Simulating Urban Growth Using the Cellular Automata Markov Chain Model in the Context of Spatiotemporal Influences for Salem and Its Peripherals, India

Urbanization is one of the biggest challenges for developing countries, and predicting urban growth can help planners policymakers understand how spatial patterns interact. A study was conducted to investigate spatiotemporal dynamics land use/land cover changes in Salem its surrounding communities from 2001 2020 simulate expansion 2030 using cellular automata (CA)–Markov geospatial techniques. The findings showed a decrease aerial vegetation an increase barren built-up land, with rapid transition bare land. transformed expected be converted into near future. Urban area estimated 179.6 sq km 2030, up 59.6 2001, 76 2011, 133.3 2020. sprawl steadily increasing towns Omalur, Rasipuram, Sankari, Vazhapadi, neighboring surpassing that directions aligned toward Salem. city being developed as smart city, which will result significant intensification coming years. study’s outcomes serve guidelines regulation monitoring.