• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.2
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• pp.298-317
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• 2019

The physical characteristics of the Ulleung Warm Eddy (UWE) and its relationship with the East Korea Warm Current (EKWC) were analyzed using the CMEMS (Copernicus Marine Environment Monitoring Service) satellite altimetry data and the CTD data of the National Institute of Fisheries Science (NIFS) near the Ulleung Basin from 1993 to 2017. The distribution of the UWEs coupled with EKWC accounts for 81% of the total number of the UWEs. Only 7% of the total eddies are completely separated from the EKWC. The UWE has the characteristics of high temperature and high salinity water inside of it when it is formed from the EKWC. However, when the UWE is wintering, its internal structure changes greatly. In the winter, surface homogeneous layer of $10^{\circ}C$ and 34.2 psu inside of the UWE is produced by vertical convection from sea-surface cooling, and deepened to a maximum depth of approximately 250 m in early spring. In summer, the UWE changes into a structure with a stratified structure in the upper layer within a depth of 100 m and a homogeneous layer made in winter in the lower layer. 62 UWEs were produced for 25 years from 1993 to 2017. on average, 2.5 UWEs were formed annually, and the average life span was 259 days (approximately 8.6 months). The average size of the UWEs is 98 km in the east-west direction and 109 km in the north-south direction. The average size of UWE using satellite altimetric data is estimated to be 1~25 km smaller than that using water temperature cross-sectional data.

• Korean Journal of Environment and Ecology
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• v.37 no.3
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• pp.209-220
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• 2023

Over the past few centuries, widespread changes to natural ecosystems caused by human activities have severely threatened biodiversity worldwide. Understanding changes in ecosystems is essential to identifying and managing threats to biodiversity. In line with this need, the IUCN Council formed the IUCN Global Ecosystem Typology (GET) in 2019, taking into account the functions and types of ecosystems. The IUCN provides maps of 10 ecosystem groups and 108 ecological functional groups (EFGs) on a global scale. According to the type classification of IUCN GET ecosystems, Korea's ecosystem is classified into 8 types of Realm (level 1), 18 types of Biome (level 2), and 41 types of Group (level 3). GETs provided by IUCN have low resolution and often do not match the actual land status because it was produced globally. This study aimed to increase the accuracy of Korean IUCN GET type classification by using land cover maps and producing maps that reflected the actual situation. To this end, we ① reviewed the Korean GET data system provided by IUCN GET and ② compared and analyzed it with the current situation in Korea. We evaluated the limitations and usability of the GET through the process and then ③ classified Korea's new Get type reflecting the current situation in Korea by using the national data as much as possible. This study classified Korean GETs into 25 types by using land cover maps and existing national data (Territorial realm: 9, Freshwater: 9, Marine-territorial: 5, Terrestrial-freshwater: 1, and Marine-freshwater-territorial: 1). Compared to the existing map, "F3.2 Constructed lacustrine wetlands", "F3.3 Rice paddies", "F3.4 Freshwater aquafarms", and "T7.3 Plantations" showed the largest area reduction in the modified Korean GET. The area of "T2.2 Temperate Forests" showed the largest area increase, and the "MFT1.3 Coastal saltmarshes and reedbeds" and "F2.2 Small permanent freshwater lakes" types also showed an increase in GET area after modification. Through this process, the existing map, in which the sum of all EFGs in the existing GET accounted for 8.33 times the national area, was modified so that the total sum becomes 1.22 times the national area using the land cover map. This study confirmed that the existing EFG, which had small differences by type and low accuracy, was improved and corrected. This study is significant in that it produced a GET map of Korea that met the GET standard using data reflecting the field conditions. 

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.91-106
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• 2022

Cryptocurrency, stood out the sharp cost rising of Bitcoin has been spotlighted by means of the solution for stagflation because it is decentralized with an existing currency differently. Especially getting into 4th industrial revolution, technologies using block chain and internet of things have been used in the many fields, and the power of influence is also widespread. Nevertheless like a remark of Elon Musk of Tesla CEO, the problems of environmental contamination for cryptocurrency have been pointed out continuously and the most representative of them is an enormous electric usage as the use of fossil fuels. Also the amount generated of carbon dioxide result in the acceleration of global warming mainly based on the climate changes of earth if the existing mining method is continued. On the other hand, review researches have been conducted restrictively as the connection with environmental contamination as the mining of cryptocurrency. In this study, it intended to review problems for environmental contamination as the diversification of ecological system of cryptocurrency concretely. Upon investigation existing prior documents on the putting recent data first, the mining of cryptocurrency has affected on the environmental contamination conflicting with carbon neutrality as increasement of the electric usage and electronic wastes. And POS method without the mining process appeared, but it had a demerit collapsing a decentralization and then we met turning point on appearing various environmental-friendly cryptocurrency. Finally the appearance of cryptocurrency using new renewable energy acted on the opportunity of the usage maximization of energy storage apparatus and the birth of national government intervention. Based on these results, we mention clearly that hereafter cryptocurrency will regress if not go abreast the value of currency as well as environmental approach.

• Korean Journal of Environmental Agriculture
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• v.34 no.2
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• pp.91-97
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• 2015

BACKGROUND: Earthworms are essential detritus feeders that play a vital role in the process of decomposition of organic matter and soil metabolism. The complex process of partial breakdown of organic matter and mixing with mucous and gut microbial flora in the form of earthworm cast results in the reduction of the toxicity. This study focused on the change of cast amount and pollutant contents before and after the eating of the organic waste and upland soil with the two species of earthworm. METHODS AND RESULTS: The two species of earthworms were compared to the cast production. In the upland soil material, the daily amount of worm's cast was 1.42 g in E. andrei and 0.40 g in A. agrestis. In the organic waste material, the cast of E. andrei was 0.78~0.83 g and the cast of A. agrestis. have not been collected because all earthworms died after the treatment. The heavy metals treated in the upland soil were evaluated the impact of the worm excretion. With the E. andrei, the cast production was decreased 0.1~0.8 times in zinc, 0.2~0.5 times in copper, and 0.1~0.7 times in cadmium compared to the control treatment according to the levels of concentration. With A. agrestis, the cast amount was decreased 0.3~1.1 times in zinc, 0.2~0.3 times in copper, and 0.1~2.1 times in cadmium, respectively. The changes of pollutant contents before and after the eating of the organic wastes with E. andrei were studied. In the treatment of the Alcohol Fermentation Processing Sludge and the Fruit Juice Processing Sludge, heavy metal content of the cast was increased 0.7~53.3% compared to the sludge materials. PAHs contents were decreased 50.1% in the cast of the Alcohol Fermentation Processing Sludge and 36.6% in the cast of the Fruit Juice Processing Sludge, respectively. CONCLUSION: In conclusion, although the A. agrestis was bigger than E. andrei in size and weight, the cast amount of A. agrestis was small. The two species of earthworm was less excretion with high concentration of heavy metals. While the heavy metals such as zinc, copper, and cadmium were considerably accumulated in the cast, the total compounds, PAHs were fairly decomposed. There results would provide us for restoring contaminated soil and cleaning organic wastes.

• Journal of Korea Water Resources Association
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• v.45 no.3
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• pp.301-316
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• 2012

Two models, TANK and SWAT (Soil and Water Assessment Tool) were compared for simulating natural flows in the Paldang Dam upstream areas of the Han River basin in order to understand the limitations of TANK and to review the applicability and capability of SWAT. For comparison, simulation results from the previous research work were used. In the results for the calibrated watersheds (Chungju Dam and Soyanggang Dam), two models provided promising results for forecasting of daily flows with the Nash-Sutcliffe model efficiency of around 0.8. TANK simulated observations during some peak flood seasons better than SWAT, while it showed poor results during dry seasons, especially its simulations did not fall down under a certain value. It can be explained that TANK was calibrated for relatively larger flows than smaller ones. SWAT results showed a relatively good agreement with observed flows except some flood flows, and simulated inflows at the Paldang Dam considering discharges from upper dams coincided with observations with the model efficiency of around 0.9. This accounts for SWAT applicability with higher accuracy in predicting natural flows without dam operation or artificial water uses, and in assessing flow variations before and after dam development. Also, two model results were compared for other watersheds such as Pyeongchang-A, Dalcheon-B, Seomgang-B, Inbuk-A, Hangang-D, and Hongcheon-A to which calibrated TANK parameters were applied. The results were similar to the case of calibrated watersheds, that TANK simulated poor smaller flows except some flood flows and had same problem of keeping on over a certain value in dry seasons. This indicates that TANK application may have fatal uncertainties in estimating low flows used as an important index in water resources planning and management. Therefore, in order to reflect actually complex and complicated physical characteristics of Korean watersheds, and to manage efficiently water resources according to the land use and water use changes with urbanization or climate change in the future, it is necessary to utilize a physically based watershed model like SWAT rather than an existing conceptual lumped model like TANK.

• Korean Journal of Environment and Ecology
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• v.31 no.4
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• pp.409-419
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• 2017

Although Korean red pine (Pinus densiflora) forests near temples are valuable as forests of the cultural landscape, they are likely to be deteriorated because of vegetation succession and climate changes. The purpose of this study is to investigate the vegetation structure, the pine vitality, and the site environmental characteristics of the pine forests near temples to identify the correlation between pine tree growth and location environment. We selected Chuneunsa, Wonhyosa, Jeungsimsa, and Taeansa Temples since these four areas still had the healthy pine forests. In all four studied area, the pine trees dominate the canopy layers while the deciduous broadleaf trees mostly inhabited appeared in the lower layers. The growth of pine trees in Jeungsimsa and Wonhyosa areas was not as good as Chuneunsa area where the pine trees tended to be older. We found higher total nitrogen content in soil in Jeungsimsa area than other areas, maybe because of increase in total nitrogen caused by the development of low vegetation in the area. This peculiarity may have led to the pine trees in the area to fall behind the deciduous broadleaf trees in competition for nitrogen nutrient and thus to show deteriorated growth. The altitude and the twig length showed a negative correlation as did the degree of slope and the mean importance percentage of the pine tree. In other words, the growth environment such as soil became poorer when the altitude and the degree of slope increased, and thus the growth amount and dominance of the pine trees were lower. The degree of slope showed a positive correlation with the twig length of the pine tree. Within boundaries of location environment where the pine tree forests were dominant, it seemed that growth of the pine trees was more favorable as the slope was steeper because the trees could avoid competition with deciduous broadleaf trees. On the other hand, the growth of pine trees deteriorated as the electrical conductivity of soil increased; increase in soil nutrients might have accelerated vegetation development of deciduous broadleaf trees and thus aggravated the growth environment of pine trees to negatively affect maintaining the health of the pine tree forests.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.3
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• pp.273-281
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• 2015

Relationship between grain quality-related traits and daily mean temperature/sunshine hours during grain filling stage was analyzed using eleven high quality rice varieties at 24 experimental sites through eight provinces of Korea in 2013~2014. In the data set pooled across varieties, experimental sites and years, grain quality-related traits such as percentage of head rice (PHR), head rice yield (HRY), protein in milled rice (PRO) and Toyo Mido Meter glossiness value (TGV) were higher at the temperature lower than $22.6^{\circ}C$ for 40 days after flowering (DAF), which was optimum for percentage of grain filling in this study. Optimum sunshine hours for 40 DAF were $6.0{\sim}6.1\;hr\;d^{-1}$when considered PHR, HRY and TGV. PRO was associated with daily mean temperature and sunshine hours for 40 DAF in more varieties than the other traits. PRO was closely correlated with daily mean temperature during early filling stage and sunshine hours during early to mid filling stage, compared to other stages during grain filling. It is concluded that general trend in the variation of grain quality-related traits could be explained by the changes in daily mean temperature and sunshine hours during grain filling. In addition, climate conditions during early grain filling stage played important roles to enhance grain quality.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.4
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• pp.346-352
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• 2020

Currently, many studies are being conducted to cope with climate changes due to global warming and abnormal weather. The objective of this study was to investigate the effects of weather on the growth, yield components, and quality of soybeans using weather data from 2017 and 2018. The average temperature in 2018 was higher than that in 2017 from R1 to R5 of the growth stage for all cultivars. On the other hand, precipitation in 2018 was reduced compared to that in 2017 for Daewon and Daepung-2ho. It was observed that the flowering date in 2018 was earlier than that in 2017 for Daewon and Daepung-2ho, but the flowering date for Pungsannamul in 2018 was similar to that in 2017. Simulating soil water content with the estimation model (AFKAE0.5) determined that there were fewer drought dates in 2017 than those in 2018, and drought lasted from R1 to early R5 of the growth stage in 2018. Soybean growth in 2017 was better than that in 2018, and seed yield and 100-seed weight of soybean were higher in 2017 than those in 2018 for all cultivars. The seed size in 2017 was larger than that in 2018 for all cultivars. Oil content in 2017 was higher than that in 2018; in particular, the difference between both years was observed for Daewon and Daepung-2ho. Protein content was higher in 2018 than that in 2017; however, there were different levels for each cultivar. Thus, these results indicate that the yield component and quality of soybeans are affected by high temperature and drought.