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Full-Text Articles in Social and Behavioral Sciences
Semi-Automated Surface Water Detection With Synthetic Aperture Radar Data: A Wetland Case Study, Amir Behnamian, Sarah Banks, Lori White, Brian Brisco, Koreen Millard, Jon Pasher, Zhaohua Chen, Jason Duffe, Laura Bourgeau-Chavez, Michael Battaglia
Semi-Automated Surface Water Detection With Synthetic Aperture Radar Data: A Wetland Case Study, Amir Behnamian, Sarah Banks, Lori White, Brian Brisco, Koreen Millard, Jon Pasher, Zhaohua Chen, Jason Duffe, Laura Bourgeau-Chavez, Michael Battaglia
Michigan Tech Publications
In this study, a new method is proposed for semi-automated surface water detection using synthetic aperture radar data via a combination of radiometric thresholding and image segmentation based on the simple linear iterative clustering superpixel algorithm. Consistent intensity thresholds are selected by assessing the statistical distribution of backscatter values applied to the mean of each superpixel. Higher-order texture measures, such as variance, are used to improve accuracy by removing false positives via an additional thresholding process used to identify the boundaries of water bodies. Results applied to quad-polarized RADARSAT-2 data show that the threshold value for the variance texture measure …