Blending multi-spatiotemporal resolution land surface temperatures over heterogeneous surfaces

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 obser...

Full description

Saved in:
Bibliographic Details
Published in2017 Joint Urban Remote Sensing Event (JURSE) pp. 1 - 4
Main Author Jinling Quan
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2017
Subjects
Data fusion
Earth
geostationary satellite
heterogeneity
land surface temperature
Landsat
MODIS
Remote sensing
Satellites
Spatial resolution
Online AccessGet full text

Cover

More Information
Summary: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).
DOI:10.1109/JURSE.2017.7924596