Monitoring and Predicting Land Use Dynamics in Djelfa City, Algeria with Google Earth Engine and Markov Chain Model

Description

Monitoring and Predicting Land Use Dynamics in Djelfa City, Algeria with Google Earth Engine and Markov Chain Model delves into the transformative changes in Djelfa from 1990 to 2020 through advanced GIS technologies. By utilizing Landsat imagery and the Support Vector Machine (SVM) technique for land use and land cover (LULC) classification, this study achieves over 90% accuracy in mapping urban changes. The research highlights a dramatic 75.6% increase in population and a shift from large extended families to smaller nuclear households, reflecting a significant socio-spatial transformation. The application of Markov Chain and Multi-Layer Perceptron models projects continued urban expansion, predicting growth from 924.09 hectares in 1990 to 2742.30 hectares by 2020, with an anticipated 1.6% of non-urban areas becoming urban by 2035. This work stresses the need for adaptive urban planning and policy adjustments to address these shifts, providing a comprehensive analysis that supports sustainable urban development strategies. It serves as a crucial resource for policymakers, urban planners and researchers interested in understanding and managing urban dynamics in Algeria and beyond.