• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Korean Journal of Soil Science and Fertilizer
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• v.25 no.3
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• pp.202-212
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• 1992

This study reports on the genesis and mineralogical characteristics of the clay minerals in the soils derived from the five major parent rocks of granite, granite-gneiss, limestone, shale, and basalt in Korea. The investigation on the mineralogical aspects of primary and secondary minerals of the rocks and coarse fractions in the soils have been already reported. In this report, the identification of clay minerals in the soil clay fractions was done through the analyses of chemical, X-ray diffraction, and thermal methods. The studies showed clearly that much of the clay minerals was evolved by the weathering of primary minerals and some were further developed by the transformation of secondary minerals. Cation exchange capacity(CEC) of the clay fractions increased with higher amotunts of vermiculite, chlorite, and illite, however, decreased with higher hydroxy octahedral sheet within the interlayer spaces of vermiculite even if dominant clay with vermiculite. Feldspars in the granite and granite-gneiss might be completely transformed to kaolin mineral, Illite, chlolrite, and vermiculite formed by the alteration of micas, amphibole, augite, and primary chlorile seem to be subsequently transformed to the mixed layer minerals such as illite/vermiculite, illite/chlorite, and chlorite/vermiculite. These weathering products may be ultimately transformed into kaolin minerals. The smectite minerals in the clay fractions of the soils developed on the limestone are considerably present and they seem to be formed directly by the precipitation from high Mg solution and/or by the transformation of vermiculite from micas and chlorite in the parent materials. Abundant presence of illite in the soil clays developed on the shale is considered to have inherited from the fine particles and more resistant hydrous muscovite. The weathering sequences of the hydrous muscovite were as follows according to the degree of soil development ; hydrous muscovite ${\rightarrow}$ illite/vermiculite mixed layer(Inceptisols, Daegu series) and hydrous muscovite ${\rightarrow}$ illite/vermiculite mixed layer ${\rightarrow}$ vermiculite ${\rightarrow}$ kaolin mineral(Alfisols, Buyeo series). The plagioclase in the basalt might be mostly weathered to kaolin minerais. The augite in the basalt is likely to be transformed through progressive stage of weathering, augite ${\rightarrow}$ chlorite ${\rightarrow}$ chlorote/vermiculite mixed layer ${\rightarrow}$ vermiculite ${\rightarrow}$ kaolin. Another weathering sequence of augite could be expected, augite ${\rightarrow}$ chlorite ${\rightarrow}$ illite by the presence of illite and illite/vermiculite mixed layer in the clay fractions. Vermiculite and gibbsite were quantified from thermogravimetry(TG) and kaolin minerals, from both TG and differerential thermal analysis (DTA). Vermiculite in Jangseong series from the limestone was the dominant clay mineral of 21.7 percent and had a range in the order of 9.2 percent in Buyeo series to 5.4 percent in Daegu series from the shale. The rest soils ranged from 8.8 to 28.3 percent. Kaolin minerals were the dominant clay mineral of 32.7 percent in Asan series from the granite-gneiss and Gueom series of 32.0 percent from the basalt. The soils from the limestone ranged from 9.4 to 14.9 percent. The rest soils ranged from 8.9 to 28.6 percent. Gibbsite were 3.9 and 2.3 percent for Weoljeong and Chahang series from the granite, respectively. In Asan and Cheongsan series from the giranite-gneiss were 1.4 and 4.5 percent, respectively, and 3.6 percent in Jangpa series from the basalt.

• Journal of the Korean Society of Groundwater Environment
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• v.7 no.3
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• pp.103-115
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• 2000

The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.