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Indicator mineral mapping for geothermal sites using multi/hyperspectral imagery
Erika
Erika
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2022
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Abstract
Geothermal energy plays an important role as a sustainable energy. In order to meet the future energy demand, more geothermal resources and utilization are needed. However, the geothermal industry is not only capital-intensive, but also has high uncertainty which needs management of high financial and technical risks. Conducting exploration to obtain sufficient information before starting or developing the project is one of the effective risk management phases.
A crucial component in geothermal exploration is mineral mapping, where the occurrence of minerals in all areas of a prospective geothermal site is mapped and used as the basis for delimiting the prospective area. Remote sensing is an effective tool for mineral mapping in the preliminary survey stage, when the target area is very large.
In this thesis, performance of remote sensing analysis conducted for ASTER, Landsat-8, Sentinel-2, and HyMap images in geothermal mineral mapping is evaluated. Eight types of target detection algorithms namely, Adaptive Coherence Estimator (ACE), Constrained Energy Minimization (CEM), Match Filtering (MF), Orthogonal Subspace Projection (OSP), Spectral Angle Mapper (SAM), Mixture Tuned Match Filtering (MTMF), Target Constrained Interference Minimized Filter (TCIMF), and Mixture Tuned Target Constrained Interference Minimized Filter (MTTCIMF ) are applied to each satellite imagery to compare different satellite imagery and the algorithms` performance to create the best mineral mapping for geothermal resource exploration. Then a set of guidelines are developed for indicator mineral mapping using satellite images for geothermal sites.
It is found that CEM, MF, TCIMF, MTTCIMF, and MTMF perform well for the images containing abundance of human-made structures (e.g. roads, buildings). On the other hand, SAM and OSP perform better for the images with limited coverage of human-made structures. HyMap is used for ground truthing due to its high spatial and spectral resolution. Then other satellite data`s accuracy is evaluated using HyMapThe satellite data that gives better accuracy for almost every method is found to be ASTER, which is followed by Landsat-8 in the second place and Sentinel-2.
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