Land Surface Temperature (LST) has emerged as a critical environmental parameter globally due to its profound impact on urban microclimates. To mitigate urban heat islands, it is crucial to use advanced geospatial techniques to map and analyze vegetation and land surface temperature for informed urban planning decisions. The main objective of this study was to examine the relationship between land surface temperature (LST) and vegetation cover in Hawassa City, employing GIS and remote sensing techniques to inform strategies for mitigating the urban heat island effect. Three different satellite datasets of Landsat 5 TM (1991), Landsat 7 ETM + (2005), and Landsat 8 OLI (2021) were employed. LST were computed from these thermal bands of datasets using mono-window algorithms. Regression and correlation analyses were conducted among LST, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI). The results of the land cover change analysis indicate that between 1991 and 2021, dense and sparse vegetation cover declined by 1.6% and 19.3%, respectively, while built-up areas increased substantially by 23.2%. This reflects rapid urban expansion at the expense of vegetated areas. A consistent decline in urban vegetation relative to built-up areas over the three decades, contributing significantly to the increase in LST. Furthermore, the analysis revealed a negative correlation between Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI), and a positive correlation with the Normalized Difference Built-up Index (NDBI), indicating that NDBI is a more effective predictor of LST than NDVI. Increasing urban green spaces and water bodies was shown to effectively reduce temperatures, with water bodies contributing to a decrease in maximum temperatures by 2.1 °C in 1991, 1.2 °C in 2005, and 0.5 °C in 2021. Therefore, expanding urban green infrastructure and rehabilitating vacant lands are vital strategies for mitigating urban heat island effects and promoting sustainable, climate-resilient development in Hawassa City

Land surface temperature (LST) is becoming a serious environmental issue, since it is an essential controller of city climate. Currently, addressing this challenge in urban planning has gained worldwide importance. The study aims to analyze the effect of land cover dynamics on LST using geographic information system and remote sensing techniques. In this study, Landsat 7 ETM+ (2002) and Landsat 8 TIRS (2022) data were used. The LST was retrieved from Landsat datasets. The correlation analyses were conducted on LST, normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI). The findings suggested that there was a negative correlation between LST and the NDVI, while a positive correlation existed with the NDBI. Moreover, NDBI was found to be a better predictor of LST than NDVI. Additionally, it was revealed that the proportion of dense and sparse vegetation cover was reduced from 24.14 km2 (17.47%) in 2002 to 18.17 km2 (13.15%) in 2022. Similarly, the average LST increased from 28.25 to 31.78°C. This indicated that the rapid growth of urban development was the primary factor behind the rise in LST. Therefore, it was deemed crucial to create a smart urban land use plan to mitigate the impacts of microclimate change.