DPSB model-based clustering algorithm for mineral mapping in hyperspectral imagery
The Dirichlet Process based on Stick-Breaking (DPSB) model-based clustering algorithm was instigated to Hyperion remote sensing imagery to map alteration minerals related to porphyry copper deposit. The DPSB clustering results were evaluated using Normalized Information Distance (NID), Normalized Mu...
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| Vydáno v: | IEEE International Geoscience and Remote Sensing Symposium proceedings s. 5470 - 5472 |
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| Jazyk: | angličtina |
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IEEE
17.07.2022
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| ISSN: | 2153-7003 |
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| Abstract | The Dirichlet Process based on Stick-Breaking (DPSB) model-based clustering algorithm was instigated to Hyperion remote sensing imagery to map alteration minerals related to porphyry copper deposit. The DPSB clustering results were evaluated using Normalized Information Distance (NID), Normalized Mutual Information (NMI) and Modified adjusted Rand index (MARI) methods. Comparing the DPSB results with the geological map of the study area reveals the MARI of 0.2253, NMI of 0.1799 and MARI of 0.2253, respectively. To verify the extent of propylitic, argillic, advanced argillic, propylitic-argillic and sericite alteration zones associated with porphyry copper deposit, a total number of 24 rock samples were measured by a SVC XHR-1024i field portable spectroradiometer. Results derived from the DPSB model-based clustering algorithm show high accuracy in distinguishing propylitic, argillic, advanced argillic, propylitic-argillic and sericite alteration zones. It is advocated that the DPSB model-based clustering algorithm can be broadly implemented to hyperspectral and multispectral remote sensing data for detecting alteration zones associated with porphyry mineralization systems in other metallogenic provinces around the world. |
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| AbstractList | The Dirichlet Process based on Stick-Breaking (DPSB) model-based clustering algorithm was instigated to Hyperion remote sensing imagery to map alteration minerals related to porphyry copper deposit. The DPSB clustering results were evaluated using Normalized Information Distance (NID), Normalized Mutual Information (NMI) and Modified adjusted Rand index (MARI) methods. Comparing the DPSB results with the geological map of the study area reveals the MARI of 0.2253, NMI of 0.1799 and MARI of 0.2253, respectively. To verify the extent of propylitic, argillic, advanced argillic, propylitic-argillic and sericite alteration zones associated with porphyry copper deposit, a total number of 24 rock samples were measured by a SVC XHR-1024i field portable spectroradiometer. Results derived from the DPSB model-based clustering algorithm show high accuracy in distinguishing propylitic, argillic, advanced argillic, propylitic-argillic and sericite alteration zones. It is advocated that the DPSB model-based clustering algorithm can be broadly implemented to hyperspectral and multispectral remote sensing data for detecting alteration zones associated with porphyry mineralization systems in other metallogenic provinces around the world. |
| Author | Yousefi, Mastoureh Pradhan, Biswajeet Tabatabaei, Seyed Hassan Pour, Amin Beiranvand |
| Author_xml | – sequence: 1 givenname: Mastoureh surname: Yousefi fullname: Yousefi, Mastoureh organization: Isfahan University of Technology,Department of Mining Engineering,Isfahan,Iran,8415683111 – sequence: 2 givenname: Seyed Hassan surname: Tabatabaei fullname: Tabatabaei, Seyed Hassan organization: Isfahan University of Technology,Department of Mining Engineering,Isfahan,Iran,8415683111 – sequence: 3 givenname: Amin Beiranvand surname: Pour fullname: Pour, Amin Beiranvand organization: Institute of Oceanography and Environment (INOS), Universiti Malaysia Terengganu (UMT),Kuala Nerus,Terengganu,Malaysia,21030 – sequence: 4 givenname: Biswajeet surname: Pradhan fullname: Pradhan, Biswajeet organization: Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney,Faculty of Engineering & IT,NSW,Australia,2007 |
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| Snippet | The Dirichlet Process based on Stick-Breaking (DPSB) model-based clustering algorithm was instigated to Hyperion remote sensing imagery to map alteration... |
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| SubjectTerms | Alteration minerals Clustering algorithms Copper Data models DPSB Hyperion Mineral exploration Mineralization Remote Sensing Rocks Spectroradiometers Static VAr compensators |
| Title | DPSB model-based clustering algorithm for mineral mapping in hyperspectral imagery |
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