A Multi-Channel Method for Retrieving Surface Temperature for High-Emissivity Surfaces from Hyperspectral Thermal Infrared Images

Sensors

Xinke Zhong²  Jelila Labed²  Guoqing Zhou⁴  Kun Shao¹  Zhao-Liang Li³ 

[1] School of Computer and Information, Hefei University of Technology, Hefei 230009, China; E-Mail:;ICube, UdS, CNRS, 300 Bld Sebastien Brant, CS10413, 67412 Illkirch, France; E-Mails:;Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China;Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China; E-Mail:

关键词: surface temperature retrieval;    spectral information;    hyperspectral thermal infrared images;    IASI;   

DOI  :  10.3390/s150613406

来源: mdpi

【 摘 要 】

The surface temperature (ST) of high-emissivity surfaces is an important parameter in climate systems. The empirical methods for retrieving ST for high-emissivity surfaces from hyperspectral thermal infrared (HypTIR) images require spectrally continuous channel data. This paper aims to develop a multi-channel method for retrieving ST for high-emissivity surfaces from space-borne HypTIR data. With an assumption of land surface emissivity (LSE) of 1, ST is proposed as a function of 10 brightness temperatures measured at the top of atmosphere by a radiometer having a spectral interval of 800–1200 cm⁻¹ and a spectral sampling frequency of 0.25 cm⁻¹. We have analyzed the sensitivity of the proposed method to spectral sampling frequency and instrumental noise, and evaluated the proposed method using satellite data. The results indicated that the parameters in the developed function are dependent on the spectral sampling frequency and that ST of high-emissivity surfaces can be accurately retrieved by the proposed method if appropriate values are used for each spectral sampling frequency. The results also showed that the accuracy of the retrieved ST is of the order of magnitude of the instrumental noise and that the root mean square error (RMSE) of the ST retrieved from satellite data is 0.43 K in comparison with the AVHRR SST product.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.