Urban Expansion Changes on Agricultural Lands Using the GLASOD Approach: A Case Study of Al Bustan 1 and 2, West Nile Delta, Egypt

The use of modern technologies such as remote sensing and geographic information systems, along with the availability of ground information and satellite images with a spatial resolution of up to 10 meters, has become essential for the success of land use estimation studies and crop area estimation in both the winter and summer seasons. However, the accuracy of the results obtained using various satellite image interpretation methods must be taken into account. In this research, artificial intelligence was used to identify areas affected by urban expansion in the study area and compare them with the urban areas extracted from Google Earth Pro platforms (GEP). Finally, the GLASOD approach was applied to determine the state of deterioration based on the precise building areas and their rate of expansion after linking the physiographic mapping units, starting from 1985 to 2025, with five-year periods (1985-1990, 1990-1995, 1995-2000, 2000-2005, 2005-2010, 2010-2015, 2015-2020, and finally 2020-2025). The results showed that the urban areas classified using the artificial intelligence method were higher than the areas calculated using the visual interpretation method, with a gradual increase during the period from 1985 to 2010, and a significant increase in the last three years from 2015 to 2025. The results of applying the GLASOD model to determine the type, degree, and extent of the impact of urban expansion on agricultural soils, and to arrive at the overall severity of degradation, showed a significant impact of urban expansion on agricultural areas, starting from the period 2005-2010 and continuing through the period 2020-2025 After discussing the results obtained using these modern techniques, we highlighted all these observations, which prompted us to search for platforms that provide multi-date satellite images with high spatial resolution, and the World View program to conduct visual interpretive analysis of the study areas in the future.