Modeling Land Surface Temperature (LST) and Surface Urban Heat Islands (SUHI) in Taguig City (Philippines) using Material Distribution Derived from Linear Spectral Unmixing of PRISMA Hyperspectral Data

Abstract. As one of the world’s fastest developing countries, urbanization in the Philippines occurs at a rapid pace – however, this process has been well established to exhibit negative climatic impacts. This study uses linear spectral unmixing (LSU) of a PRISMA hyperspectral image alongside land surface temperature (LST) data to establish the relationship between material abundance and LST, quantify said relationship through correlation analysis, and identify how materials contribute to surface temperature. Material fraction maps derived from PRISMA were validated using high-resolution PlanetScope imagery, yielding strong agreement for vegetation and built-up areas (R^2 = 0.8420 and 0.9007, respectively). Correlation analysis revealed that vegetation (r = -0.7808 and -0.7794) had strong negative correlations while impervious surfaces, particularly galvanized iron (GI) sheets (r = 0.7260 and 0.7229), exhibited positive correlations with LST and UTFVI calculated using Landsat thermal image. Multilinear regression further quantified these relationships showing that the presence of vegetation and GI sheets produced a strong cooling and warming effect, respectively, on LST; it also identified GI sheets as the most thermally impactful material. These findings demonstrate the effectiveness of combining hyperspectral and thermal remote sensing for UHI analysis and emphasize the need to consider material-specific thermal behavior in planning and building tropical urban environments.