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<p>This study investigates the temporal dynamics of Land Surface Temperature (LST) in Hawassa City Administration, Ethiopia, using thermal remote sensing data. Satellite imagery from Landsat-7 ETM+ (22 March 2002) and Landsat-8 OLI/TIRS (22 March 2019) was analyzed to assess changes in LST over a 17-year period. The classification accuracy of the satellite-derived land use/land cover (LULC) maps was assessed using overall accuracy and the Kappa coefficient. The results indicate a high level of reliability, with an overall accuracy of 91.1%. Class-specific accuracies were 85.0% for built-up areas, 90.5% for agricultural land, 91.7% for vegetation, and 96.0% for open/barren land. The Normalized Difference Vegetation Index (NDVI) was derived from the red and near-infrared bands to estimate surface emissivity, while LST was retrieved from the thermal infrared bands using a single-channel algorithm and validated against MODIS LST products. Land-use/land-cover (LULC) maps were generated using an on-screen classification approach to evaluate the influence of LULC transitions on thermal patterns. The results indicate that in 2002, LST ranged from 6.62&#xa0;°C to 22.54&#xa0;°C (mean = 14.58&#xa0;°C; SD = 11.25), while in 2019, LST increased substantially to 11.97–35.5&#xa0;°C (mean = 23.74&#xa0;°C; SD = 16.64). Higher LST values were consistently associated with built-up areas, roads, barren, and open lands, whereas lower LST values corresponded to vegetation-rich zones such as forests, croplands, shrubs, and grasslands. The increase in LST over time is largely attributed to urban expansion, loss of vegetation due to deforestation, and the spread of impervious surfaces. The findings highlight the urgent need for urban greening strategies, including expanding evergreen tree cover, developing city parks, restoring degraded green spaces, and integrating green infrastructure into urban planning to mitigate rising surface temperatures and improve urban thermal comfort. This study underscores the effectiveness of geospatial technologies for LST monitoring and supports climate-responsive land-use management in rapidly growing cities.</p>

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Thermal Remote Sensing: A tool to Determine Temporal Land Surface Temperature in Hawassa City, Ethiopia

  • 期刊论文

  • 发表日期：

    2026年7月3日

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  • Mikias Biazen Molla,
  • Kamran Jafarpour Ghalehteimouri

摘要

This study investigates the temporal dynamics of Land Surface Temperature (LST) in Hawassa City Administration, Ethiopia, using thermal remote sensing data. Satellite imagery from Landsat-7 ETM+ (22 March 2002) and Landsat-8 OLI/TIRS (22 March 2019) was analyzed to assess changes in LST over a 17-year period. The classification accuracy of the satellite-derived land use/land cover (LULC) maps was assessed using overall accuracy and the Kappa coefficient. The results indicate a high level of reliability, with an overall accuracy of 91.1%. Class-specific accuracies were 85.0% for built-up areas, 90.5% for agricultural land, 91.7% for vegetation, and 96.0% for open/barren land. The Normalized Difference Vegetation Index (NDVI) was derived from the red and near-infrared bands to estimate surface emissivity, while LST was retrieved from the thermal infrared bands using a single-channel algorithm and validated against MODIS LST products. Land-use/land-cover (LULC) maps were generated using an on-screen classification approach to evaluate the influence of LULC transitions on thermal patterns. The results indicate that in 2002, LST ranged from 6.62 °C to 22.54 °C (mean = 14.58 °C; SD = 11.25), while in 2019, LST increased substantially to 11.97–35.5 °C (mean = 23.74 °C; SD = 16.64). Higher LST values were consistently associated with built-up areas, roads, barren, and open lands, whereas lower LST values corresponded to vegetation-rich zones such as forests, croplands, shrubs, and grasslands. The increase in LST over time is largely attributed to urban expansion, loss of vegetation due to deforestation, and the spread of impervious surfaces. The findings highlight the urgent need for urban greening strategies, including expanding evergreen tree cover, developing city parks, restoring degraded green spaces, and integrating green infrastructure into urban planning to mitigate rising surface temperatures and improve urban thermal comfort. This study underscores the effectiveness of geospatial technologies for LST monitoring and supports climate-responsive land-use management in rapidly growing cities.