The objective of this activity is to develop a retrieval algorithm for LST with high temporal and spatial resolution over urban areas aimed at public health applications: providing health authorities with high-quality data for heat risk assessment and mitigation. High temporal resolution will be achieved by a synergistic use of data from multiple TIR missions, including medium-resolution Sentinel-3 data and high-resolution data from the upcoming LSTM mission. Radiometric harmonisation of the instruments will be ensured, after a rigorous uncertainty analysis. High spatial resolution is targeted by downscaling relying on an Optimal Estimation (OE) method based on LSE derived from land cover maps produced by sub-pixel classification (spectral unmixing) of hyperspectral data from the future ESA CHIME mission. The developed retrieval will be validated and demonstrated with (1) a high-fidelity simulation dataset where input data will be simulated by a high-resolution RTM developed for urban environments and sampled, spatially and spectrally, to represent the missions of interest; and (2) a representative mission dataset where input data will be obtained from currently available missions (ECOSTRESS, Landsat-8/9, Sentinel-3 SLSTR, PRISMA, EnMAP).
