Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method
AbstractLand Surface Temperature (LST) is a key parameter in climate systems. The methods for retrieving LST from hyperspectral thermal infrared data either require accurate atmospheric profile data or require thousands of continuous channels. We aim to retrieve LST for natural land surfaces from hyperspectral thermal infrared data using an adapted multi-channel method taking Land Surface Emissivity (LSE) properly into consideration. In the adapted method, LST can be retrieved by a linear function of 36 brightness temperatures at Top of Atmosphere (TOA) using channels where LSE has high values. We evaluated the adapted method using simulation data at nadir and satellite data near nadir. The Root Mean Square Error (RMSE) of the LST retrieved from the simulation data is 0.90 K. Compared with an LST product from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat, the error in the LST retrieved from the Infared Atmospheric Sounding Interferometer (IASI) is approximately 1.6 K. The adapted method can be used for the near-real-time production of an LST product and to provide the physical method to simultaneously retrieve atmospheric profiles, LST, and LSE with a first-guess LST value. The limitations of the adapted method are that it requires the minimum LSE in the spectral interval of 800–950 cm−1 larger than 0.95 and it has not been extended for off-nadir measurements. View Full-Text
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Zhong, X.; Huo, X.; Ren, C.; Labed, J.; Li, Z.-L. Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method. Sensors 2016, 16, 687.
Zhong X, Huo X, Ren C, Labed J, Li Z-L. Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method. Sensors. 2016; 16(5):687.Chicago/Turabian Style
Zhong, Xinke; Huo, Xing; Ren, Chao; Labed, Jelila; Li, Zhao-Liang. 2016. "Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method." Sensors 16, no. 5: 687.
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