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Mineral potential mapping for Au and As using Gap statistic method in multivariate mode
Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry for mineral exploration and environmental assessment. To identify and separate geochemical anomalies, several statistical methodologies (nonstructural and structural) are pre...
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Published in: | Carbonates and evaporites 2020-03, Vol.35 (1), Article 2 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry for mineral exploration and environmental assessment. To identify and separate geochemical anomalies, several statistical methodologies (nonstructural and structural) are presented by researchers. The Gap statistic method is a traditional approach which does not depend on the location of samples. This method is one of the univariate methods which assess the threshold based on one variable (one element). In this study, the Gap statistic applied on grade values of samples for separating anomaly from background in the case of Au and As resulted from surface sampling in Susanvar district, Iran. Then, this method is employed to delineation geochemical anomalies in multivariate mode using Euclidean distance. Finally, bivariate geochemical anomaly map is provided for Au and As using multivariate Gap statistic method. Results show that dispersion of the anomalous samples indicated by this method has decreased and they are located near each other in comparison with other univariate nonstructural ones. Also, it is seen that performance of Gap statistic method is increased for estimating threshold and separation in multivariate mode using Euclidean distance. So that, prepared mineral potential map for Au and As using multivariate Gap statistic shows that anomalous area is corresponded to Au occurrences in the region. |
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ISSN: | 0891-2556 1878-5212 |
DOI: | 10.1007/s13146-019-00546-8 |