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Proceedings Paper

Comparison of different water infrared emissivity retrieval methods with the theoretical model
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Paper Abstract

Water surface emissivity is a vital parameter in thermal remote sensing, since knowledge of them is required to estimate surface temperature with enough accuracy. It is also important in meteorological and climatological analysis. In this study, we show the results obtained for the water surface emissivity spectra from absolute emissivity method (AE) and the temperature and emissivity separation (TES) algorithm in the laboratory measurements with a mutiband thermal radiometer. And compare the retrieved emissivities with the water surface theoretical model. The results show that there is an agreement better than 1% for all bands for AE method, However, the TES algorithm retrieves get bad results, the deviations nearly reach 3%, due to the water have low emissivity spectral contrast, which correspond to an error in water surface temperature from 1.7 K to 2K. By revising TES algorithm (TSE*), which precision indicate accuracy of lower than 1%. Both AE and revised TES (TES*) algorithm demonstrate that they can be applying to retrieve accurate emissivity spectra for water surfaces in laboratory measurements. And providing other emissivity measurements methods reference, also supplying some thermal emission and temperature algorithm researches guidance.

Paper Details

Date Published: 12 October 2015
PDF: 10 pages
Proc. SPIE 9639, Sensors, Systems, and Next-Generation Satellites XIX, 963920 (12 October 2015); doi: 10.1117/12.2193857
Show Author Affiliations
Ji-An Wei, Second Institute of Oceanography, SOA (China)
Difeng Wang, Second Institute of Oceanography, SOA (China)
Fang Gong, Second Institute of Oceanography, SOA (China)
Yan Bai, Second Institute of Oceanography, SOA (China)
Xianqiang He, Second Institute of Oceanography, SOA (China)
Jianyu Chen, Second Institute of Oceanography, SOA (China)


Published in SPIE Proceedings Vol. 9639:
Sensors, Systems, and Next-Generation Satellites XIX
Roland Meynart; Steven P. Neeck; Haruhisa Shimoda, Editor(s)

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