Downscaling Land Surface Temperature via Assimilation of LandSat 8/9 OLI and TIRS Data and Hypersharpening

Land surface temperature (LST) plays a pivotal role in many environmental sectors. Unfortunately, thermal bands produced by instruments that are onboard satellites have limited spatial resolutions; this seriously impairs their potential usefulness. In this study, we propose an automatic procedure for the spatial downscaling of the two 100 m thermal infrared (TIR) bands of LandSat 8/9, captured by the TIR spectrometer (TIRS), by exploiting the bands of the optical instrument. The problem of fusion of heterogeneous data is approached as hypersharpening: each of the two sharpening images is synthesized following data assimilation concepts, with the linear combination of 30 m optical bands and the 15 m panchromatic (Pan) image that maximizes the correlation with each thermal channel at its native 100 m scale. The TIR bands resampled at 15 m are sharpened, each by its own synthetic Pan. On two different scenes of an OLI-TIRS image, the proposed approach is compared with 100 m to 15 m pansharpening, carried out uniquely by means of the Pan image of OLI and with the two high-resolution assimilated thermal images that are used for hypersharpening the two TIRS bands. Besides visual evaluations of the temperature maps, statistical indexes measuring radiometric and spatial consistencies are provided and discussed. The superiority of the proposed approach is highlighted: the classical pansharpening approach is radiometrically accurate but weak in the consistency of spatial enhancement. Conversely, the assimilated TIR bands, though adequately sharp, lose more than 20% of radiometric consistency. Our proposal trades off the benefits of its counterparts in a unique method.