Some key preprocessing techniques on airborne imaging spectrometer data for quantitative analysis

Linli Cui; Wenyi Fan; Jun Shi; Ping Tang; Zhongming Zhao; Zhiqiang Gao

doi:10.1117/12.556669

14 October 2004 Some key pre-processing techniques on airborne imaging spectrometer data for quantitative analysis

Linli Cui, Wenyi Fan, Jun Shi, Ping Tang, Zhongming Zhao, Zhiqiang Gao

Proceedings Volume 5548, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective; (2004) https://doi.org/10.1117/12.556669
Event: Optical Science and Technology, the SPIE 49th Annual Meeting, 2004, Denver, Colorado, United States

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.

Citation Download Citation

Linli Cui, Wenyi Fan, Jun Shi, Ping Tang, Zhongming Zhao, and Zhiqiang Gao "Some key pre-processing techniques on airborne imaging spectrometer data for quantitative analysis", Proc. SPIE 5548, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, (14 October 2004); https://doi.org/10.1117/12.556669

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