Discrimination of mangrove forests and characterization of adjoining land cover classes using temporal C-band Synthetic Aperture Radar data: A case study of Sundarbans |
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| Institution: | 1. Climate and Livability Initiative, Division of Biological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;2. Red Sea Research Center and Computational Bioscience Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;3. Red Sea Research Center, Division of Biological and Environmental Sciences and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;4. Division of Physical Science and Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;1. National Earth and Marine Observation Group, Geoscience Australia, Symonston, ACT, Australia;2. Earth Observation and Ecosystem Dynamics Research Group, Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, United Kingdom;3. Joint Remote Sensing Research Program, School of Environment and Earth Sciences, University of Queensland, Brisbane, Queensland 4067, Australia;4. CSIRO, Land and Water Business Unit, Black Mountain Laboratories, Australian Capital Territory, Australia |
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| Abstract: | C-band dual polarization (HH, HV) Synthetic Aperture Radar (SAR) data from Radarsat-2 were used to discriminate and characterize mangrove forests of the Sundarbans. Multi-temporal data acquired during winter and rainy seasons were analysed for the segregation of mangrove forest area. A decision rule based classification involving combination of three-date HH (range ?11 to ?2 dB) with single-date cross-polarization ratio (2–8) was applied on the datasets for discriminating mangrove forests from other land cover classes. Application of textural measures (entropy and angular second moment) in the aforesaid decision rule based classification produced three broad homogeneous mangrove classes. The area covered by the most homogeneous class increased from January to March and decreased from July to September, and correlated well to the change in the phenological status of the mangroves. Extent of homogeneous areas was more in the eastern region of the Sundarbans than that of the central and western side. Thus, the study revealed that textural measures combined with multi-temporal HH backscatter and single-date cross-polarization ratio in a decision rule classification could be satisfactorily used for characterization of the mangrove forests. |
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| Keywords: | C-band SAR Multi-temporal Mangrove forests Decision rule classification Texture analysis |
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