Remote Sensing Mineralization Information Extraction And Multi-source Data Of Metallogenic Prediction

Northwest China, sparsely populate, inaccessible and vegetation are not developed, remote sensing technology in the field of geological prospecting and evaluation field has unique advantages and good results. With the rapid development of computers, GIS and other related technologies, remote sensing alteration information extraction and combined with multi-source data metallogenic prediction work has been widely carried out.This paper relies on mineral survey project in Dunhuang Baishan area of Gansu Province, analysis and research existing geological data to understand the geological background research and metallogenic environment. Through interpret based remote sensing image of this area, obtain stratigraphic and structural information to statistical analysis, outlines the basic structure of the distribution pattern of the study area. Using Principal Component Analysis to extract iron stained and mud of remote sensing alteration information. Finally, comprehensive analysis multi-source data include geological, geochemical,geophysical and remote sensing information use of GIS spatial analysis technology, combined with the geological background and metallogenic regularity of the study area, delineated six metallogenic prediction area.Main achieved the following results:1. The selected ETM image data were processed with statistical basis, through geometric correction and image fusion acquired 741 bands portfolio based remote sensing images in line with geological interpretation.2. Through quantitative statistical analysis of linear and ring structure length,orientation and density divided the construction density levels, fully reflect the structure of rules and distribution in the study area.3. Using principal component analysis to extract the iron staining and argillicalteration information, divides the two alteration information and summarizes their distribution.4. Analysis the relationship between the various abnormality information using Superposition Analysis, using weights of evidence model analyzed of multi-source data to metallogenic prediction, delineated six metal mineralization prospective areas.Prediction method prediction accuracy is better than a single technology is more scientific and reasonable.