OBTAINING AND EVALUATION OF LAND SURFACE TEMPERATURE USING CLOUD-BASED APPLICATIONS: THE CASE OF ANKARA PROVINCE

Abstract

Rapid urban expansion, characterized by high land surface temperatures (LST) in urban areas, has led to environmental and health concerns along with increased energy consumption. Recent advances in remote sensing have facilitated the investigation of spatiotemporal LST patterns and their relationships with factors such as vegetation, built-up land, and soil moisture. However, a limited number of studies investigate whether these relationships differ between urban and rural areas. Leveraging the power of cloud computing resources such as Google Earth Engine (GEE) and Microsoft Azure, researchers can now examine these issues on a larger scale and over a longer period. Focusing on Ankara, the capital city known for its recent urban growth, we specifically calculated the annual average and seasonal average LST at the grid level, performed urban-rural slope analysis, examined the relationship between LST and vegetation and built-up land in urban and rural areas separately, and analyzed how LST relates to land cover types in Ankara. Using GEE for geographic spatial analysis, the study sheds light on critical issues such as the relationship between LST and various land cover types. By providing valuable insights into seasonal LST variations in various areas, the study investigates how LST relates to land characteristics in urban and rural areas and aims to assist in sustainable urban planning.