Abstract
Abstract. Nowadays, remote sensing technologies are playing a significant role in mineral potential mapping. To optimize the exploration approach along with a cost-effective way, narrow down the target areas for a more detailed study for mineral exploration using suitable data selection and accurate data processing approaches are crucial. To establish optimum procedures by integrating space-borne remote sensing data with other earth sciences data (e.g., airborne magnetic and electromagnetic) for exploration of Iron Oxide Copper Gold (IOCG) mineralization is the objective of this study. Further, the project focus is to test the effectiveness of Copernicus Sentinel-2 data in mineral potential mapping from the high Arctic region. Thus, Inglefield Land from northwest Greenland has been chosen as a study area to evaluate the developed approach. The altered minerals, including irons and clays, were mapped utilizing Sentinel-2 data through band ratio and principal component analysis (PCA) methods. Lineaments of the study area were extracted from Sentinel-2 data using directional filters. Self-Organizing Maps (SOM) and Support Vector Machines (SVM) were used for classification and analysing the available data. Further, various thematic maps (e.g., geological, geophysical, geochemical) were prepared from the study area. Finally, a mineral prospectively map was generated by integrating the above mentioned information using the Fuzzy Analytic Hierarchy Process (FAHP). The prepared potential map for IOCG mineralization using the above approach of Inglefield Land shows a good agreement with the previous geological field studies.
Highlights
1.1 Mineral explorationMineral exploration is performed with the objective of finding ore deposits in commercially viable concentrations and is often a sequential process of information gathering and interpretation
Airborne geophysical data, geochemical data and geological field observation data are transferred into a common geo database in order to prepare for application of data integration techniques
By applying a linear transformation, this technique reduces the redundancy of correlated data and transforms a set of correlated input bands into uncorrelated principal components (PCs)
Summary
Mineral exploration is performed with the objective of finding ore deposits in commercially viable concentrations and is often a sequential process of information gathering and interpretation. Geophysical, geochemical and geological field work and associated data processing and interpretation constitute major parts of the expenses prior to any decision on drilling and mining activities. Satellite based remote sensing data may provide information for planning of more optimised field work as well as aid the interpretations. Availability of various remote sensing datasets (e.g., NASA’s Landsat series (1-8) and ASTER, ESA’s Sentinel series (1 to 5)) with low or no cost are playing key role to narrow down and target the potential areas in mineral exploration. This study is focusing on the use of Copernicus Sentinel-2 data for mineral exploration. The interpretations involve integration of the remote sensing data with airborne geophysical data
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