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21 February 2017 Characterization and classification of freshwater marshy wetland using synthetic aperture radar polarimetry: a case study from Loktak wetland, Northeast India
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Abstract
Loktak is the largest natural wetland of Northeast India, the last home of endangered brow-antlered deer, and a site of global significance recognized under Ramsar convention. Ecological and human-meditated spatial patterns of Loktak wetland were characterized and classified using a Radarsat-2 C band synthetic aperture radar (SAR) satellite data. Radarsat-2 quad-pol scene of dry season was preprocessed and classified using PolSARpro software. Eigen vector–eigen value decomposition of coherency matrix (T3) was performed to characterize the scattering properties of wetland targets based on entropy (H)/anisotropy (A)/alpha angle (α) segmentation. Results illustrate that RGB color display of H/A/α images is a useful indicator of wetland structure and composition, and provide clear visual discrimination of open water, floating phumdi, permanent phumdi cover, and associated man-made features. Six classes, namely, floating phumdi, permanent phumdi, scrub/shrub, fallow land, built-up, and open water were mapped using Wishart classification of H/A/α images. Scattering mechanisms of natural and man-made targets synthesized from PolSAR data, and their classification using Wishart algorithm have been validated through a visually classified map and field reference points. The land cover generated would be useful for conservation and management of Loktak wetland and brow-antlered deer population.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2017/$25.00 © 2017 SPIE
Hitendra Padalia and Mohamed Musthafa "Characterization and classification of freshwater marshy wetland using synthetic aperture radar polarimetry: a case study from Loktak wetland, Northeast India," Journal of Applied Remote Sensing 11(1), 016029 (21 February 2017). https://doi.org/10.1117/1.JRS.11.016029
Received: 29 February 2016; Accepted: 31 January 2017; Published: 21 February 2017
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