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Proceedings Paper

Measurements of natural surface emissivity with portable Fourier transform infrared spectroradiometer
Author(s): Bo-Hui Tang; Jie Wang; Zhao-Liang Li; Hua Wu; Ronglin Tang
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Paper Abstract

Land surface emissivity (LSE) is a critical parameter for retrieving land surface temperature (LST) from remotely sensed data. Due to its non-uniformity and a change through vegetation and physical parameters such as texture, composition, surface moisture, roughness, and view angle, the measurement of LSE in laboratory cannot reflect the real world conditions that material interacts with its background and the environment. The filed measurement currently observed by a thermal sensor is radiance, which is a function of many contributing parameters. To accurately obtain the LSE, this paper devotes to develop a scheme for deriving the spectral emissivity from field measured radiance observed by a hand portable FT-IR spectroradiometer Model 102F. A piecewise linear spectral emissivity constraint method is used to decouple the LST and LSE. The results show that the trends of the derived emissivity spectra for different natural surfaces of sand, bare soil and grass are reasonable. Comparisons of several field and laboratory collected LSE spectra for different natural surfaces show that the root mean square errors (RMSEs) are below 0.02, which indicates that the proposed method is accurately to derive LSE spectrum from the measurement of field natural surface with 102F field spectroradiometer.

Paper Details

Date Published: 9 December 2015
PDF: 7 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 98081B (9 December 2015); doi: 10.1117/12.2207602
Show Author Affiliations
Bo-Hui Tang, Institute of Geographic Sciences and Natural Resources Research (China)
Jie Wang, Institute of Geographic Sciences and Natural Resources Research (China)
Univ. of Chinese Academy of Sciences (China)
Zhao-Liang Li, Institute of Geographic Sciences and Natural Resources Research (China)
Chinese Academy of Agricultural Sciences (China)
ICube, Univ. of Strasbourg, CNRS (France)
Hua Wu, Institute of Geographic Sciences and Natural Resources Research (China)
Ronglin Tang, Institute of Geographic Sciences and Natural Resources Research (China)


Published in SPIE Proceedings Vol. 9808:
International Conference on Intelligent Earth Observing and Applications 2015
Guoqing Zhou; Chuanli Kang, Editor(s)

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