Version 1
: Received: 19 October 2019 / Approved: 22 October 2019 / Online: 22 October 2019 (04:26:18 CEST)
How to cite:
Xu, K.; Wang, X.; Kong, C.; Feng, R.; Liu, G.; Wu, C. Identification of Hydrothermal Alteration Minerals for Exploring Gold Deposit Based on SVM and PCA Using ASTER Data: A Case Study of Gulong. Preprints2019, 2019100251
Xu, K.; Wang, X.; Kong, C.; Feng, R.; Liu, G.; Wu, C. Identification of Hydrothermal Alteration Minerals for Exploring Gold Deposit Based on SVM and PCA Using ASTER Data: A Case Study of Gulong. Preprints 2019, 2019100251
Xu, K.; Wang, X.; Kong, C.; Feng, R.; Liu, G.; Wu, C. Identification of Hydrothermal Alteration Minerals for Exploring Gold Deposit Based on SVM and PCA Using ASTER Data: A Case Study of Gulong. Preprints2019, 2019100251
APA Style
Xu, K., Wang, X., Kong, C., Feng, R., Liu, G., & Wu, C. (2019). Identification of Hydrothermal Alteration Minerals for Exploring Gold Deposit Based on SVM and PCA Using ASTER Data: A Case Study of Gulong. Preprints. https://doi.org/
Chicago/Turabian Style
Xu, K., Gang Liu and Chonglong Wu. 2019 "Identification of Hydrothermal Alteration Minerals for Exploring Gold Deposit Based on SVM and PCA Using ASTER Data: A Case Study of Gulong" Preprints. https://doi.org/
Abstract
Dayaoshan, as an important metal ore producing area in China, is faced with the dilemma of resource depletion due to long-term exploitation. In this paper, remote sensing method is used to circle the favorable metallogenic areas and find new ore points for Gulong. Firstly, vegetation interference bas been removed by using mixed pixel decomposition method with hyperplane and genetic algorithm (GA) optimization; then, altered mineral distribution information has been extracted based on principal component analysis (PCA) and support vector machine (SVM) method; Thirdly, the favorable areas of gold mining in Gulong has been delineated by using ant colony algorithm (ACA) optimization SVM model to remove false altered minerals; Lastly, field survey verified that the extracted alteration mineralization information is correct and effective. The results show that the mineral alteration extraction method proposed in this paper has certain guiding significance for metallogenic prediction by remote sensing.
Keywords
gold deposit; alteration information; ASTER image; support vector machine (SVM); principal component analysis (PCA)
Subject
Environmental and Earth Sciences, Geophysics and Geology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
