Mapping Mineral Potential by Combining Multi-Scale and Multi-Source Geo-Information

Author

Wang, Wenlei ; Cheng, Qiuming

Author_Institution

Dept. of Earth & Space Sci. & Eng., York Univ., Toronto, ON

Volume

2

fYear

2008

fDate

7-11 July 2008

Abstract

Image fusion can be divided into pixel, feature and decision level. GIS based methods for mineral exploration are commonly based on feature and decision level. In this paper, a Spatially Weighted Principal Component Analysis (SWPCA) method was applied to combine multi-scale and multi-source geo-information at pixel level. The combination of various geo-information data sets will be either spectrally or spatially based. Results obtained by applying SWPCA to geophysical & remote sensing data and geochemical & remote sensing data clearly show the spatial distribution of intrusive bodies and mineral deposits related anomalies, respectively.

Keywords

geographic information systems; geophysical prospecting; geophysical signal processing; image fusion; minerals; mining; principal component analysis; remote sensing; GIS based methods; decision level image fusion; feature level image fusion; geochemical remote sensing data; geoinformation data sets; geophysical remote sensing data; mineral exploration; mineral potential mapping; multiscale geoinformation; multisource geoinformation; pixel level image fusion; principal component analysis; spatially weighted PCA; Data mining; Geographic Information Systems; Geology; Image fusion; Mineralization; Minerals; Pixel; Principal component analysis; Remote sensing; Sensor fusion; GIS; Multi-scale; PCA; image fusion; multi-source;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International

Conference_Location

Boston, MA

Print_ISBN

978-1-4244-2807-6

Electronic_ISBN

978-1-4244-2808-3

Type

conf

DOI

10.1109/IGARSS.2008.4779247

Filename

4779247