of results can vary among image interpreters. In recent years, Synthetic Aperture Radar (SAR) images have been increasingly used. Microwave signals sensitive to water content make SAR systems useful for mapping surface water, saturated soils, and flooded vegetation. In this study, a fully automatic method based on robust stepwise thresholding was developed to map and track the change in the extent of surface water using Polarimetric SAR data. The application of this method in both Radarsat-2 and Sentinel-1 data in central Ontario, Canada demonstrates that the developed robust stepwise thresholding approach could facilitate rapid mapping of open water areas with a promising accuracy of over 95%. In addition, the time-series extent of surface water extracted from May 2008 to August 2016 reveals the dynamic nature of surface inundation, and the trend was consistent with the local precipitation data. View Full-Text
Keywords: surface water; synthetic aperture radar; polarimetric data; thresholding; classification surface water; synthetic aperture radar; polarimetric data; thresholding; classification
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MDPI and ACS Style

Zhang, W.; Hu, B.; Brown, G.S. Automatic Surface Water Mapping Using Polarimetric SAR Data for Long-Term Change Detection. Water 2020, 12, 872.

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