Simulation of land use/land cover change at a basin scale using satellite data and markov chain model

Abstract

The aim of the study is to analyze the past and future land use and land cover change (LULCC) in Betwa River Basin (BRB), central India. The LULC maps were derived from Landsat satellite images using Maximum Likelihood Classifier (MLC). The artificial neural network (ANN) embedded with Land Change Modeler (LCM) was trained with driver variables. The model prediction accuracy has been accessed by evaluating Receiver Operating Characteristic (ROC) values. The study reveals that during the period 1990-2020 agriculture land, open forest, and built-up land area have increased significantly. Further, the LULCC prediction for the period 2030-2050 suggests that expansion in open forest and the built-up land area will continue while agriculture land area will keep back in the future. This research provides up-to-date LULCC information of BRB, which would be useful for all the stakeholders governing river basin management and land resource planning in this region.