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Erschienen in: Earth Science Informatics 2/2021

08.04.2021 | Research Article

Distance anomaly factors for gold potential mapping in the Jinchanggouliang area, Inner Mongolia, China

verfasst von: Yongliang Chen, Guosheng Sun, Qingying Zhao

Erschienen in: Earth Science Informatics | Ausgabe 2/2021

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Abstract

Distance anomaly factors (DAFs) were defined for each cell of the unit cell population in a study area to represent mineral potential of the cell. A DAF of a cell is a formula for the total distance from the cell to all other cells in the study area. The distance between two cells can be expressed as the Manhattan distance, Canberra distance, Euclidean distance, and kernel Euclidean distance. The kernels in the kernel Euclidean distance can be radial basis function (RBF) kernel, chi-squared kernel, sigmoid kernel, Laplacian kernel, and polynomial kernel. Accordingly, eight DAFs were defined to map gold potential of the Jinchanggouliang area, Inner Mongolia, China. The receiver operating characteristic (ROC) curve analysis was used to evaluate the effectiveness of the eight DAFs. The results show that these DAFs are comparable to one-class support vector machine (OCSVM) in gold potential mapping. The optimal threshold for distinguishing gold potential cells from all the cells was determined by maximizing the Youden index. The gold potential targets predicted by the eight DAFs occupy 7.4% – 16.5% of the study area, while containing 78% - 91% of the discovered gold deposits. The gold potential targets predicted by the default parameter OCSVM and by the bat-optimized OCSVM occupy 9.4% and 16.4% of the study area, respectively, while containing 78% and 87% of the discovered gold deposits. Therefore, the eight DAFs are feasible approaches for gold potential mapping. Their effectiveness needs to be further tested in mineral potential mapping in other areas.

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Metadaten
Titel
Distance anomaly factors for gold potential mapping in the Jinchanggouliang area, Inner Mongolia, China
verfasst von
Yongliang Chen
Guosheng Sun
Qingying Zhao
Publikationsdatum
08.04.2021
Verlag
Springer Berlin Heidelberg
Erschienen in
Earth Science Informatics / Ausgabe 2/2021
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI
https://doi.org/10.1007/s12145-021-00614-5

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