Kim, Jeong-Ho;Yun, Yong-Han;Kim, Hak-Gi;Lee, Myeong-Hun;Park, Yeong-jin;Lee, Dong-Jae;Sin, Yong-jin
Korean Journal of Environment and Ecology
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v.35
no.6
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pp.669-678
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2021
This study surveyed three land cover types in Chungju City in Chungcheongbuk Province to check the distribution of cultured bacteria in bio-aerosols according to land cover type. It was possible to compare and analyze the distribution of bacteria according to microclimatic changes at each measurement point by examining meteorological factors and bio-aerosols according to land cover. The microclimate temperature in each measurement point was 8.7℃ for the urban forest, 10.8℃ for the waterside green area, and 10.2℃ for the urban area, indicating the urban forest had the lowest temperature among the measurement points. The relative humanity was 61.8% fin the urban forest, 59.3% in the waterside green area, and 55.7% in the urban area, indicating that the urban forest was the most humid among the measurement points. The identified bacteria were found to be 43 genera and 99 species. In terms of species diversity of cultured bacteria, 22 genera were found in the waterside green area, 21 genera in the urban forest, and 17 genera in the urban area, 37 species were found in the waterside green area, 31 species in the urban area, and 31 species in the urban forest. Bacillus toyonensis and Pseudarthrobacter oxydan were the species present in all three types of measurement sites, and Herbiconiux flava was confirmed to inhabit green areas such as urban forests and waterside green areas. The analysis result of the bacterial concentration according to the microclimatic environment in each measurement point was 333 CFU/m3 in the urban forest, 287 CFU/m3, in the waterside green area, and 173 CFU/m3 in the downtown area. The relative humidity and wind speed were analyzed to show a similar trend as the concentration. This study is expected to provide basic data for healthy urban management and green area creation by identifying the distribution of cultured bacteria in bio-aerosols according to land cover type and comparing and analyzing the traits of bio-aerosol in each measurement point.
Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.
Myeong-Ju, Choi;Joong-Bae, Ahn;Young-Hyun, Kim;Min-Kyung, Jung;Kyo-Moon, Shim;Jina, Hur;Sera, Jo
Korean Journal of Agricultural and Forest Meteorology
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v.24
no.4
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pp.218-233
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2022
The long-term (1986~2020) predictability of the number of days of heat and cold damages for each growth stage of soybean is evaluated using the daily maximum and minimum temperature (Tmax and Tmin) data produced by Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF). The Predictability evaluation methods for the number of days of damages are Normalized Standard Deviations (NSD), Root Mean Square Error (RMSE), Hit Rate (HR), and Heidke Skill Score (HSS). First, we verified the simulation performance of the Tmax and Tmin, which are the variables that define the heat and cold damages of soybean. As a result, although there are some differences depending on the month starting with initial conditions from January (01RUN) to May (05RUN), the result after a systematic bias correction by the Variance Scaling method is similar to the observation compared to the bias-uncorrected one. The simulation performance for correction Tmax and Tmin from March to October is overall high in the results (ENS) averaged by applying the Simple Composite Method (SCM) from 01RUN to 05RUN. In addition, the model well simulates the regional patterns and characteristics of the number of days of heat and cold damages by according to the growth stages of soybean, compared with observations. In ENS, HR and HSS for heat damage (cold damage) of soybean have ranged from 0.45~0.75, 0.02~0.10 (0.49~0.76, -0.04~0.11) during each growth stage. In conclusion, 01RUN~05RUN and ENS of PNU CGCM-WRF Chain have the reasonable performance to predict heat and cold damages for each growth stage of soybean in South Korea.
Jonghoon Park;Sinyoung Kim;Soomin Seo;Hyun A Lee;Nam C. Woo
Economic and Environmental Geology
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v.56
no.2
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pp.139-153
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2023
This study aimed to understand the spatiotemporal variations in nitrogen content in the Gyeongan stream along the main stream and at the discharge points of the sub-basins, and to identify the origin of the nitrogen. Field surveys and laboratory analyses, including chemical compositions and isotope ratios of nitrate and boron, were performed from November 2021 to November 2022. Based on the flow duration curve (FDC) derived for the Gyeongan stream, the dry season (mid-December 2021 to mid-June 2022) and wet season (mid-June to early November 2022) were established. In the dry season, most samples had the highest total nitrogen(T-N) concentrations, specifically in January and February, and the concentrations continued to decrease until May and June. However, after the flood season from July to September, the uppermost subbasin points (Group 1: MS-0, OS-0, GS-0) where T-N concentrations continually decreased were separated from the main stream and lower sub-basin points (Group 2: MS-1~8, OS-1, GS-1) where concentrations increased. Along the main stream, the T-N concentration showed an increasing trend from the upper to the lower reaches. However, it was affected by those of the Osan-cheon and Gonjiamcheon, the tributaries that flow into the main stream, resulting in respective increases or decreases in T-N concentration in the main stream. The nitrate and boron isotope ratios indicated that the nitrogen in all samples originated from manure. Mechanisms for nitrogen inflow from manure-related sources to the stream were suggested, including (1) manure from livestock wastes and rainfall runoff, (2) inflow through the discharge of wastewater treatment plants, and (3) inflow through the groundwater discharge (baseflow) of accumulated nitrogen during agricultural activities. Ultimately, water quality management of the Gyeongan stream basin requires pollution source management at the sub-basin level, including its tributaries, from a regional context. To manage the pollution load effectively, it is necessary to separate the hydrological components of the stream discharge and establish a monitoring system to track the flow and water quality of each component.
Journal of Korean Tunnelling and Underground Space Association
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v.25
no.4
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pp.261-283
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2023
This study aimed to review the performance stability of PET (Polyethylene terephthalate) fiber reinforcing materials among the synthetic fiber types for which the application of performance reinforcing materials to fiber-reinforced concrete is being reviewed by examining short-term and long-term performance changes. To this end, the residual performance was analyzed after exposing the PET fiber to an acid/alkali environment, and the flexural strength and equivalent flexural strength of the PET fiber-reinforced concrete mixture by age were analyzed, and the surface of the PET fiber collected from the concrete specimen was examined using a scanning microscope (SEM). The changes in were analyzed. As a result of the acid/alkali environment exposure test of PET fiber, the strength retention rate was 83.4~96.4% in acidic environment and 42.4~97.9% in alkaline environment. It was confirmed that the strength retention rate of the fiber itself significantly decreased when exposed to high-temperature strong alkali conditions, and the strength retention rate increased in the finished yarn coated with epoxy. In the test results of the flexural strength and equivalent flexural strength of the PET fiber-reinforced concrete mixture, no reduction in flexural strength was found, and the equivalent flexural strength result also did not show any degradation in performance as a fiber reinforcement. Even in the SEM analysis results, no surface damage or cross-sectional change of the PET reinforcing fibers was observed. These results mean that no damage or cross-section reduction of PET reinforcing fibers occurs in cement concrete environments even when fiber-reinforced concrete is exposed to high temperatures in the early stage or depending on age, and the strength of PET fibers decreases in cement concrete environments. The impact is judged to be of no concern. As the flexural strength and equivalent flexural strength according to age were also stably expressed, it could be seen that performance degradation due to hydrolysis, which is a concern due to the use of PET fiber reinforcing materials, did not occur, and it was confirmed that stable residual strength retention characteristics were exhibited.
The musical characteristics of Fishing songs in North Korean which recorded on Anthology of North Korean Folk Songs were examined in this paper. The results are as follows. Among Fishing songs in North Korea, there are "Rowing Song," the "Song for Hauling Nets," and the "Song for Picking Up Fish" in songs related to walleye pollack fishing and in songs related to croaker fishing, the "Song for Dropping Anchor" and the "Full-Load-of-Fish Song" in songs related to croaker fishing, the "Song for Weighing Anchor," the "Song for Shaking Fish," the "Full-Load-of-Fish Rowing Song," and the "Song for Hanging Walleye Pollack" in songs related to walleye pollack fishing. There are the "Song for Setting a sail" and the "Song for catching shells" in Fishing songs in North Korea, too. In the rhythmic elements of Fishing songs in North Korea, the tempo of the "Songs for Setting a sail" is moderato, and that of the "Songs for Picking Up Fish" of songs related to anchovy or herring fishing is quite slow. "Rowing Songs"(croaker fishing) have various tempos but faster than moderato, and usually get faster and faster as time goes by. Most songs have 4/♩. time and there are some of 2, 3 or 5 time. Some songs use irregular time or 6 time overlapping 2 beats. The mode Menari is the most common tonal system used in fishing songs of North Korea. And the mode Susimga, the mode Changbutaryeong, the mode Nanbongga, and the mode Odolttogi are also used in the tonal system of Fishing songs in North Korea. There are shoutting intonations that have indefinite pitch, too. Modulation or interaction by the mode Changbutaryeong appeared in songs of the mode Menari. There is a tendency to favor a certain tonal system by category. Responsorial form is mostly used, but in the most cases, they were sung in solo. In responsorial songs, several calling songs overlap with the responding songs. Durchkomponiert form is sung by antiphon or in solo, but the case sung in solo originally seems to have been sung by antiphon or unison, if we consider the procedure of the work. The "Song for Picking Up Fish" of Seonbong-gun of North Hamgyeong Province and Yangyang-gun of Gangwon Province, the "Full-Load-of-Fish Song-Bongjuktaryeong" of Jeungsan-gun of South Pyeongan Province and "Full-Load-of-Fish Song-Baechigisory" of Taean-gun of South Chungcheong Province, "Rowing Song" of Nampo City and Ganghwa-gun of Gyeonggi Province are resembled. In neighboring areas, even if the songs of different categorys, sometimes share a same melody. In a certain category, sometimes a same melody is shared to a considerable distance. It was first identified that in anchovy or herring fishing or dybowskii' sand eel fishing, the "Song for Picking Up Fish" is widely shared in the East Sea Coast area.
Min Jeong Ban;Sangwook Shin;Dong Hoon Lee;Jeong-Gyu Kim;Hosik Lee;Young Kim;Jeong-Hun Park;ShunHwa Lee;Seon-Young Kim;Joo-Hyon Kang
Journal of Wetlands Research
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v.25
no.4
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pp.306-314
/
2023
Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.
In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.
Bo Ra Kang;Eun Hee Kim;Yeon Kyoung Kim;Ah Hhyun Kim;Gyu Yeon Oh;Yoo Min Park;Ah Hyeon Jo;Hwan Sik Na;Mi Yeong Shin;Yang Joon An;Jeong Yong Cho;So Hyeon Lee
Food Science and Preservation
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v.31
no.2
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pp.267-275
/
2024
Artemisia fukudo Makino belongs to the Asteraceae family, is a halophyte that can grow in salinity soils and is known for its various physiological activities. However, few studies were comparing it according to the growth environment. Therefore, in this study, we analyzed the antioxidant activity, functional ingredients, and safety of Artemisia fukudo Makino according to the growth environment. Total polyphenol content was the highest in native mature leaves, but 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) and 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity was higher in cultivated leaves than in native leaves. The total mineral content, excluding sodium, was higher in cultivated than in native leaves. The content of potassium and calcium was higher in cultivated leaves than in native leaves. In addition, heavy metal analysis showed that cultivated leaves were generally lower than those of native leaves. Residual pesticides were not detected in all samples. In conclusion, since there is no significant difference in cultivated leaves compared to native leaves, it was judged that cultivated leaves could be used as a variety to be grown and mass-produced.
Yeong-Il Jeong;Kun-Ki Kim;Soon-Oh Kim;Sang-Woo Lee;Jin-Young Lee
Economic and Environmental Geology
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v.57
no.2
/
pp.233-241
/
2024
This study was conducted to investigate the geological distribution characteristics of fluorine in rocks, which can be a major resource of forest aggregates in Korea. Samples of forest aggregates were collected from 224 sites in 22 cities and counties for this study. The national background concentration was 344 mg/kg, which was significantly lower than the average fluorine concentration of crustal, which was 625 mg/kg, and slightly higher than the average fluorine concentration of world soil, which was 321 mg/kg. In terms of region and tectonic structure, fluorine concentrations were investigated to be highest in Gyeonggi-do(394 mg/kg) and Gyeonggi massif(396 mg/kg), respectively. The concentration distribution by the origin of the parent rock was in the order of metamorphic rock(362 mg/kg) > sedimentary rock(354 mg/kg) > igneous rock(328 mg/kg), and the concentration distribution by geologic ages was the highest in the Paleozoic at 394 mg/kg. The concentration distribution by rock types was in the order of diorite(515 mg/kg) > gneisses(377 mg/kg) > schists(344 mg/kg) > phyllite(306 mg/kg) > granites(305 mg/kg) > quartz porphyry(298 mg/kg). Consequently, it is speculated that gneisses and schists, Precambrian metamorphic rocks in the Gyeonggi massif that forms the crust of Gyeonggi-do, contain high fluorine concentrations.
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