Aim: The aim is to analyze spatio-temporal LULC changes in Miandoab County, Iran (2013-2024) and predict transformations to 2054 using the CA-Markov model. This research provides a scientific basis for sustainable land management by addressing the impacts of rapid urbanization and climate pressures on the region’s environmental balance.
Material & Method: Landsat 8 imagery was classified using the Maximum Likelihood Classification (MLC) algorithm. For future prediction, a CA-Markov model was employed, which was refined by cropping agricultural zones and merging classes (e.g., roads and buildings) to improve accuracy. The model's final predictive performance was validated as acceptable with a Kappa coefficient of 0.5474.
Finding: Over the past decade, farms and built-up areas grew significantly, while gardens, soil, and water resources sharply declined. Projections for 2054 show an intensification of this trend, with farm areas increasing by approximately 1097 ha and built-up areas by 550 ha. This expansion is predicted to occur mainly at the expense of over 1063 ha of gardens and 555 ha of soil, signifying a structural shift from perennial horticulture to seasonal farming.
Conclusion: Land use change in Miandoab reflects a critical imbalance between human development and the region's ecological capacity. The current trajectory threatens local sustainability with serious risks, including biodiversity loss, soil erosion, and increased water stress. This necessitates urgent and informed policy interventions to mitigate environmental degradation. It is suggested that in future research, with the aim of increasing the realism of the model
Innovation: In this research, land use was generated using Landsat satellite images with very high accuracy, and the CA-Markov model and satellite image processing were combined to provide a quantitative and spatial perspective of the future. Its results can be used as a decision-making tool for planners, natural resource managers, and executive institutions to formulate conservation and sustainable development policies.