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Abstract
Land-surface temperature (LST) is of great significance for the estimation of radiation and energy budgets associated with land-surface processes. However, the available satellite LST products have either low spatial resolution or low temporal resolution, which constrains their potential applications. This paper proposes a spatiotemporal fusion method for retrieving LST at high spatial and temporal resolutions. One important characteristic of the proposed method is the consideration of the sensor observation differences between different land-cover types. The other main contribution is that the spatial correlations between different pixels are effectively considered by the use of a variation-based model. The method was tested and assessed quantitatively using the different sensors of Landsat TM/ETM+, moderate resolution imaging spectroradiometer and the geostationary operational environmental satellite imager. The validation results indicate that the proposed multisensor fusion method is accurate to about 2.5 K.
Acknowledgements
This work was supported by the Major State Basic Research Development Program (973 Program) under Grant 2011CB707103, National High Technology Research and Development Program (863 Program) under Grant 2013AA12A301, National Natural Science Foundation of China under Grant 41271376, the Hubei Natural Science Foundation under Grant 2011CDA096, and the Fundamental Research Funds for the Central Universities under Grant 2012205020205. Many thanks to the anonymous reviewers. We would like to thank F. Gao, F. Li, and D. L. Sun for their help.