Metallogenic Prognosis Analysis Based on GIS and Weights of Evidence Modeling in Central Southern Peru
详细信息
- 责任者：Xi Zhen (School of Geosciences and Info-Physics ; Central South University ; Changsha 410083 ; China) ; Gao Guangming
- 刊名：Geotectonica et Metallogenia
- 出版年：2013
- 卷期：37(2)
- 关键词：成矿预测 ; metallogenic prediction ; 地理信息系统 ; geographic information system ; 秘鲁 ; Peru
- 页码：p.340-348
- 图表：illus., 5 tables, 18 refs.
- 分类号：1001
- issnNo：ISSN1001-1552
- isbnNo：CN44-1595/P
摘要
Peru is located in central Andes of South America. Based on the multisource data including geological,mining,Landsat ETM+,geochemical,aeromagnetic,GIS spatial analysis and geological mineralization analysis were integrated for mineral potential mapping. Principally,geochemical composite elements anomalies were extracted in the Mahalanobis distance method. Based on ETM+satellite data,principal component analysis and ratio a-nalysis were used to extract iron-stained and argillic alteration. Correlation between deposits and prospecting information variation calculating by the weights of evidence method was exploited to select the optimal prospecting information quantity as an evidence factor. Geochemical and aeromagnetic anomalies could indicate the possible contact zone of the intrusive rocks with layers which is favorable for ore formation. Remote sensing anomalies show that the western parts of the studied area generally distribute iron mineralization and silicification,clay alteration. On analysis by synthesis,22 important factors were selected to establish weight of evidence prognosis model. Metallogenic prognosis posterior probability map was drawn. The result showed that there are four potential metallogenic prospect areas,which might be favorable for polymetallic mineralization. Seventy-eight percent of the known mineral occurrences fell in these four areas. Further provided reference for resource prediction and assessment study in the high posterior probability zones were expounded. This result based on weight of evidence model by multisource data analysis offered scientific evidence of resource exploration in the Central Southern Peru.
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