Multi-temporal LULC Classification using Hybrid Approach and Monitoring Built-up Growth with Shannon’s Entropy for a Semi-arid Region of Rajasthan, India

Abstract

Land use land cover (LULC) classification of Churu district of Rajasthan state in India was done through hybrid classification technique. Landsat imageries of 1998, 2008 and 2018 were used to ascertain the rate and nature of spatio-temporal LULC changes. Major focus was given on vegetative cover change detection of the study area. On the basis of field survey and standard classification classes, the land use classes of the study area were divided into eleven classes. A detailed vegetative classification has been done while categorizing the classes. This classification method employed maximum likelihood and ISODATA clustering. The decision tree approach was used to create the multi-temporal hybrid LULC classification. The accuracy assessment results have shown excellent results at 91% overall accuracy with a kappa of 0.92. The results indicated that agriculture, crop land dominated the land use of Churu district while natural vegetation (forest areas) had the least share in land cover during the entire study period from 1998 to 2018. Shannon’s entropy index was used to determine the changes in spatial distributional pattern of built up during the period 1998 to 2018 for the study area in general and also for each of the eight sub-administrative regions (tehsils). The increase in the built up area in the study area during the period of 1998 to 2018 was quite paltry with a general dispersed type of built up. The increase varied from moderate to nominal with the entropy value decreasing from 0.84 to 0.71 for the study area in general.