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Geothermal Surface Manifestation Identification Using Airborne Hyperspectral Imagery Case Study: Davis-Schrimpf Geothermal Field, Salton Sea, California Izzul Qudsi; Muhammad Rifat Noor
Indonesian Journal on Geoscience Vol 9, No 1 (2022)
Publisher : Geological Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17014/ijog.9.1.119-130

Abstract

DOI:10.17014/ijog.9.1.119-130Research on surface geothermal evidence has been done extensively using remote sensing techniques. For detailed remote sensing exploration on geothermal areas, UAV and airborne based were preferred over the satellite-based sensor. In this research, anomalies in surface temperature, mineral occurrence, and ammonia emission were studied on a set of airborne hyperspectral imagery from NASA, the Hyperspectral Thermal Emission Spectrometer (HyTES). High-resolution surface temperature and mineral maps were able to identify and describe the mineralogy of the mud pots and gryphons at the Davis-Schrimpf Geothermal Field, Salton Sea, California. From the surface temperature map, the surface temperature of the geothermal features was measured at approximately 314°K (40oC) and higher. The purest pixels from MNF transformation of the first four cleanest bands of emissivity map produce endmembers that include the geothermal indicator minerals (barite, anhydrite, quartz, gypsum). Based on the mineralogy deposits, these manifestations are classified as potassic alteration types from a porphyry system that could be an indication of an active geothermal system. This also explains that the surface features are part of the upper reservoir of the Salton Sea Geothermal Field. On the other hand, ammonia detection that was performed in this research failed to get any clear recognition from the simple image processing. It is concluded that the airborne hyperspectral imagery could be a reliable option for remote sensing geothermal exploration, as it was able to characterize the surface geothermal manifestation with quite good detail using this imagery from a wide area of survey.
Mineral Mapping on Hyperspectral Imageries Using Cohesion-based Self Merging Algorithm Afnindar Fakhrurrozi; Izzul Qudsi; Mochamad Rifat Noor; Anggun Mayang Sari
Jurnal Elektronika dan Telekomunikasi Vol 22, No 2 (2022)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/jet.507

Abstract

Recently, hybrid clustering algorithms gained much research attention due to better clustering results and are computationally efficient. Hyperspectral image classification studies should be no exception, including mineral mapping. This study aims to tackle the biggest challenge of mapping the mineralogy of drill core samples, which consumes a lot of time. In this paper, we present the investigation using a hybrid clustering algorithm, cohesion-based self-merging (CSM), for mineral mapping to determine the number and location of minerals that formed the rock. The CSM clustering performance was then compared to its classical counterpart, K-means plus-plus (K-means++). We conducted experiments using hyperspectral images from multiple rock samples to understand how well the clustering algorithm segmented minerals that exist in the rock. The samples in this study contain minerals with identical absorption features in certain locations that increase the complexity. The elbow method and silhouette analysis did not perform well in deciding the optimum cluster size due to slight variance and high dimensionality of the datasets. Thus, iterations to the various numbers of k-clusters and m-subclusters of each rock were performed to get the mineral cluster. Both algorithms were able to distinguish slight variations of absorption features of any mineral. The spectral variation within a single mineral found by our algorithm might be studied further to understand any possible unidentified group of clusters. The spatial consideration of the CSM algorithm induced several misclassified pixels. Hence, the mineral maps produced in this study are not expected to be precisely similar to ground truths.
Geothermal Surface Manifestation Identification Using Airborne Hyperspectral Imagery Case Study: Davis-Schrimpf Geothermal Field, Salton Sea, California Izzul Qudsi; Muhammad Rifat Noor
Indonesian Journal on Geoscience Vol. 9 No. 1 (2022)
Publisher : Geological Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17014/ijog.9.1.119-130

Abstract

DOI:10.17014/ijog.9.1.119-130Research on surface geothermal evidence has been done extensively using remote sensing techniques. For detailed remote sensing exploration on geothermal areas, UAV and airborne based were preferred over the satellite-based sensor. In this research, anomalies in surface temperature, mineral occurrence, and ammonia emission were studied on a set of airborne hyperspectral imagery from NASA, the Hyperspectral Thermal Emission Spectrometer (HyTES). High-resolution surface temperature and mineral maps were able to identify and describe the mineralogy of the mud pots and gryphons at the Davis-Schrimpf Geothermal Field, Salton Sea, California. From the surface temperature map, the surface temperature of the geothermal features was measured at approximately 314°K (40oC) and higher. The purest pixels from MNF transformation of the first four cleanest bands of emissivity map produce endmembers that include the geothermal indicator minerals (barite, anhydrite, quartz, gypsum). Based on the mineralogy deposits, these manifestations are classified as potassic alteration types from a porphyry system that could be an indication of an active geothermal system. This also explains that the surface features are part of the upper reservoir of the Salton Sea Geothermal Field. On the other hand, ammonia detection that was performed in this research failed to get any clear recognition from the simple image processing. It is concluded that the airborne hyperspectral imagery could be a reliable option for remote sensing geothermal exploration, as it was able to characterize the surface geothermal manifestation with quite good detail using this imagery from a wide area of survey.