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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Bibliographic Details
Published in:Geocarto international Vol. 37; no. 25; pp. 9788 - 9816
Main Authors: Yousefi, Mastoureh, Tabatabaei, Seyed Hassan, Rikhtehgaran, Reyhaneh, Pour, Amin Beiranvand, Pradhan, Biswajeet
Format: Journal Article
Language:English
Published: Taylor & Francis 13.12.2022
Subjects:
algorithms
Alteration zones
case studies
DPSB
hyperion
Iran
mineralization
porphyry copper systems
remote sensing
SAM
Iran
ISSN:1010-6049, 1752-0762, 1752-0762
Online Access:Get full text
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Summary: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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ISSN:1010-6049
1752-0762
1752-0762
DOI:10.1080/10106049.2022.2025917