Abstract:
The Modelling and Simulation of land cover change are fundamental to the evaluation of successive environmental effects. In modelling several factors that are interacting with each other at the local or micro level in a non-linear way. In this research, an attempt has been made to predict urban growth by using the
cellular automata- Markov model to predict the urban growth of Rohtak city. Rohtak is one of the 8 priority towns of the NCR region, and it lies 70 km from Delhi. The method applied for this research consists of the following steps. Started with the collection of remote sensing data from 1985 to 2022 and supervised
classification was performed. From analysis, aerial increase and direction of growth were determined. The change analysis on Terrset Geospatial Monitoring and Modelling system gain and losses from 1995 to 2021 was calculated. Map transition from the vegetation to built up, barren to built up and water to built maps
were created. From literature parameters such as distance from CBD, distance from roads, distance from the district centre, population density and environmental factors were selected. These are variable parameters with the static role and their Euclidean distance was created on maps. Run the transition sub-model with 4
hidden and with 15,000 iterations. As a result, generation map transition potential was created. A probability matrix with built-up, water, vegetation and barren land according to their weightage. Markov model used on these transition potential maps and prediction map with defined years can be created. As an outcome, we
get projected transition potential and projected land cover. Validation is done with a comparison with the previous map and false positives were determined. From the analysis, we get vegetation is changing to built up at a rapid pace and need attention so that environment can be conserved.
