Volume 40 Issue 8
Aug.  2015
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Article Navigation >  Earth Science  > 2015  >  40(8): 1432-1440
Wei Jing, Ming Yanfang, Liu Fujiang, 2015. Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination. Earth Science, 40(8): 1432-1440. doi: 10.3799/dqkx.2015.130
Citation: Wei Jing, Ming Yanfang, Liu Fujiang, 2015. Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination. Earth Science, 40(8): 1432-1440. doi: 10.3799/dqkx.2015.130
shu

Hyperspectral Mineral Mapping Method Based on Spectral Characteristic Parameter Combination

doi: 10.3799/dqkx.2015.130
  • 1.

    College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China

  • 2.

    Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China

  • Received Date: 2015-04-02
  • Publish Date: 2015-08-01
    Abstract
  • Influenced by the atmospheric environment and other factors, the mineral recognition with hyperspectral remote sensing is difficult to achieve a high accuracy. To improve the accuracy of the mineral identification with such technology, a hyperspectral mineral recognition method based on spectral characteristic parameter combination, which can maintain relatively stable characteristics with the atmospheric changes, is proposed in this paper. Various spectral characteristic parameters are calculated, and the optimal combination of the parameters is selected through the optimum index factor (OIF), based on which, mineral identification is realized with pattern recognition method. Based on the above method, mineral type identification test is carried out in Cuprite mine of Nevada, with airborne visible infrared imaging spectrometer (AVIRIS) hyperspectral data. The results are compared with the work of previous mineral mapping, it shows that the combination of the spectral characteristic parameters, P-A-S2 (P is absorption wave trough position, A is absorption area, S2 is absorption right shoulder position) can get the highest identification precision, the overall accuracy can reach 74.68%.

     

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