Forecasting urban territorial expansion using GIS and artificial intelligence technologies

This study presents an innovative approach using modern GIS and artificial intelligence technologies to predict the future territorial expansion of Samarkand city. Using Landsat satellite imagery, land use and land cover (LULC) images were created using ArcGIS software. These images were input into a ConvLSTM model, allowing for the prediction of urban expansion trends. Additionally, a U-Net model was applied to accurately identify and monitor urban boundaries. The research results showed uneven expansion of Samarkand city, which is crucial in the decision-making process for urban planning and management. The obtained data can serve as a valuable resource in developing urban policies, infrastructure development, and addressing environmental issues related to urban expansion. This methodology can be applied not only to Samarkand but also to other rapidly growing cities, contributing to sustainable urban development.

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