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

• Published in: Remote sensing (Basel, Switzerland) Vol. 11; no. 16; p. 1854
• Main Authors: Mahdavi, Sahel, Salehi, Bahram, Huang, Weimin, Amani, Meisam, Brisco, Brian
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2019
• Subjects: Change detection; Classification; Dongting Lake; Earth science; Environmental hazards; Environmental management; Environmental monitoring; Flood mapping; Flooded areas; Floods; Hydrology; Likelihood ratio; Methods; Neighborhoods; neighbourhood; Principal components analysis; Radar imaging; Radar polarimetry; Remote sensing; Studies; Synthetic aperture radar; Synthetic Aperture RADAR (SAR); Weather; Canada; United States > US
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs11161854

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.