Analysis of urban development on land cover changes of three cities of Gujarat state, India

Urbanization generally serves as a key navigator of the economic growth and development country. There is need for fast accurate urban planning to accommodate more people in city area. Remote sensing technology has been used expansion design areas. A novel machine learning (ML) classifier formed by combining AdaBoost extra trees algorithm have investigated change detection area three cities Gujarat region India. Using Indian Sensing (IRS) Resourcesat-2 LISS IV satellite images, performance object-based AdaBoosted (ABETC) terms overall accuracy (OA) kappa coefficient (KC) was compared benchmarked algorithms. As first step classification (OBC), Shepherd segmentation segment images. For all cities, ABETC demonstrated highest efficiency when conventional classifiers. The rise built-up Ahmedabad noted 87.39 sq km from year 2011 2020 showing city. This increase compensated depletion 30.26 sq. km. vegetation area, 57.13 open land class. Vadodara Rajkot enlarged 17.24 6.79 respectively. OA 96.04% KC 0.94 image with object based algorithm.