Experiment study on quantitative retrieval of mineral abundances from reflectance spectra

Bokun Yan; Shengwei Liu; Runsheng Wang; Xiaofang Guo; Weidong Sun

doi:10.1117/12.815549

24 November 2008 Experiment study on quantitative retrieval of mineral abundances from reflectance spectra

Bokun Yan, Shengwei Liu, Runsheng Wang, Xiaofang Guo, Weidong Sun

Proceedings Volume 7123, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China; 712303 (2008) https://doi.org/10.1117/12.815549
Event: Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 2007, Beijing, China

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.

Citation Download Citation

Bokun Yan, Shengwei Liu, Runsheng Wang, Xiaofang Guo, and Weidong Sun "Experiment study on quantitative retrieval of mineral abundances from reflectance spectra", Proc. SPIE 7123, Remote Sensing of the Environment: 16th National Symposium on Remote Sensing of China, 712303 (24 November 2008); https://doi.org/10.1117/12.815549

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