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An Improved Cloud Gap-Filling Method for Longwave Infrared Land Surface Temperatures through Introducing Passive Microwave Techniques
2021
Remote Sensing
Satellite-derived land surface temperature (LST) data are most commonly observed in the longwave infrared (LWIR) spectral region. However, such data suffer frequent gaps in coverage caused by cloud cover. Filling these 'cloud gaps' usually relies on statistical re-constructions using proximal clear sky LST pixels, whilst this is often a poor surrogate for shadowed LSTs insulated under cloud. Another solution is to rely on passive microwave (PM) LST data that are largely unimpeded by cloud cover
doi:10.3390/rs13173522
fatcat:jsmnnlkeezh5lale6ku6ramuai