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Proceedings Paper

Land surface emissivity retrieval from airborne hyperspectral scanner thermal infrared data over urban surfaces
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Paper Abstract

Land surface emissivity (LSE) is a key parameter for characterizing the land surface, and is vital for a wide variety of surface-atmosphere studies. This paper retrieved LSEs of land surfaces over the city of Madrid, Spain from airborne hyperspectral scanner (AHS) thermal infrared data using temperature emissivity separation (TES) method. Six different kinds of urban surfaces: asphalt, bare soil, granite, pavement, shrub and grass pavement, were selected to evaluate the performance of the TES method in urban areas. The results demonstrate that the TES method can be successfully applied to retrieve LSEs in urban area. The six urban surfaces have similar curve shape of emissivity spectra, with the lowest emissivity in band 73, and highest in band 78; the LSE for bare soil varies significantly with spectra, approximately from 0.90 in band 72 to 0.98 in band 78, whereas the LSE for grass has the smallest spectral variation, approximately from 0.965 in band 72 to 0.974 in band 78, and the shrub presents higher LSE than other surfaces in bands 72, 73, 75-77, but a little lower in bands 78 and 79. Furthermore, it is worth noting that band 73 is suitable for discriminating different urban surfaces because large LSE differences exist in this channel for different urban surfaces.

Paper Details

Date Published: 9 December 2015
PDF: 6 pages
Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 980823 (9 December 2015); doi: 10.1117/12.2220606
Show Author Affiliations
C. X. Gao, Academy of Opto-Electronics (China)
Y. G. Qian, Academy of Opto-Electronics (China)
N. Wang, Academy of Opto-Electronics (China)
L. L. Ma, Academy of Opto-Electronics (China)
X. G. Jiang, Univ. of Chinese Academy of Sciences (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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