Share Email Print
cover

Proceedings Paper

Comparative analysis of land surface emissivity retrieval methods and the impact on the land surface temperature based on Landsat-8 thermal infrared data
Author(s): Zenghui Kan; Chaoshun Liu; Cong Zhou; Zhijun Li
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

With the increasingly prevalent and far-reaching application of remote sensing, several algorithms have been put forward for land surface temperature retrieval. However, there is still no consensus on the calculation of land surface emissivity (LSE), which is one of the significant parameters in land surface temperature (LST) retrieval. In this paper, two methods of estimating LSE based on thematic mapper data were introduced: Van’s empirical formula method and the mixed pixels method. Based on the detailed introduction to Van’s empirical formula and the mixed pixels decomposing method in computing surface emissivity, Landsat-8 thermal infrared data and the radiative transfer equation method were used to obtain the land surface temperature in Taihu region. In this paper, atmospheric parameters are based on real-time atmospheric profile to reduce the LST error brought by the atmospheric profile. Two figures were acquired, which represented the LST of Van’s empirical formula and the mixed pixels decomposing method respectively. The relationship between land surface temperature and land cover was also studied.

Paper Details

Date Published: 4 September 2015
PDF: 9 pages
Proc. SPIE 9610, Remote Sensing and Modeling of Ecosystems for Sustainability XII, 961012 (4 September 2015); doi: 10.1117/12.2186766
Show Author Affiliations
Zenghui Kan, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Colorado State Univ. (United States)
Chaoshun Liu, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Colorado State Univ. (United States)
Cong Zhou, East China Normal Univ. (China)
Institute of Remote Sensing and Digital Earth (China)
Colorado State Univ. (United States)
Zhijun Li, Jingjiang Meteorological Bureau (China)


Published in SPIE Proceedings Vol. 9610:
Remote Sensing and Modeling of Ecosystems for Sustainability XII
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)

© SPIE. Terms of Use
Back to Top
PREMIUM CONTENT
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?
close_icon_gray