Please wait a minute...
 
REMOTE SENSING FOR LAND & RESOURCES    2002, Vol. 14 Issue (4) : 44-50     DOI: 10.6046/gtzyyg.2002.04.10
Technology and Methodology |
STUDYING ON THE ALTERATION MINERALS IDENTIFICATION USING HYPERION DATA
GAN Fu-ping, WANG Run-sheng, YANG Su-ming
China Aero Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China
Download: PDF(1356 KB)  
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  The minerals identification is primary study using hyperspectral remote sensing technique. And it is also the field where hyperspectral imaging may be proved to be useful. Some alteration minerals, such as sericite(including high Al and low Al respectively), kaolinite and chlorite, are identified and extracted effectively and elementary by SIT(Spectral Identification Tree) technique based on decision rules from various minerals using satellite-borne hyperspectral imaging data at Qulong district of Tibert. Comparing with the geological map, the mineral identification by SIT gained approximate result. At the same time, one new similarity alteration minerals assembled area is discovered. Some geological information gained directly by hyperspectral imaging technique can be used to prognosticate and discover new ore spots or deposits.
Keywords Vegetation suppression      Forced invariance      Multi-spectral      Hyperspectrum     
Issue Date: 02 August 2011
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
SHU Le
ZHANG Qin-Yu
ZHU Jun
ZHANG Deng-Rong
Cite this article:   
SHU Le,ZHANG Qin-Yu,ZHU Jun, et al. STUDYING ON THE ALTERATION MINERALS IDENTIFICATION USING HYPERION DATA[J]. REMOTE SENSING FOR LAND & RESOURCES, 2002, 14(4): 44-50.
URL:  
https://www.gtzyyg.com/EN/10.6046/gtzyyg.2002.04.10     OR     https://www.gtzyyg.com/EN/Y2002/V14/I4/44


[1] Acron

[EB/OL].http://www.aigllc.com/acron/intro.asp.





[2] Baugh W M, Kruse F A, et al. Quantitative geochemical mapping of ammonium minerals in the Southern Cedar Mountains, Nevada, using the airborne visible/infrared imaging spectrometer(AVIRIS) [J].Remote Sens. Environ.,1998, 65:292-308.





[3] Clark N R. Spectroscopy of Rocks and Minerals, and Principles of Spectroscopy

[EB/OL].http://speclab.cr.usgs.gov (last revised June 25,1999).





[4] Gan F, Wang R, Ma A. Spectral Identification Tree (SIT) for Mineral Extraction Using AVIRIS Data[C]. Proceedings of SPIE, 2000,4897.





[5] Hearn D, Digenis C J, Lencioni D E, et al. EO-1 Advanced Land Imager Overview[C].IEEE 2001 International Geoscience and Remote Sensing Symposium, July 9-13,2001.





[6] Liao L, JarEckc P, Glcichauf D, et al. Performance Characterization of the hyperion Imaging spectrometer Instrument[C].Proceedings of SPIE, 2000, 4135:264-275.





[7] Pearlman J, Carman S, Segal C, et al. Overview of the Hyperion Imaging Spectrometer for the NASA EO-1 Mission[C]. 2001 International Geoscience and Remote Sensing Symposium, July 9-13,2001.





[8] 程力军,李志,等.冈底斯东段多金属成矿带的基本特征[J].西藏地质,2001,(1):43-53.





[9] 甘甫平,王润生,马蔼乃. 基于特征谱带的矿物谱系识别[J].地学前缘,2003,(待刊).





[10] 甘甫平, 王润生,郭小方,等.高光谱遥感信息提取与地质应用前景[J]. 国土资源遥感, 2000,(3):38-44.





[11] 王润生, 郭小方,王天兴. 成像光谱方法技术开发应用研究

[P]. 国土资源部"九五"重点科研报告,1999,北京.





[12] 张宗贵,王润生.基于谱学的成像光谱遥感技术发展与应用[J].国土资源遥感. 2000,(3):16-24.
[1] DU Cheng, LI Delin, LI Genjun, YANG Xuesong. Application and exploration of dissolved oxygen inversion of plateau salt lakes based on spectral characteristics[J]. Remote Sensing for Natural Resources, 2021, 33(3): 246-252.
[2] GAO Kaixuan, JIAO Haiming, WANG Xinchuang. Inversion model of forest canopy height based on image texture,spectral and topographic features[J]. Remote Sensing for Land & Resources, 2020, 32(3): 63-70.
[3] Zhan YIN, Lijun ZHANG, Jianliang DUAN, Pei ZHANG. Improvement and application of forced invariance vegetation suppression in southern vegetation area[J]. Remote Sensing for Land & Resources, 2019, 31(2): 82-88.
[4] GUO Xi, YE Yingcong, XIE Biyu, KUANG Lihua, XIE Wen. Inversion of available nitrogen content in hilly paddy soil of southern China based on hyperspectral characteristics[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(2): 94-99.
[5] LI Sha, NI Weiping, YAN Weidong, WU Junzheng, ZHANG Han. Change detection of multi-spectral images based on iterative estimation with weight selection and unsupervised classification[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(4): 34-40.
[6] LI Lin, LUO Heng, TANG Xinming, LI Zhen. Characteristic analysis and quality assessment of ZY-3 multi-spectral image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(1): 17-24.
[7] SHU Le, ZHANG Qin-Yu, ZHU Jun, ZHANG Deng-Rong. A General Approach for Suppressing Vegetation in Optical Remotely Sensed Imagery[J]. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(2): 38-42.
[8] YANG Fei, ZHANG Bai, LIU Zhi-Meng, LIU Dian-Wei, WANG Zong-Meng, SONG Kai-Shan. A STUDY OF CORN FPAR ESTIMATION FROM HYPERSPECTRAL DATA BASED ON PCA APPROACH AND NEAR-INFRARED SHORTWAVE BANDS[J]. REMOTE SENSING FOR LAND & RESOURCES, 2008, 20(4): 9-13.
[9] QIAN Le-xiang, PAN Xue-qin, ZHAO Qian . ADVANCES IN THE APPLICATION AND RESEARCHES OF HYPERSPECTRAL IMAGING REMOTE SENSING IN CHINA[J]. REMOTE SENSING FOR LAND & RESOURCES, 2004, 16(2): 1-6.
[10] YU Fan. THE IMPROVED METHOD FOR HUMIDITY FIELD RETRIEVAL IN CLOUD SKY BY MEANS OF MULTI-SPECTRAL SATELLITE IMAGERY[J]. REMOTE SENSING FOR LAND & RESOURCES, 2003, 15(1): 38-42.
[11] Shi Jizhong. THE COMPARISON BETWEEN IMAGE SIR-A AND MSS IN DIFFERENT AREA IN CHINA[J]. REMOTE SENSING FOR LAND & RESOURCES, 1996, 8(4): 1-8.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech