
Proceedings Paper
Experiment study on quantitative retrieval of mineral abundances from reflectance spectraFormat | Member Price | Non-Member Price |
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Paper Abstract
Quantitatively retrieving mineral abundances from hyperspectral data is one of promising and challenging geological
application fields of hyperspectral data, and the most basic obstacles are mixture characteristic of mineral spectra and
deconvolution method of mixture spectra. A series of mineral mixture schemes were designed, and several kinds of
mineral were used for investigating the two obstacles. In the experiment, average single scattering albedo was calculated
from reflectance spectra on the basis of Hapke radiative transfer model. The error of mineral abundances derived from
reflectance spectra and single scattering albedo is 20.05% and 5.03% respectively, which shows that mixture spectra of
all kinds of mineral belongs to nonlinear mixing, and Hapke model is a good method of resolving this problem. Finally,
deconvolution of continuum-removed single scattering albedo spectra other than single scattering albedo spectra is
considered to be the possible method that could be applied to imaging spectrometer data (e.g. AVIRIS and Hyperion data)
to retrieve mineral abundances successfully, because intensity of spectra is influenced by terrain considerably rather than
shape of spectra feature is influenced by terrain slightly.
Paper Details
Date Published: 24 November 2008
PDF: 11 pages
Proc. SPIE 7123, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 712303 (24 November 2008); doi: 10.1117/12.815549
Published in SPIE Proceedings Vol. 7123:
Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China
Qingxi Tong, Editor(s)
PDF: 11 pages
Proc. SPIE 7123, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 712303 (24 November 2008); doi: 10.1117/12.815549
Show Author Affiliations
Bokun Yan, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Shengwei Liu, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Runsheng Wang, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Shengwei Liu, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Runsheng Wang, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Xiaofang Guo, China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)
Weidong Sun, Xinjiang Bureau of Exploration and Development of Geology & Mineral Resources (China)
Weidong Sun, Xinjiang Bureau of Exploration and Development of Geology & Mineral Resources (China)
Published in SPIE Proceedings Vol. 7123:
Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China
Qingxi Tong, Editor(s)
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