Integrated fusion of multi-scale polar-orbiting and geostationary satellite observations for the mapping of high spatial and temporal resolution land surface temperature

Land surface temperature (LST) and its diurnal variation are important when evaluating climate change, the land–atmosphere energy budget, and the global hydrological cycle. However, the available satellite LST products have either a coarse spatial resolution or a low temporal resolution, which constrains their potential applications. This paper proposes a spatio-temporal integrated temperature fusion model (STITFM) for the retrieval of high temporal and spatial resolution LST from multi-scale polar-orbiting and geostationary satellite observations. Compared with the traditional fusion methods for LST with two different sensors, the proposed method is able to fuse the LST from arbitrary sensors in a unified framework. The model was tested using LST with fine, moderate, and coarse-resolutions. Data from the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM +) sensors, the Moderate Resolution Imaging Spectroradiometer (MODIS), the Geostationary Operational Environmental Satellite (GOES) Imager, and the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) were used. The fused LST values were evaluated with in situ LST obtained from the Surface Radiation Budget Network (SURFRAD) and the Land Surface Analysis Satellite Application Facility (LSA SAF) project. The final validation results indicate that the STITFM is accurate to within about 2.5 K.