Integrating the CA-Markov model and geospatial techniques for spatiotemporal prediction of land use/land cover dynamics in Qus District, Egypt

Land use land cover (LULC) is the primary driving force behind environmental change. These changes significantly impact ecosystem functions, disrupt natural landscape, and lead to serious consequences such as environmental degradation, economic loss, declining quality of life and well-being, and social instability. To maintain and safeguard land resources, it is crucial to monitor and predict changes in LULC. This is essential for addressing environmental challenges and guiding sustainable development. To support this objective, this study applies a hybrid CA-Markov model, supported by remote sensing and GIS techniques, to assess spatiotemporal LULC dynamics in Qus district, Egypt, from 2000 to 2020 and to forecast changes through 2040. Landsat imagery and ancillary datasets were classified using a supervised maximum likelihood classifier, achieving high accuracy levels (> 89%) and Kappa coefficients exceeding 0.84. Significant expansions were observed in built-up areas (+ 6%, with an annual change rate of 85.9 ha/year) and agricultural land (0.2% increase with an annual rate of 1.9 ha/year). In contrast, barren land and water bodies have declined by 6% and 0.2%, respectively. Validation of the CA-Markov model against actual 2020 data demonstrated strong agreement (Kappa > 86%), confirming the model's robustness and reliability. Predictions for 2040 indicate continued urban and agricultural expansion, primarily at the expense of barren land. These findings provide critical and valuable insights for land use planning and policymaking, particularly in arid regions.