Fusion of Remote Sensing, Magnetometric, and Geological Data to Identify Polymetallic Mineral Potential Zones in Chakchak Region, Yazd, Iran

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, geophy...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2022-12, Vol.14 (23), p.6018
Main Authors: Aali, Ali Akbar, Shirazy, Adel, Shirazi, Aref, Pour, Amin Beiranvand, Hezarkhani, Ardeshir, Maghsoudi, Abbas, Hashim, Mazlan, Khakmardan, Shayan
Format: Article
Language:English
Subjects:
Copper
data fusion
Depletion
Drilling
Fault detection
Fuzzy logic
Geographic information systems
geological data
Geologists
Geology
Geophysics
Iran
Landsat
Lithology
Low cost
magnetometry
Mineral deposits
Mineral exploration
Mineralization
Modelling
polymetallic mineralization potential mapping
Provinces
Remote sensing
Sediments
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Summary: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.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14236018