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Proceedings Paper

Remote sensing strategic exploration of large or superlarge gold ore deposits
Author(s): Shouxun Yan; Qingsheng Liu; Hongmei Wang; Zhigang Wang; Suhong Liu
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Paper Abstract

To prospect large or superlarge gold ore deposits, blending of remote sensing techniques and modern metallogenitic theories is one of the effective measures. The theory of metallogeny plays a director role before and during remote sensing technique applications. The remote sensing data with different platforms and different resolutions can be respectively applied to detect direct or indirect metallogenic information, and to identify the ore-controlling structure, especially, the ore-controlling structural assemblage, which, conversely, usually are the new conditions to study and to modify the metallogenic model, and to further develop the exploration model of large or superlarge ore deposits. Guidance by an academic idea of 'adjustment structure' which is the conceptual model of transverse structure, an obscured ore- controlling transverse structure has been identified on the refined TM imagery in the Hadamengou gold ore deposit, Setai Hyperspectral Geological Remote Sensing Testing Site (SHGRSTS), Wulashan mountains, Inner Mongolia, China. Meanwhile, The MAIS data has been applied to quickly identify the auriferous alteration rocks with Correspondence Analysis method and Spectral Angle Mapping (SAM) technique. The theoretical system and technical method of remote sensing strategic exploration of large or superlarge gold ore deposits have been demonstrated by the practices in the SHGRSTS.

Paper Details

Date Published: 17 August 1998
PDF: 12 pages
Proc. SPIE 3502, Hyperspectral Remote Sensing and Application, (17 August 1998); doi: 10.1117/12.317786
Show Author Affiliations
Shouxun Yan, Institute of Remote Sensing Applications (China)
Qingsheng Liu, Institute of Remote Sensing Applications (China)
Hongmei Wang, Institute of Remote Sensing Applications (China)
Zhigang Wang, Institute of Remote Sensing Applications (China)
Suhong Liu, Institute of Remote Sensing Applications (China)


Published in SPIE Proceedings Vol. 3502:
Hyperspectral Remote Sensing and Application
Robert O. Green; Qingxi Tong, Editor(s)

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