Refining the Urban Thermal Landscape: Insights from Corrected Emissivity over Indigenous Roof Materials

What are the main findings? Standard emissivity algorithms are inaccurate over low-emissivity surfaces such as metal roofs. Applying actual emissivity values for metal roofs in Land Surface Tempera-ture (LST) retrieval yields significantly higher land surface temperature esti-mates. What is the implication of the main finding? Landsat and ECOSTRESS LST products for indigenous cities with extensive metallic roofing appear misleadingly low. There is a need to adjust satellite LST algorithms to properly account for metal roof emissivity. Highlights: The increased reliance on thermal satellite images for urban climatic analysis requires robust temperature retrievals for urban surfaces. As the emissivity of any surface type determines the amount of thermal radiation received by a sensor, accurate emissivity values of reflecting surfaces are important in Land Surface Temperature (LST) computations. It is known that the commonly used Temperature Emissivity Separation (TES) algorithm is inaccurate over low-emissivity surfaces such as desert sand and metallic surfaces. However, in indigenous cities, much of the satellite ‘seen’ surface consists of metallic roofing materials like corrugated iron or aluminum. This study uses 853 ECOSTRESS images to examine the diurnal and seasonal pattern of LST for five indigenous cities in sub-Saharan Africa. Surface Urban Cool Islands (SUCIs) were observed in all five cities during both summer and winter, which were more pronounced during daytime than at night. This conflicts with air temperature data and published reports, as well as the dominant low-rise urban morphology, which would suggest the occurrence of Surface Urban Heat Islands (SUHIs). The influence of emissivity on urban LST was examined by allocating more realistic emissivity values to metallic surfaces. For a Landsat image, LST values for the urban area increased from 41 °C to 44, 46, and 49 °C when metallic surfaces were allocated emissivity values of 0.96, 0.83, 0.74, and 0.63, respectively, and SUHIs, rather than SUCIs, were observed. Similar results were obtained for an ECOSTRESS image. As increasing summer temperatures cause significant morbidity and mortality in the populations of these cities, accurate urban climatic data are essential.