Satellite Based Estimation of Urban Surface Emissivity with the Use of Sub-Pixel Classification Techniques

Abstract

Information about the spatial distribution of urban surface emissivity is essential for surface temperature estimation which is an important component of urban microclimate and it is critical in many applications, like turbulent sensible and latent heat fluxes estimation, energy budget, urban canopy modeling, bio-climatic studies and urban planning. The proposed method presents an improvement in emissivity estimation as compared with existing methods, such as the look-up table approach, wherein emissivity and other biophysical parameters are assigned to grid cells based on land cover types. The basic premise of this method is a sub-pixel classification of urban surface into vegetation, impervious and soil, based on spectral mixture analysis. The proposed approach was applied to Landsat-7 ETM + observations over the area of Athens, Greece. Spatial distributions of surface emissivity, as well as land surface temperature in the spectral region of 10.4–12.5 μm were derived. ASTER (Advanced Spectral Reflection and Emission Radiometer) emissivity and surface temperature products were used for evaluation.