The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLII-2/W7
https://doi.org/10.5194/isprs-archives-XLII-2-W7-913-2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-913-2017
13 Sep 2017
 | 13 Sep 2017

GEOSTATISTICAL SOLUTIONS FOR DOWNSCALING REMOTELY SENSED LAND SURFACE TEMPERATURE

Q. Wang, V. Rodriguez-Galiano, and P. M. Atkinson

Keywords: Image fusion, Downscaling, Geostatistics, Land surface temperature (LST), Landsat thermal imagery

Abstract. Remotely sensed land surface temperature (LST) downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK), downscaling cokriging (DSCK), kriging with external drift (KED) and area-to-point regression kriging (ATPRK), are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.