Spatio-temporal simulation of future urban growth trends using an integrated CA-Markov model

Urban growth, a dynamic and demographic phenomenon, refers to the increased spatial value of urban areas, such as cities towns, due social economic forces. Nowadays, lands are rapidly increasing, replacing non-urban agricultural, forest, water, rural, open lands. In this study, CA-Markov model was utilized predict growth their trends in Seremban, Malaysia. The performance also assessed. Markov chain applied produce quantitative values transition probabilities for Subsequently, CA used land changes. change use from 1984 2010 modeled using calibration purposes compute optimal rules, well future growth. For accuracy assessment, validated kappa coefficient. An 83% overall observed index statistics, which indicates excellent proposed model. Finally, based on rules area matrix produced model-based process, Seremban 2020 2030 simulated.