Analyzing and Predicting Land Use and Land Cover Changes with an Integrated CA-Markov Model: A Spatiotemporal Perspective in Case of Chuko Town and Surroundings, Sidama Region, Ethiopia
Abstract
Land use and land cover changes fundamentally shape global environmental and societal dynamics. The study uses an integrated CA-Markov Model to analyze and predict the land use and cover changes from 2003 to 2023 in Chuko Town and its surroundings. LULC maps were extracted from Landsat 5, Landsat 7, and Landsat 8 data and the CA-Markov model simulated the LULC for 2043. The findings reveal a significant expansion of the built-up area, increasing from 243.18 hectares in 2003 to 356.60 hectares in 2013 and further to 982.33 hectares by 2023. In contrast, the bare land decreased from 426.74 hectares in 2003 to 388.86 hectares in 2013 and 280.26 hectares in 2023. However, the vegetation category remained relatively stable, with areas of 2241.81 hectares, 2221.58 hectares, and 2085.53 hectares in 2003, 2013, and 2023, respectively. The validation model for 2023 showed an overall KIA value of 0.8, indicating reasonable prediction accuracy. Looking ahead to 2023-2043, the built-up area is projected to increase by 721.81 hectares, while the areas of bare land, agriculture, and vegetation are predicted to decrease by 182.03 hectares, 386.29 hectares, and 153.49 hectares, respectively. This projection suggests reducing vegetation, agriculture, and bare land areas by 2043. Thus, understanding historical and simulated LULC changes is invaluable for decision-makers and urban planners to formulate effective policies and strategies to address urban growth, make informed decisions, and promote sustainable city development.
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