Rice Crop Discrimination Using Single Date RISAT1 Hybrid (RH, RV) Polarimetric Data
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Rice is the most important food grain crop in India and contributes to more than 40 percent of the country's food grain production. Spaceborne remote sensing offers economically viable and accurate production and area statistics. The utility of optical remote sensing in mapping rice cropped area is limited by persistent cloud cover during monsoon season. Temporal availability of SAR data has facilitated an operational procedure to monitor the rice crop. The current study discriminates rice crop, using single date hybrid polarimetric data available from RISAT-1 SAR. This was subjected to Raney m-delta, m-chi decompositions, and supervised classification was performed. The accuracy was estimated using the field points. The results were compared with rice map generated using optical sensor Resourcesat-2 LISS-IV and statistical data. The spatial agreement between the estimate from RISAT-1 and LISS-IV data was found to be 85 percent. The class kappa value was 0.94 and 0.92 for LISS-IV and RISAT-1, respectively.
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