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Proceedings Paper

Uncertainty analysis of in-flight spectral calibration for hyperspectral imaging spectrometers
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Paper Abstract

Hyperspectral imaging instrument performance, especially spectral response parameters, may change when the sensors work in-flight due to vibrations, temperature and pressure changes compared with the laboratory status. In order to derive valid information from imaging data, accurate spectral calibration accompanied by uncertainty analysis to the data must be made. The purpose of this work is to present a process to estimate the uncertainties of in-flight spectral calibration parameters by analyzing the sources of uncertainty and calculating their sensitivity coefficients. In the in-flight spectral calibration method, the band-center and bandwidth determinations are made by correlating the in-flight sensor measured radiance with reference radiance. In this procedure, the uncertainty analysis is conducted separately for three factors: (a) the radiance calculated from imaging data; (b) the reference data; (c) the matching process between the above two items. To obtain the final uncertainty, contributions due to every impact factor must be propagated through this process. Analyses have been made using above process for the Hyperion data. The results show that the shift of band-center in the oxygen absorption (about 762nm), compared with the value measured in the lab, is less than 0.9nm with uncertainties ranging from 0.063nm to 0.183nm related to spatial distribution along the across-track direction of the image, the change of bandwidth is less than 1nm with uncertainties ranging from 0.066nm to 0.166nm. This results verify the validity of the in-flight spectral calibration process.

Paper Details

Date Published:
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Proc. SPIE 10427, Image and Signal Processing for Remote Sensing XXIII, ; doi: 10.1117/12.2277702
Show Author Affiliations
Huijie Zhao, BeiHang Univ. (China)
Ruonan Geng, BeiHang Univ. (China)
Guorui Jia, BeiHang Univ. (China)
Daming Wang, China Geological Survey (China)


Published in SPIE Proceedings Vol. 10427:
Image and Signal Processing for Remote Sensing XXIII
Lorenzo Bruzzone, Editor(s)

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