An Improved TES Method to Retrieve Urban Surface Temperature

Abstract

The urban complex material and geometry characteristics result in a 3-D thermal heterogeneity and that limits the urban surface temperature (UST) retrieval. In this study, we improved the temperature and emissivity separation (TES) algorithm by incorporating thermal heterogeneity within mixed pixel (MP). The improvement was based on the discrete anisotropic radiative transfer (DART) model and applied to retrieve land surface temperature (LST) from Sustainable Development Goals Science Satellite 1 (SDGSAT-1). The TES algorithm retrieval approach for MP (TES-MP) algorithm was validated with ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and the data simulated by the DART model, and the results show that it can reach good accuracy under complex urban conditions. Based on the simulated scenes from the Sheung Wan building in Hong Kong, the root mean squared error (RMSE) of the TES-MP algorithm is 0.85 K under thermal homogeneous conditions and 1.13 K under thermal heterogeneous conditions. Additionally, new high-reflectivity construction materials are common in urban areas, i.e., metal materials. It shows that the relationship between maximum-minimum difference (MMD) and minimum emissivity (ε_min) is not applicable to these materials. Thus, the impacts of such materials on the UST retrieval were evaluated. The results show that the higher the reflectivity and the fractional abundance of such materials, the larger the LST underestimation. Under nadir observation conditions, the proportion of high-reflectivity walls does not cause significant LST retrieval errors. The geometry and adjacency effects on retrieved LST were evaluated, and the results show that the TES-MP algorithm has some resistance to geometry and adjacency effects, thereby reducing errors in LST retrieval. This study provides a new view on retrieving LST of urban MPs and also suggests that three or more bands should be considered when setting up thermal infrared (TIR) sensors.