Spatial Downscaling Frameworks for Satellite Based Land Surface Temperature to Support Permafrost Modelling

Land surface temperature (LST) retrieved from satellite data is a crucial parameter in the energy exchange between the Earth’s surface and the atmosphere and for environmental monitoring. One important application is permafrost modelling, where LST is a key input layer. Permafrost modelling requires continuous high spatiotemporal LST information to capture the heterogeneous nature of Arctic land cover accurately. Recent advances in spatiotemporal fusion and super-resolution models offer new solutions to downscale thermal infrared (TIR) data and, therefore, allow obtaining LST data at a high spatial and temporal resolution. This study compares the performances of different models to increase the spatial resolution of Advanced Very High Resolution Radiometer (AVHRR) LST data in the Arctic.