Modeling and Predicting Urban Expansion with Its Impact on Land Surface Temperature Using Remote Sensing and Random Forest in Al-Zubair District Center, Iraq

Abstract

Urban expansion is a dynamic process of increasing the geographical area of cities, districts and constitutes a significant focus in modern studies, as urban lifestyles have become increasingly prevalent worldwide. There is a flaw in the temporal and spatial distribution of urban expansion trends that requires a comprehensive analysis and study of its impact on the Earth's surface temperature in the center of Al-Zubair district ,one of the most important Towns in Al-Basra Governorate, which is witnessing an increase in urban sprawl. Urban expansion and its relationship with environmental factors have become an important focus of many recent studies. The study relied on Landsat 8 satellite data from 2015-2025 to calculate the Land Surface Temperature Index (LSTI), the Built-up Area Standard Difference Index (NDBI), the Built-up Area Index (BUI), the Urban Heat Island Index (UHIS), and the Modified Water Standard Difference Index (MNDWI), using Remote Sensing and Geographic Information Systems (GIS) techniques. In addition to creating future predictions for the year (2050) using machine learning techniques, specifically the random forest algorithm. The results indicate a direct relationship between urban expansion and (UHIS) , and an inverse relationship with water bodies during the observed period. The study area witnessed a gradual increase in average surface temperature and a real increase in urbanized area of 6.11% over 10 years. (UHIS) developed by 14.34%, particularly in the northeastern and northwestern parts of the study area, while the area of water bodies decreased by 10.5%. Future predictionsindicate that approximately 48% of AL-Zubair district center will be converted to built-up areas over the next 25 years, further increasing (UHIS).