Terrestrial Hydrology Research Group
Princeton University
Global Land Surface Temperature Data
To access the data, please give some details about yourself and its intended usage. Please cite the following reference in any work that uses the dataset:
Coccia, G., Siemann, A.L., Pan, M., Wood, E.F., 2015: Creating consistent datasets by combining remotely-sensed data and land surface model estimates through Bayesian uncertainty post-processing: The case of Land Surface Temperature from HIRS. Remote Sensing of Environment, 170, pp. 290-305.

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Terrestrial Hydrology Group
Dept. Civil and Environmental Engineering
Princeton University
Princeton, NJ 08544