• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.83-92
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• 2019

Land cover (LC) is an important factor in socioeconomic and environmental studies. According to various studies, a number of LC maps, including global land cover (GLC) datasets, are made using polar orbit satellite data. Due to the insufficiencies of reference datasets in Northeast Asia, several LC maps display discrepancies in that region. In this paper, we performed a feasibility assessment of LC mapping using Geostationary Ocean Color Imager (GOCI) data over Northeast Asia. To produce the LC map, the GOCI normalized difference vegetation index (NDVI) was used as an input dataset and a level-2 LC map of South Korea was used as a reference dataset to evaluate the LC map. In this paper, 7 LC types(urban, croplands, forest, grasslands, wetlands, barren, and water) were defined to reflect Northeast Asian LC. The LC map was produced via principal component analysis (PCA) with K-means clustering, and a sensitivity analysis was performed. The overall accuracy was calculated to be 77.94%. Furthermore, to assess the accuracy of the LC map not only in South Korea but also in Northeast Asia, 6 GLC datasets (IGBP, UMD, GLC2000, GlobCover2009, MCD12Q1, GlobeLand30) were used as comparison datasets. The accuracy scores for the 6 GLC datasets were calculated to be 59.41%, 56.82%, 60.97%, 51.71%, 70.24%, and 72.80%, respectively. Therefore, the first attempt to produce the LC map using geostationary satellite data is considered to be acceptable.

• Economic and Environmental Geology
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• v.25 no.3
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• pp.317-336
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• 1992

The garden soils, main road dusts, residential road dusts, and playground soils/dusts of Seoul, Geumsan, Onsan, and Taebaek areas were analyzed in order to investigate the level of heavy metal pollution by urbanization and industrialization. The soil pH is in the range of 5.48~8.40 and was generally neutral. The color of soils and dusts is mainly Raw Umber to dark greyish Raw Umber. Some samples from Taebaek city, a coal mining area, showed a deep black color due to contamination by coal dusts. Major minerals of the dusts and soils are quartz, feldspars, and micas, reflecting the composition of the parent rocks. However, pyrite was found as a major mineral in the samples of industrial road dusts of Onsan, a smelting area, and resicential road dusts of Taebaek. Thus, the high level of heavy metals in mining and smelting areas can be explained with the sulfide minerals. The mode of occurences of heavy metals in Seoul, a comprehensive urbanized area, were related to the metallic pollutants and organic materials through observation by scanning eletron microscopy. In main road and residential road dusts of Onsan area, Cd, Zn, and Cu were extremely high. Some industrial road and residential road dusts of Seoul area showed high Cu, Zn, and Pb contents, wereas some garden soils and residential road dusts of Taebaek area were high in As content. In general, the heavy metal contents in dust samples were two to three times higher than those in soil samples. Main road dust samples were the most reflective from the discriminant analysis of multi-element data. Cadmium, Sb, and Se in Onsan area, As in Taebaek area, Pb and Te in Seoul area were most characteristic in discriminating the studied areas. Therefore, Cd in smelting areas, As in coal mining areas, and Pb in metropolitan areas can be suggested as the characteristic elements of each pollution pattern. The dispersion of heavy metal elements in urban areas tends to orignate in main roads and deposit in garden soils through the atmosphere and residential roads. The heavy metal contamination in Seoul is characteristic in areas with high population, factory, road, and traffic decsities. Heavy metal contents are high in the vicinity of smelters in Onsan area and are decayed to background levels from one kilometer away from the smelters.

• Journal of Environmental Impact Assessment
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• v.32 no.3
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• pp.166-175
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• 2023

This study aims to identify the cause of the red-water occurrence (the phenomenon of water being red) that occurs at some points and sections of rivers in Yongin City. As a result of conducting a preliminary investigation, total three sites were selected as the investigation point as it was found that the red-water occurrence continued. As a result of the investigation, it is judged that the cause of the red-water in Yongin-city river is due to the soil color and iron content of the region. JPS, SBS, and JJS sites all showed that the color of soil is mainly consist of reddish brown and red-yellow. The average Fe concentration was 13.75 mg/L, 10.85 mg/L, and 1.31 mg/L, for each sites, and considering that the Fe concentration in general river water was less than 0.5 mg/L, it was confirmed that the concentration was quite high. At the JPS and JJS points, the red-water occurrence occurred mainly in stagnant places, which is believed to be strengthened by the reaction of organic and microorganisms. In the case of SBS, the wateris red, but as a result of observing the actual color, it is judged that the iron component deposited in the pipe causes an optical illusion with a deep red color. In addition, it is believed that the iron concentration can be reduced to the general river water concentration range by removing the particulate iron component through a decrease of more than 95% as a result of filtering with glass fiber filter with particulate iron. As a result of this study, it is necessary to manage the river to maintain the flow, and it is believed that the occurrence of red-water at the survey point can be alleviated through uptake action through planting and agglomeration precipitation and agglomeration filtration methods for particulate iron treatment.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.2
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• pp.16-24
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• 2002

Classification of the land cover characteristics is a major application of remote sensing. The goal of this study is to propose an optimal classification process for electro-optical camera(EOC) of Korea Multi-Purpose Satellite(KOMPSAT). The study was carried out on Landsat TM, high spectral resolution image and KOMPSAT EOC, high spatial resolution image of Miho river basin, Korea. The study was conducted in two stages: one was image fusion of TM and EOC to gain high spectral and spatial resolution image, the other was land cover classification on fused image. Four fusion techniques were applied and compared for its topographic interpretation such as IHS, HPF, CN and wavelet transform. The fused images were classified by radial basis function neural network(RBF-NN) and artificial neural network(ANN) classification model. The proposed RBF-NN was validated for the study area and the optimal model structure and parameter were respectively identified for different input band combinations. The results of the study propose an optimal classification process of KOMPSAT EOC to improve the thematic mapping and extraction of environmental information.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.153-170
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• 2013

This study was conducted to analyze the thermal comfort in the urban neighborhood park and to obtain a plan for improvement of the thermal environment. First, in the result of the analysis of the distribution characteristics of the park's main thermal environment factors and differences among types of space, temperature, relative humidity, and wind speed did not show a clear difference spatially. However, the median radiant temperature showed great differences according to the openness of the space and the covering material. According to the evaluation of thermal comfort by types of space based on derived thermal environmental factors, the PMV value of the square was the highest at 4.39, the paths showed 2.58, greenery 1.90, and resting spaces 0.42. In the result of the PMV regression model established for the evaluation of the significance of these thermal environment factors that decide thermal comfort, it showed that the relative significance to the PMV was as follows in decreasing order: median radiant temperature(1.084), wind speed(-0.280), temperature(0.013), and relative humidity(-0.009). When conducting a scenario analysis on the areas with need for improvement in thermal environment, it was found that through reflectivity, color and the change in the physical properties of packing materials the thermal comfort felt by the body could be improved, and it is believed that through this the improvement plan can be established.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.8 no.5
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• pp.10-18
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• 2005

The research was carried out to define the morphological and growth characteristics of Poa pratensis L.(Kentucky bluegrass) 'Sewon' in native to Korea. Poa pratensis 'Sewon' was collected at the terrace land on the river in Guiman-ri, Cheongcheon-myeon, Goesan-gun, Chungcheongbuk-do on May 5, 1995. The collected Poa pratensis 'Sewon' was grown under non-mowing naturally growing condition. The morphological characteristics of Poa pratensis 'Sewon' are as follows. : The height of plant was 21.6cm but was increased to 33cm at the flowering time. The height of first node from the base was 5.0cm and the length and width of leaf were 9.6cm and 4.1cm, respectively. The length of inflorecences was 37.8cm and the length of a spike was 7.3cm. Based on these morphological characteristics, Poa pratensis 'Sewon' was defined to dwarf~medium and coarse texture type Kennturky bluegrass. 1 to 9 scale of visual quality, visual color and visual density were measured. Poa pratensis 'Sewon' showed best turf qualities among native Kentucky bluegrasses. In spring and fall growing season, Poa pratensis 'Sewon' were measured to be excellent performances for turf qulities similar to foreign excellent quality cultivars such as Midnight, Nuglade and Brilliant Kentucky bluegrasses. But turf quality of Poa pratensis 'Sewon' decreased by plant disease according to temperature increase in summe compared to foreign excellent quality cultivars. So, Poa pratensis 'Sewon' should be improved of disease tolerent quality by incessant breeding work in order to compete foreign excellent quality cultivars.

• Journal of the Korean Solar Energy Society
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• v.30 no.3
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• pp.71-80
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• 2010

This study carried out to understand the thermal characteristics of various surface material which compose the city through the observation in the summer. To examine passive cooling effect of planting of building, it is arranged four different materials that is natural grass, grass block, concrete slab and artificial grass. The results of this study are as follows; (1) Natural grass and grass block show the lower surface temperature because of the structures of leaf can do more thermal dissipation effectively. (2) There is little surface temperature between artificial grass and concrete. But there is little high surface temperature difference between natural grass and concrete because of latent heat effect. (3) The concrete can play a role of the tropical nights phenomenon as high heat capacity of concrete compare with other materials. (4) It is nearly same color in artificial grass and natural grass but there is large difference between natural grass and artificial grass at albedo. There is different albedo in near infrared ray range. (5) A short wave radiation gives more effect at the globe temperature than long wave radiation. (6) The artificial turf protected the slab surface temperature increase in spite of thin and low albedo materials.

• Journal of Forest and Environmental Science
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• v.28 no.1
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• pp.56-62
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• 2012

There is little information about appropriate greenspace structures to satisfy aesthetic function in Korea. The purpose of this study was to analyze Korean's aesthetic preferences for greenspace structures concerned with urban tree plantings of an areal type to explore desirable greenspace landscapes. The study considered 5 structural variables of greenspace which were species composition, tree density, tree size, vertical and horizontal structure, and tree layout pattern. A photo-questionnaire was prepared through color simulations of different landscape types for each structural variable. Preference responses of an interval-scale rating from 214 respondents were statistically analyzed between landscape types and between respondent groups. Respondents preferred greenspace landscapes with diverse tree species to single species, higher tree density to lower density, larger trees to many smaller trees, multilayered and grouped plantings to single-layered and sparse plantings, and informal pattern to formal pattern. These preferences tended to be relatively higher for educated specialist and student groups than for other generalist group. Thus, multilayered and dense plantings in natural pattern including larger trees of diverse species, which are similar to ecological plantings, are recommended to increase aesthetic function of greenspace.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.