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Remote Sens. 2017, 9(2), 161; doi:10.3390/rs9020161

Algorithm Development for Land Surface Temperature Retrieval: Application to Chinese Gaofen-5 Data

1
Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
2
ICube (UMR7357), UdS, CNRS, 300 Bld Sébastien Brant, CS10413, Illkirch 67412, France
3
Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China
*
Author to whom correspondence should be addressed.
Academic Editors: Jose Moreno and Prasad S. Thenkabail
Received: 7 December 2016 / Revised: 2 February 2017 / Accepted: 13 February 2017 / Published: 16 February 2017
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Abstract

Land surface temperature (LST) is a key variable in the study of the energy exchange between the land surface and the atmosphere. Among the different methods proposed to estimate LST, the quadratic split-window (SW) method has achieved considerable popularity. This method works well when the emissivities are high in both channels. Unfortunately, it performs poorly for low land surface emissivities (LSEs). To solve this problem, assuming that the LSE is known, the constant in the quadratic SW method was calculated by maintaining the other coefficients the same as those obtained for the black body condition. This procedure permits transfer of the emissivity effect to the constant. The result demonstrated that the constant was influenced by both atmospheric water vapour content (W) and atmospheric temperature (T0) in the bottom layer. To parameterize the constant, an exponential approximation between W and T0 was used. A LST retrieval algorithm was proposed. The error for the proposed algorithm was RMSE = 0.70 K. Sensitivity analysis results showed that under the consideration of NEΔT = 0.2 K, 20% uncertainty in W and 1% uncertainties in the channel mean emissivity and the channel emissivity difference, the RMSE was 1.29 K. Compared with AST 08 product, the proposed algorithm underestimated LST by about 0.8 K for both study areas when ASTER L1B data was used as a proxy of Gaofen-5 (GF-5) satellite data. The GF-5 satellite is scheduled to be launched in 2017. View Full-Text
Keywords: land surface temperature; land surface emissivity; split-window; Gaofen-5 land surface temperature; land surface emissivity; split-window; Gaofen-5
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chen, Y.; Duan, S.-B.; Ren, H.; Labed, J.; Li, Z.-L. Algorithm Development for Land Surface Temperature Retrieval: Application to Chinese Gaofen-5 Data. Remote Sens. 2017, 9, 161.

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