Modeling Vegetation Cover Maps Affecting Land Surface Temperature in Erbil City Using Remote Sensing

This study aims to monitor and analyze vegetation cover and its impact on land surface temperature (LST) in Erbil City over the period 1990–2023. The research utilizes JavaScript programming within the Google Earth Engine (GEE) platform to acquire satellite imagery for both vegetation cover (NDVI) and LST. Extracted temperature data were classified using internationally recognized standards and further processed within a Geographic Information System (GIS) environment. Advanced cartographic modeling techniques were applied to generate LST classification maps throughout the study period.The results reveal a significant rise in land surface temperatures across Erbil City. Warm zones accounted for 34.8% of the total area, hot zones covered 37.6%, and very hot zones made up 27.7%. These findings underscore the substantial impact of rising temperatures on the urban environment and overall quality of life, highlighting the urgent need for sustainable environmental planning and urban heat mitigation strategies.