Abstract
Due to the trade-off between spatial and temporal resolutions, no available satellite-derived land surface temperature (LST) products have concurrently high spatiotemporal resolution. This study proposes a method that BLEnds Spatiotemporal Temperatures (BLEST) derived from multiscale satellite observations. The purpose of this study is to generate hourly ∼100m-resolution LSTs over heterogeneous surfaces while considering land cover change. The method is tested on both simulated data and actual satellite data, resulting in improved accuracies and spatial details compared to the spatial and temporal adaptive reflectance fusion model (STARFM), Enhanced STARFM (ESTARFM), and spatiotemporal integrated temperature fusion model (STITFM).
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