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Changes in land use can significantly impact natural resource sustainability, socioeconomic activities, and flood risks. Cellular Automata-Markov model (CA-Markov) is utilized in this study to predict land use changes by modeling the spatial dynamics and transitions of land use categories over time in one of the flood-prone area in Segamat district, Johor. Satellite images obtained from Landsat 5 Thematic Mapper and Satellite Pour I’Observation de la Terre (SPOT) 5, 6, and 7 for years 2006, 2011, and 2016 were utilized to assess the magnitude of the land use change via unsupervised and supervised classification. Additionally, ancillary data such as residential, road, water bodies, and slopes were used as input to forecast future land use. The findings revealed that between 2006 to 2026, there was an increase in built-up areas and mixed agriculture up to 26%. The expansion of built-up areas and mixed agricultures involves the removal of forests, further exacerbating flood risks. This fundamental research can provide valuable insights for effective land management and urban planning.
Mohamad et al. (Sun,) studied this question.