Examination of the Relationship Between Surface Temperature and Spectral Land Cover Indices for Different Köppen Climate Classes

Abstract. Land Surface Temperature (LST) serves as a critical parameter for evaluating urban climate dynamics and surface energy exchanges. This study examines the relationships between LST and four spectral land cover indices—Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Water Index (NDWI), and Normalized Difference Bareness Index (NDBaI)—across four Köppen–Geiger climate zones: Kars (Dfb – Humid Continental), Kilis (Csa – Hot-Summer Mediterranean), Cairo (BWh – Hot Desert), and Malanje (Aw – Tropical Savanna). Using Landsat 8 OLI/TIRS Collection 2 Level-2 imagery acquired in September 2023 (and 2020 for Kars), LST and spectral indices were extracted and analyzed through pixel-based Pearson correlation analysis. The results revealed diverse climatic dependence in the LST–index interactions. In Kars, LST showed a strong positive correlation with NDBI (r = 0.63) and a moderate correlation with NDBaI (r = 0.39). In Kilis, NDVI exhibited a moderate negative relationship with LST (r = −0.47), while NDBI correlated weakly (r = 0.22). Cairo displayed weak overall relationships, with LST–NDBI (r = 0.38) and LST–NDVI (r = −0.22) reflecting the dominance of impervious and arid surfaces. Conversely, Malanje demonstrated the strongest vegetation–temperature interaction, where LST–NDVI correlation reached r = −0.75, LST–NDWI r = 0.72, and LST–NDBI r = 0.53. Across all cities, built-up and bare areas consistently increased LST, while vegetation showed cooling effects that intensified in warmer, more humid climates. These findings highlight that the magnitude and direction of LST–land cover correlations are strongly controlled by regional climate regimes, emphasizing the necessity of climate-specific urban heat mitigation strategies.