Hydrothermally altered areas forming pyrophyllite-kaolin-sericite-alunite deposits are distributed in Chonnam and Kyongsang areas, Cretaceous volcanic field of the Yuchon Group. The Chonnam alteration area is located within depression zone which is composed of volcanic and granitic rocks of late Cretaceous age. The clay deposits of this area show the genetic relationship with silicic lava domes. The Kyongsang alteration area is mainly distributed within Kyongsang Basin comprising volcanic, sedimentary and granitic rocks of Cretaceous and Tertiary age. Most of the clay deposits of this area are closely related to cauldrons. Paleozoic clay deposit occurs in the contact zone between Precambrian Hongjesa granite gneiss and Paleozoic Jangsan quartzite of Choson Supergroup. Cretaceous igneous rocks of the both alteration areas belong to high K calc-alkaline series formed in the volcanic arc of continental margin by subduction-related magmatism. Chonnam igneous rocks show more enrichment of crustal components such as K, La, Ce, Sm, Nd and Ba, higher (La/Yb)cn ratio, and higher initial ⁸⁷Sr/⁸⁶Sr ratio (0. 708 to 0. 712) than those of Kyongsang igneous rocks. This might be due to the difference of degree of crustal contamination during Cretaceous magmatism. The most characteristic alteration minerals of Chonnam clay deposits are alunite, kaolin, quartz, pyrophyllite and diaspore which were formed by acidic solution. Those of Kyongsang clay deposits are sericite, quartz and pyrophyllite which were formed by weak acid and neutral solution. The formation ages of the clay deposits of two alteration areas range from 70. 1 to 81. 4 Ma and 39. 7 to 79. 4 Ma, respectively. The Daehyun clay deposit in Ponghwa area of Kyongsang province shows the alteration age range from 290 to 336 Ma. This result shows the different alteration episode from the hydrothermal alteration of Cretaceous to early Tertiary in the Kyongsang and Chonnam alteration areas. These data indicate, at least, three hydrothermal activities of Tertiary (middle to late Eocene), late Cretaceous (Santonian to Maastrichtian) and Paleozoic Carboniferous Periods in South Korea.

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.

Hydrothermal deposits in the Gyeongsang Basin show the genetic relationship with igneous activity from Late Cretaceous to Early Tertiary in the spatial and temporal viewpoints. Many hydrothermal Au‐Ag‐Cu‐Pb‐Zn and clay deposits are dominantly distributed within the Gyeongsang Basin. The Gyeongsang Basin is divided into seven metallogenic provinces by spatial distribution. The age ranges of igneous activity and mineralization are 140∼40 Ma and 100∼40 Ma, respectively, and the most dominant age ranges of the both activities are from 90 Ma (Coniacian) to 50 Ma (Eocene). The age consistency between igneous activity and mineralization suggests that this age range is the climactic period of the hydrothermal activity of the Gyeongsang Basin. The metallogenic epochs in the Gyeongsang Basin are divided into three epochs of 100∼80 Ma (western part of the Gyeongsang Basin), 80∼60 Ma (central part of the Gyeongsang Basin), and 60∼40 Ma (eastern part of the Gyeongsang Basin). The mineralization and igneous activity tend to become young eastward in the Gyeongsang Basin.NNW‐SSE mineralized veins from 100 to 80 Ma in the western part of the Gyeongsang Basin are interpreted as the control of the parallel tensional fissures caused by NNW‐SSE compressional stress. NW‐SE mineralized veins from 80 to 60 Ma in the central part of the Gyeongsang Basin seem to have been formed under the same stress as that of the Gaeum and Yangsan Fault Systems. Namely, NW‐SE tensional stress is associated with a conjugate set of fracturing of the WNW‐ESE Gaeum Fault System and NNE‐SSW Yangsan Fault System. Also NE‐SW mineralized veins from 60 to 40 Ma in the eastern part of the Gyeongsang Basin seem to be controlled by the NE‐SW fractures. The fractures are related with NE‐SW compressional stress and are developed as secondary fractures within the dextral strike slip Yangsan Fault System.

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 spectral response to arsenic (As) stress of pine needles (Pinus densiflora Siebold and Zucc.) from an abandoned lead (Pb)–zinc (Zn) mine was investigated based on chemical and spectroscopic analyses. The correlation analysis between the content of As in needle samples and that of soils and spectral parameters of the needle samples were conducted. The results showed very high correlation between As content in pine needles and soils. The major spectral response of pine needles to the As stress were characterized by the increase in the green and red color reflectance, the decrease in the first derivatives at 1648 nm, and the shrink in the red absorption feature. These changes were caused by the pigment content loss and the structural changes of phenolic compounds in the pine needles due to the As content. The linear regression analysis with the stepwise method showed the first derivatives at 668 nm and 1648 nm were the most useful variables in the regression model for As content prediction in pine needles. The As index of pine needles could be used to detect As content in soils associated with As and heavy metals contamination and/or mineralization in coniferous forests.

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