Abstract
We present an approach for reconstructing land surface temperature (LST) time series over mountainous areas based on Regression Kriging (RK) technique and a data processing scheme for filtering out LST noise and artifacts. A total of 1462 eight-day composite Moderate Resolution Imaging Spectroradiometer LST images over central Qinghai-Tibet Plateau over 2003-2010 are reconstructed. The regression model includes four auxiliary predictors-latitude, longitude, elevation, and NDVI-which are proven to be a good estimator for the 8-day LST. Comparison of ground surface temperature (GST) measurements at eight meteorological stations with the raw and reconstructed LST series shows that the reconstruction strategy can effectively recover complete high-quality over-land LST maps and significantly improve the consistency between LST and GST.
Original language | English |
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Article number | 6545342 |
Pages (from-to) | 1602-1606 |
Number of pages | 5 |
Journal | IEEE Geoscience and Remote Sensing Letters |
Volume | 10 |
Issue number | 6 |
DOIs | |
Publication status | Published - 31 Oct 2013 |
Keywords
- Image analysis
- image processing
- image reconstruction
- remote sensing
- temperature.
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Geotechnical Engineering and Engineering Geology