Land use land cover change detection by different supervised classifiers on LISS-III temporal datasets

The objective of this paper is to report the study carried out to assess and evaluate changes in Land-Use Land-Cover(LULC) at the region of Aurangabad Municipal Corporation (AMC) for the year 2009 and 2015 using multispectral images acquired from remotely sensed Linear-Imaging-Self-Scanning-Sensor-HI(LISS-HI). The area was categorized into six types, viz. Residential(R), Vegetation(V), Water_Body(W), Rock(Ro), Barren Land(B) and Fallow_Land(F). Four different types of supervised classifiers have been used and it was found the Maximum Likelihood classifier has provided satisfactory and reliable results. The overall accuracy with the classifier was found to be 83% and 93% with Kappa Coefficient 0.78 and 0.90 for the year 2009 and 2015, respectively. The residential area was found to be increased by 1.35% whereas area related to Water Body, Vegetation and Fallow Land have decreased by 0.83%, 2.59% and 18.43% respectively. The areas for Rock remain same, as it was reserved. The area covered by Barren Land increased by 20.44%. The results are of significant for planning and management of AMC.