||You Know The Temperature at the Weather Station But Do You Know It Anywhere Else? Assessing Land Surface Temperature Using Landsat ETM+ Data
||J. R. Otukei, T. Blaschke
||Landsat ETM+, Land Surface Temperature, Apparent Reflectance and FLAASH Models
||Land Surface Temperature (LST) is one of the important parameters affecting climate change. This study investigated the potential of Landsat ETM+ low and high Thermal InfraRed (TIR) bands for assessing the LST in Kampala, Mukono and Jinja Districts. Data analysis was carried out using the Apparent Reflectance (AR) and FLAASH models. The LST estimates derived from the TIR bands was validated using available ground truth data. The analysis of low gain TIR band using the AR model provided the lowest error of 0.71oC. Furthermore, areas with high green vegetation cover were found to have low LST and high emissivity values. In Contrast, bare ground and urban areas had low emissivity and high LST. Overall, Landsat ETM+ TIR bands provide a high potential for assessing LST at local scales. The results obtained are not only of high accuracy but also provides spatial distribution of LST at local scales, which is not possible with traditional methods.
||The first Conference on Advances in Geomatics Research (2011)