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Proceedings Paper

Some key pre-processing techniques on airborne imaging spectrometer data for quantitative analysis
Author(s): Linli Cui; Wenyi Fan; Jun Shi; Ping Tang; Zhongming Zhao; Zhiqiang Gao
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Paper Abstract

Hyperspectral image possesses incomparable advantage over spaceborne multispectral image when it is employed to quantitatively retrieve these parameters such as vegetation type, coverage, biomass, bare soil moisture, etc. This paper focuses on crucial issues present in the pre-processing of hyperspectral image: band selection, edge radiant correction, tangent correction and spectral reflectivity conversion, exemplified by a case study in which modular airborne OMIS-I imaging spectrometer data are employed to evaluate desertification. The author gives comprehensive consideration to the statistic characteristics of each spectral band, diagnostic spectral reflection of different targets and the purpose of practical application, and fixed upon 41 applicable bands after trying different bands. In the course of edge radiant correction, one correction method based on histogram matching was used, and its result was satisfactory. In addition, tangent correction directing against tangent distortion was carried out, which enriched the normal geometric rectification. Lastly, during the process of surface feature spectral reflectivity conversion, the author converted symbolic model into statistic model by employing some necessary theoretical inference and parameter-setting. The result suggests the quality of OMIS-I data get better improved after these processing and basically can meet the requirements of quantitative retrieval for desertification evaluation.

Paper Details

Date Published: 14 October 2004
PDF: 11 pages
Proc. SPIE 5548, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, (14 October 2004); doi: 10.1117/12.556669
Show Author Affiliations
Linli Cui, Institute of Remote Sensing Applications (China)
Graduate School of the Chinese Academy of Sciences (China)
Wenyi Fan, Northeast Forestry Univ. (China)
Jun Shi, Institute of Geographic Sciences and Natural Resources Research (China)
Graduate School of the Chinese Academy of Sciences (China)
Ping Tang, Institute of Remote Sensing Applications (China)
Zhongming Zhao, Institute of Remote Sensing Applications (China)
Zhiqiang Gao, Institute of Geographic Sciences and Natural Resources Research (China)


Published in SPIE Proceedings Vol. 5548:
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective
Hung-Lung Allen Huang; Hal J. Bloom, Editor(s)

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