Prediction and Modeling of Land Cover Changes in Qom Province Using Landsat Satellite Imagery
Subject Areas : Natural resources and environmental management
1 - عضو هیئت علمی دانشگاه امام حسین
2 - Remote Sensing and GIS devision
Keywords: Modeling, Land Cover Changes, Prediction, Markov Chain,
Abstract :
Modeling and predicting land cover changes are essential for sustainable land use planning. This study aims to model land cover changes in Qom Province using Landsat satellite imagery from 2015 to 2023 and to predict changes up to 2027. For this purpose, the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI) were employed, along with the Support Vector Machine (SVM) classification method. Additionally, a combination of the Markov Chain model and Cellular Automata was utilized to simulate historical land cover change trends from 2015 to 2023 and to predict future changes for 2027. The results indicate that vegetation cover returned to its 2015 state after 2019, while urban growth has continued to increase steadily. The predictions suggest an expansion of 2,700 square meters in urban areas by 2027. These findings can support improved decision-making in natural resource management, urban infrastructure development, and efforts to achieve regional sustainable development. Moreover, the research outcomes provide a valuable tool for future planning.
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