ASSESSING LAND SURFACE TEMPERATURE IN URBAN AREAS USING OPEN-SOURCE GEOSPATIAL TOOLS

Abstract

Land surface temperature (LST) in urban areas can be traditionally observed by thermal remote sensors. The increasing availability of 3D city models provides an alternative approach based on geospatial modeling. Using solar radiation tools and scripting in GRASS GIS, we have developed a physically-based LST model that can be used to estimate LST in urban areas represented by vector 3D city models. It uses standard input parameters such as solar irradiance, albedo or convection heat transfer coefficient for urban surfaces. The solar irradiance is estimated using the v.sun solar radiation add-on module in GRASS GIS. The LST values are calculated using map algebra operations using a Python script. The suggested methodology was applied to the study area in the city of Košice, Slovakia. Results indicate that urban morphology has a strong impact on spatial distribution of LST during the daylight hours. The accurate parameterization of urban surfaces can increase the accuracy of the model that can be used for urban planning, optimization of energy use in buildings or mitigation of urban heat island effects.