Title :
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
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;
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
DOI :
10.1109/IGARSS.2008.4779247
