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Land surface temperature (LST) is an important parameter highly responsive to surface energy fluxes and has become valuable to many disciplines. Prior to the advent of satellites, it was difficult to obtain LSTs over extensive areas. Even today, as a result of the resolution tradeoffs involved in using satellite data, it is difficult, and sometimes impossible, to acquire satellite LSTs with high spatial and temporal resolutions. This low resolution results in a thermal mixture effect, where the resolution cells are larger than the thermal elements. The disaggregation of remotely sensed land surface temperature (DLST), a research field that focuses on decomposing pixel-based temperatures, has been critical in related fields such as the surface flux downscaling, forest fire detection, and urban heat island monitoring and it is now growing rapidly as one of the thriving subbranches of thermal remote sensing. Various methods have …