Application of an Integrated CA-Markov Model in Simulating Spatiotemporal Changes in Forest Cover: A Case Study of Malekshahi County Forests, Ilam Province

In order to optimize the planning and management of natural resources and the environment, it is essential to know the status of land cover changes over the past decades. Modeling land cover change can provide valuable information for better understanding of this process, determining of effective factors and forecasting of regions subject to change. This study aimed to determine and simulate the distribution and amount of reduced forest cover changes in Malekshahi County in Ilam province using Fusion CA-Markov model during the years 1976 to 2010. To simulate forest cover changes, Landsat MSS of 1976 and LISSIII of 2007 and 2010 images were processed and classified. To investigate the relationship between forest cover changes and human and environmental factors and land conversion utility maps, the logistic regression method was used. Then the land cover and land use map in 2021 was simulated using a combined model of Markov chain and automated cells based on observed changes between 1976 to 2010. To validate the model, simulation maps of forest cover in 2010 were created using CA-Markov model and classified images of 1976 to 2007 years. Comparison of simulated maps with real map from 2010 showing the high capability of classifying these models to simulate forest cover changes in Zagros forests (kappa index = 0.83). The results of the model indicate significant reductions in Malekshahi county forest resources.