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A PolSAR Change Detection Index Based on Neighborhood Information for Flood Mapping

Department of Electrical and Computer Engineering, Memorial University of Newfoundland, St John’s, NL A1B 3X7, Canada
Wood Environment and Infrastructure Solutions, a Division of Wood Canada Limited, St. John’s, NL A1B 1H3, Canada
C-CORE, St. John’s, NL A1B 3X5, Canada
College of Environmental Science and Forestry (ESF), State University of New York (SUNY), Syracuse, NY 13210, USA
The Canada Center for Mapping and Earth Observation, Ottawa, ON K1S 5K2, Canada
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1854;
Received: 12 June 2019 / Revised: 2 August 2019 / Accepted: 7 August 2019 / Published: 9 August 2019
Change detection using Remote Sensing (RS) techniques is valuable in numerous applications, including environmental management and hazard monitoring. Synthetic Aperture Radar (SAR) images have proven to be even more effective in this regard because of their all-weather, day and night acquisition capabilities. In this study, a polarimetric index based on the ratio of span (total power) values was introduced, in which neighbourhood information was considered. The role of the central pixel and its neighbourhood was adjusted using a weight parameter. The proposed index was applied to detect flooded areas in Dongting Lake, Hunan, China, and was then compared with the Wishart Maximum Likelihood Ratio (MLR) test. Results demonstrated that although the proposed index and the Wishart MLR test yielded similar accuracies (accuracy of 94% and 93%, and Kappa Coefficients of 0.82 and 0.86, respectively), inclusion of neighbourhood information in the proposed index not only increased the connectedness and decreased the noise associated with the objects within the produced map, but also increased the consistency and confidence of the results. View Full-Text
Keywords: Synthetic Aperture RADAR (SAR); change detection; neighbourhood; Dongting Lake Synthetic Aperture RADAR (SAR); change detection; neighbourhood; Dongting Lake
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Mahdavi, S.; Salehi, B.; Huang, W.; Amani, M.; Brisco, B. A PolSAR Change Detection Index Based on Neighborhood Information for Flood Mapping. Remote Sens. 2019, 11, 1854.

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