This study introduced a detection method for magnesite and associated gangue minerals, including dolomite, calcite, and talc, based on mineralogical, chemical, and hyperspectral analyses using hand samples from thirteen different source locations and Specim hyperspectral short wave infrared (SWIR) hyperspectral images. Band ratio methods and logistic regression models were developed based on the spectral bands selected by the random forest algorithm. The mineralogical analysis revealed the heterogeneity of mineral composition for naturally occurring samples, showing various carbonate and silicate minerals as accessory minerals. The Mg and Ca composition of magnesite and dolomite varied significantly, inferring the mixture of minerals. The spectral characteristics of magnesite and associated gangue minerals showed major absorption features of the target minerals mixed with the absorption features of accessory carbonate minerals and talc affected by mineral composition. The spectral characteristics of magnesite and dolomite showed a systematic shift of the Mg-OH absorption features toward a shorter wavelength with an increased Mg content. The spectral bands identified by the random forest algorithm for detecting magnesite and gangue minerals were mainly associated with spectral features manifested by Mg-OH, CO₃, and OH. A two-step band ratio classification method achieved an overall accuracy of 92% and 55.2%. The classification models developed by logistic regression models showed a significantly higher accuracy of 98~99.9% for training samples and 82–99.8% for validation samples. Because the samples were collected from heterogeneous sites all over the world, we believe that the results and the approach to band selection and logistic regression developed in this study can be generalized to other case studies of magnesite exploration.

Numerous reports have successfully detected or differentiated carbonate minerals such as calcite and dolomite by using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). However, there is a need to determine whether existing methods can differentiate magnesite from other carbonate minerals. This study proposes optimal band ratio combinations and new thresholds to distinguish magnesite, dolomite, and calcite using ASTER shortwave-infrared (SWIR) data. These were determined based on the spectral and chemical analysis of rock samples collected from Liaoning, China and Danchon, North Korea and the reflectance values from ASTER images. The results demonstrated that the simultaneous use of thresholds 2.13 and 2.015 for relative absorption band depths (RBDs) of (6 + 8)/7 and (7 + 9)/8, respectively, was the most effective for magnesite differentiation. The use of RBDs and band ratios to discriminate between dolomite and calcite was sufficiently effective. However, talc, tremolite, clay, and their mixtures with dolomite and calcite, which are commonly found in the study area, hampered the classification. The assessment of the ASTER band ratios for magnesite grade according to magnesium oxide content indicated that a band ratio of 5/6 was the most effective for this purpose. Therefore, this study proved that ASTER SWIR data can be effectively utilized for the identification and grade assessment of magnesite on a regional scale.

The axinite-bearing Gukjeon Pb–Zn deposit is hosted by the limestone, a member of the Jeonggaksan Formation, which, in turn, forms the part of the Jusasan subgroup of the Yucheon Group in the Gyeongsang Basin in the southeastern part of the Korean Peninsula. In this study, we attempted to interpret the spatial and temporal relationships among geologic events, including the mineralization of this deposit. We constructed a new 3D orebody model and suggested a relationship between skarn alteration and related mineralization. Mineralization timing was constrained using SHRIMP zircon age dating results combined with boron geochemistry on coeval intrusive rocks. Skarn alterations are restrictively found in several horizons of the limestone formation. The major skarn minerals are garnet (grossular), pyroxene (hedenbergite), amphibole (actinolite and ferro-actinolite), axinite (tizenite and ferro-axinite), and epidote (clinozoisite and epidote). The three stages of pre-skarn, syn-skarn, and post-skarn alteration are recognized within the deposit. The syn-skarn alteration is characterized by prograde metasomatic pyroxene and garnet, and the retrograde metasomatic amphibole, axinite, and epidote. Major skarn sulfide minerals are sphalerite, chalcopyrite, galena, and pyrite, which were predominantly precipitated during the retrograde stage and formed amphibole and axinite skarns. The skarn orebodies seem to be disc- or flat-shaped with a convex form at the central part of the orebodies. The vertical ascending and horizontal infiltration of boron-rich hydrothermal fluid probably controlled the geometry of the orebodies. Considering the whole-rock major, trace, and boron geochemical and geochronological results, the timing of Pb–Zn mineralization can be tightly constrained between the emplacement of boron-poor intrusion (fine-grained granodiorite, 82.8 Ma) and boron-rich intrusion (porphyritic andesite in Beomdori andesitic rocks, 83.8 Ma) in a back-arc basin setting. The boron for mineralization was sourced from late Cretaceous (Campanian), subduction-related magmatic rocks along the margin of the Pacific plate.

지상기반 초분광 영상 기술을 이용해 경기광업과 가사리 탄산염암 노두를 대상으로 광물 탐지 성능을 평가하고 광물 분포도를 작성하였다. 연속체 제거 기법은 CO₃, Al-OH에 의한 광물 고유의 흡수 특징을 쉽고 빠르게 탐지할 수 있었지만 세분화된 광물 분류는 어려웠다. 반면 다중 범위 분광특징근사 기법은 백운석, 방해석, 마그네사이트와 같은 탄산염 광물들 뿐만 아니라 고령석, 일라이트와 같은 층상 규산염 광물들을 세부적으로 분류할 수 있었다. 현장 관찰과 암석시료에 대한 X선 회절 분석 및 분광측정 결과들은 초분광 영상을 이용한 탄산염 광물 분류 결과에 대한 높은 정확도를 보여준다. 초분광 영상으로부터 획득되는 분광학적 특징들은 탄산염 광물의 유기물 함량, 입자크기, 분급, 다공성과 같은 물리적, 화학적 특성과 관련이 있기 때문에 초분광 영상기술은 탄산염 노두를 해석하는데 있어 현장 관찰과 화학분석과 같은 전통적 탐사기법과 함께 상호보완적으로 활용될 수 있을 것이다. 지상기반 초분광 영상 기술은 특히 직접적인 조사가 어려운 높은 수직 노두에 대해 광물 정보를 얻거나 층서 및 구조 분석과 관련된 지질매핑이나 해석을 할 때 효과적으로 사용 될 수 있을 것으로 보인다.