Coherence-based land cover classification in forested areas of Chattisgarh, Central India, using environmental satellite—advanced synthetic aperture radar data

Abstract

In the present work, the potential of synthetic aperture radar (SAR) interferometric coherence in land cover classification is studied over forested areas of Bilaspur, Chattisgarh, India using Environmental Satellite-Advanced Synthetic Aperture Radar (ENVISAT-ASAR) C-band data. Single look complex (SLC) interferometric pair ASAR data of 24th September 2006 (SLC-1) and 29th October 2006 (SLC-2) covering the study area were acquired and processed to generate backscatter and interferometric coherence images. A false colored composite of coherence, backscatter difference, and mean backscatter was generated and subjected to maximum likelihood classification to delineate major land cover classes of the study area viz., water, barren, agriculture, moist deciduous forest, and sal mixed forests. Accuracy assessment of the classified map is carried out using kappa statistics. Results of the study suggested potential use of ENVISAT-ASAR C-band data in land cover classification of the study area with an overall classification accuracy of 82.5%, average producer's accuracy of 83.69%, and average user's accuracy of 81%. The present study gives a unique scope of SAR data application in land cover classification over the tropical deciduous forest systems of India, which is still waiting for its indigenous SAR system.