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Fusion of remote sensing, magnetometric, and geological data to identify polymetallic mineral potential zones in Chakchak region, Yazd, Iran

Aali, Ali Akbar and Shirazy, Adel and Shirazi, Aref and Pour, Amin Beiranvand and Hezarkhani, Ardeshir and Maghsoudi, Abbas and Hashim, Mazlan and Khakmardan, Shayan (2022) Fusion of remote sensing, magnetometric, and geological data to identify polymetallic mineral potential zones in Chakchak region, Yazd, Iran. Remote SensingVolume , Issue, 14 (23). pp. 1-24. ISSN 2072-4292

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Official URL: http://dx.doi.org/10.3390/rs14236018

Abstract

Exploration geologists are urged to develop new, robust, and low-cost approaches to identify high potential zones related to underground/unexplored mineral deposits because of increased depletion of ore deposits and high consumption of basic metal production industries. Fusing remote sensing, geophysical and geological data has great capability to provide a complete range of prerequisite data to accomplish this purpose. This investigation fuses remote sensing data, such as Sentinel-2 and Landsat 7, aerial magnetic geophysical data, and geological data for identifying polymetallic mineralization potential zones in the Chakchak region, Yazd province, Iran. Hydrothermal alteration mineral zones and surface and deep intrusive masses, hidden faults and lineaments, and lithological units were detected using remote sensing, aerial magnetic, and geological data, respectively. The exploratory/information layers were fused using fuzzy logic modeling and the multi-class index overlap method. Subsequently, mineral potential maps were generated for the study area. Some high potential zones of polymetallic mineralization were identified and verified through a detailed field campaign and drilling programs in the Chakchak region. In conclusion, the fusion of remote sensing, geophysical, and geological data using fuzzy logic modeling and the multi-class index overlap method is a robust, reliable, and low-cost approach for mining companies to explore the frontier areas with identical geologic conditions that are alleged to indicate polymetallic mineralization potential.

Item Type:Article
Uncontrolled Keywords:data fusion, geological data, Iran, magnetometry, polymetallic mineralization potential mapping, remote sensing
Subjects:G Geography. Anthropology. Recreation > G Geography (General) > G70.39-70.6 Remote sensing
Divisions:Built Environment
ID Code:98971
Deposited By: Widya Wahid
Deposited On:22 Feb 2023 02:51
Last Modified:22 Feb 2023 02:51

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