Monitoring and Prediction of Urban Expansion and Land Use Change Using An Integrated Markov Chain and Cellular Automata: A Case Study of Freetown City, Sierra Leone
In this study, land-cover change in Freetown city was simulated using the integrated Cellular Automata and Markov model (CA-Markov) within the Geographic Information System (GIS) and Remote Sensing (RS). Firstly, area changes and spatial distribution of land used in the town were analyzed and calculated between the time span of 2000–2018. Secondly, the transition matrix and spatial distribution of urban land use in 2026 were simulated, the changes were predicted and possible growth patterns were identified as well.The results showed a declining trend of4.21% in dense vegetation,7.54% in Freetown sparse vegetation and 10.92 % in barren land, and also an increasing trend of 22.99% in urban areas for a time span2000 to 2026. Major expansions in urban areas were witnessed aroundnorthwestern western urban and northeastern borders of the city. This study provides an opportunity to define and apply better strategies for environmental management of land use to make an optimized balance between urban development and ecological protection of environmental resources.
Keywords: CA–Markov, GIS, Land use change, Urban growth