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Abstract
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Desertification involves processes that arise from both natural factors and human mismanagement. Therefore, it is essential
to develop effective strategies for the quantitative assessment of desertification. In this study, the desertification status of
the region under investigation was first examined using the MEDALUS model. Based on the results obtained from this
model and a review of studies conducted by other researchers, seven remote sensing indices were selected for modeling.
The methods SVM, GBM, GLM, and RF were employed to model desertification risk in Central Iran (Isfahan Province).
Ultimately, to provide a comprehensive model, a weighted average of the four models was utilized in the SDM statistical package for modeling and predicting desertification. According to the results from the MEDALUS model, the most
significant factors contributing to desertification in the study area were identified as management and policy criteria (score
1.61), vegetation (1.51), erosion (score 1.48), climate (1.34), and soil (score 1.26). Additionally, 41% of the area falls into
the low and negligible desertification class, 3% into the moderate class, 18% into the severe class, and finally, 38% into
the very severe desertification class. Statistical indicators revealed that in 2009, the SVM model performed better than
other models with an AUC of 0.81, TSS of 0.86, and Kappa of 0.89; while in 2023, the RF model outperformed others
with an AUC of 0.83, TSS of 0.7, and Kappa of 0.87. The results from the ensemble model indicate an increasing trend
of desertification in eastern Isfahan Province. By examining the changes in desertification from 2009 to 2023, three key
areas for desertification expansion were identified: Gavkhuni Wetland (southeast), Sagzi Plain (central), and Rig-e Boland
Desert (north and northeast). Therefore, based on the results from the ensemble model as a comprehensive framework with
minimal uncertainty, appropriate planning, optimal management, and corrective measures can be employed in affected
areas to prevent further desertification processes.
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