Predicting the Changes in National Parks Due to Urbanization Growth, Applying the CA_Markov Model Approach: Bamou National Park Case Study—Fars Province—Iran

ABSTRACT National parks have a great role in ecosystems. They provide many natural benefits for different types of animal species. The research underscores the importance of understanding urbanization's effects on protected areas to inform conservation efforts. To predict land use changes in Bamou National Park, data from the TM, ETM+, and OLI sensors for the years 1986, 1996, 2006, and 2016 were classified using the Random Forest method. After validating the model's accuracy, land use simulations were carried out for the year 2050. Mathematical formulation of the CA‐Markov model was developed, including transition probability matrices and cellular automata rules. The CA‐Markov model indicated an expected increase in construction and agricultural areas by 2050. A significant reduction in the area of pastures was also observed, which could lead to the disappearance of water resources. The transition probability matrix showed robust calibration with historical data, validated through sensitivity analysis. This study highlights the importance of using predictive models like CA‐Markov for better management of urban development and ecosystem conservation. Based on the findings, specific policy recommendations are proposed for protected area management, including zoning regulations, buffer zone establishment, and sustainable urban planning measures. The findings of this research can assist policymakers in making more informed decisions to mitigate the negative impacts of urbanization on the environment.