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REMOTE SENSING FOR LAND & RESOURCES    2005, Vol. 17 Issue (4) : 28-31     DOI: 10.6046/gtzyyg.2005.04.07
Technology and Methodology |
MINERAL AUTO-IDENTIFICATION BASED ON
HYPERSPECTRAL IMAGING DATA AND ITS APPLICATION
ZHOU Qiang 1,2, GAN Fu-ping 2, WANG Run-sheng 2, CHEN Jian-ping 1
1.China University of Geosciences, Beijing 100083, China; 2.China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China
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Abstract  

Spectral knowledge acquired through the understanding of mineral spectral features was used to perform automatic extraction of mineral type information based on mathematical, logic and some other decision rules in the hyperspectral imaging field. In this paper, a mineral auto-identification module for hyperspectral imaging data (MAIM-HID) has been designed by IDL language on ENVI software. It has intelligence and batch processing capacity so that it can identify and extract as many as over 10 types of minerals or mineral groups directly. This module is applicable to aero Hymap and AVIRIS data as well as satellite Hyperion data. It already identified and discriminated some minerals in East Tianshan Mountain of Xinjiang and Qulong area of Tibet in China and Cuprite in U.S.A.

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TP 391.41

 
Issue Date: 10 September 2009
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Yang Wenjin
Liu Xinji
Cite this article:   
Yang Wenjin,Liu Xinji. MINERAL AUTO-IDENTIFICATION BASED ON
HYPERSPECTRAL IMAGING DATA AND ITS APPLICATION[J]. REMOTE SENSING FOR LAND & RESOURCES, 2005, 17(4): 28-31.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2005.04.07     OR     https://www.gtzyyg.com/EN/Y2005/V17/I4/28
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[J]. REMOTE SENSING FOR LAND & RESOURCES, 2005, 17(2): 33-35.
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