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 ( T 3 ) 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)
Hitendra Padalia, Hitendra Padalia, Mohamed Musthafa, 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 . Submission: Received: 29 February 2016; Accepted: 31 January 2017
Received: 29 February 2016; Accepted: 31 January 2017; Published: 21 February 2017
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