Assessing the effects of vegetation change on urban land surface temperature using remote sensing data: The case of Addis Ababa city, Ethiopia

Abstract

Land Surface Temperature (LST) plays an essential role in regulating the temperature and surface processes of land features. Advancement in remote sensing has paved the way for the use of satellite data to estimate land surface temperature. The objective of this study was to estimate changes in vegetation and LST from Landsat TM (Thematic Mapper) of 1985 and Landsat 8 OLI (Operational Land Imager) of 2015 for Addis Ababa City, Ethiopia. Land use/land cover classification using supervised image classification and the maximum likelihood algorithm method was applied to study changes in land use/land cover from 1985 to 2015. Brightness temperature, Land Surface Emissivity (LSE) and Normalized Difference Vegetation Index (NDVI) were computed to estimate land surface temperature. The result of the study showed a reduction of vegetation cover and rapid expansion of built-up area against grazing lands and other land use classes from 1985 to 2015. The area of built-up has increased from 18.23% in 1985 to 33.86% in 2015. In the centre of the city and areas with low vegetation cover, land surface temperature has shown an increase of 3–8 °C from 1985 to 2015. Correlation analysis showed a negative correlation between NDVI and land surface temperature in all sub-cities of Addis Ababa. The findings of this study could support the designing of suitable strategies to mitigate urban heat stress.