EXPLORATION OF IOCG MINERALIZATIONS USING INTEGRATION OF SPACE-BORNE REMOTE SENSING DATA WITH AIRBORNE GEOPHYSICAL DATA
| Autor: | Mahendra K. Pal, Thorkild Maack Rasmussen, Mehdi Abdolmaleki |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
lcsh:Applied optics. Photonics
020301 aerospace & aeronautics Data processing 010504 meteorology & atmospheric sciences Lineament Exploration geophysics lcsh:T lcsh:TA1501-1820 02 engineering and technology Geophysics lcsh:Technology 01 natural sciences Support vector machine Mineral exploration Thematic map 0203 mechanical engineering Arctic lcsh:TA1-2040 Principal component analysis lcsh:Engineering (General). Civil engineering (General) Geology 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2020, Pp 9-16 (2020) |
| ISSN: | 2194-9034 |
| DOI: | 10.5194/isprs-archives-xliii-b3-2020-9-2020 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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