Detection of alteration zones using the Dirichlet process Stick-Breaking model-based clustering algorithm to hyperion data: the case study of Kuh-Panj porphyry copper deposits, Southern Iran
Detection of hydrothermal alteration zones (HAZs) associated with porphyry copper systems using remote sensing imagery is a crucial stage for discovering high potential zone of ore mineralization. Statistical model-based clustering methods have great potential for automatic and accurate detection of...
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| Vydáno v: | Geocarto international Ročník 37; číslo 25; s. 9788 - 9816 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Taylor & Francis
13.12.2022
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| ISSN: | 1010-6049, 1752-0762, 1752-0762 |
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| Abstract | Detection of hydrothermal alteration zones (HAZs) associated with porphyry copper systems using remote sensing imagery is a crucial stage for discovering high potential zone of ore mineralization. Statistical model-based clustering methods have great potential for automatic and accurate detection of hydrothermal alteration minerals using hyperspectral remote sensing imagery. In this research, the Dirichlet Process based on Stick-Breaking (DPSB) model-based clustering algorithm was implemented to hyperion remote sensing imagery to discriminate HAZs associated with the Kuh-Panj porphyry copper deposit, south, Iran. The DPSB clustering algorithm was implemented and subsequently compared with the k-means algorithm, CLARA clustering, hierarchical clustering, Gaussian finite mixture model (GFMM), Gaussian model for high-dimensional (GMHD) and spectral clustering as well as spectral angle mapping (SAM). Results derived from the DPSB model-based clustering algorithm show 88.6% accuracy in distinguishing propylitic, argillic, advanced argillic, propylitic-argillic and phyllic alteration zones. The DPSB algorithm can be broadly implemented to hyperspectral remote sensing imagery for detecting alteration zones associated with porphyry systems. |
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| AbstractList | Detection of hydrothermal alteration zones (HAZs) associated with porphyry copper systems using remote sensing imagery is a crucial stage for discovering high potential zone of ore mineralization. Statistical model-based clustering methods have great potential for automatic and accurate detection of hydrothermal alteration minerals using hyperspectral remote sensing imagery. In this research, the Dirichlet Process based on Stick-Breaking (DPSB) model-based clustering algorithm was implemented to hyperion remote sensing imagery to discriminate HAZs associated with the Kuh-Panj porphyry copper deposit, south, Iran. The DPSB clustering algorithm was implemented and subsequently compared with the k-means algorithm, CLARA clustering, hierarchical clustering, Gaussian finite mixture model (GFMM), Gaussian model for high-dimensional (GMHD) and spectral clustering as well as spectral angle mapping (SAM). Results derived from the DPSB model-based clustering algorithm show 88.6% accuracy in distinguishing propylitic, argillic, advanced argillic, propylitic-argillic and phyllic alteration zones. The DPSB algorithm can be broadly implemented to hyperspectral remote sensing imagery for detecting alteration zones associated with porphyry systems. |
| Author | Yousefi, Mastoureh Pradhan, Biswajeet Tabatabaei, Seyed Hassan Rikhtehgaran, Reyhaneh Pour, Amin Beiranvand |
| Author_xml | – sequence: 1 givenname: Mastoureh orcidid: 0000-0002-8412-0792 surname: Yousefi fullname: Yousefi, Mastoureh organization: Department of Mining Engineering, Isfahan University of Technology – sequence: 2 givenname: Seyed Hassan orcidid: 0000-0003-2869-748X surname: Tabatabaei fullname: Tabatabaei, Seyed Hassan organization: Department of Mining Engineering, Isfahan University of Technology – sequence: 3 givenname: Reyhaneh orcidid: 0000-0001-5815-2769 surname: Rikhtehgaran fullname: Rikhtehgaran, Reyhaneh organization: Department of Mathematical Sciences, Isfahan University of Technology – sequence: 4 givenname: Amin Beiranvand orcidid: 0000-0001-8783-5120 surname: Pour fullname: Pour, Amin Beiranvand organization: Institute of Oceanography and Environment (INOS), Universiti Malaysia Terengganu (UMT) – sequence: 5 givenname: Biswajeet orcidid: 0000-0001-9863-2054 surname: Pradhan fullname: Pradhan, Biswajeet organization: Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan Malaysia |
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| SubjectTerms | algorithms Alteration zones case studies DPSB hyperion Iran mineralization porphyry copper systems remote sensing SAM |
| Title | Detection of alteration zones using the Dirichlet process Stick-Breaking model-based clustering algorithm to hyperion data: the case study of Kuh-Panj porphyry copper deposits, Southern Iran |
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