• 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 Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.1-18
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• 2024

This study analyzed the effect of warming on PM_2.5 aerosol production in mid-latitude East Asia during June 2020 using PM_2.5 aerosol anomalies, which were identified by incorporating meteorological and climate data into the Weather Research Forecasting model coupled with Chemistry (WRF-Chem) model. The decadal temperature change trend over a 30-year period (1991-2020) in East Asia showed that recent warming has been greater in summer than in winter. Summer warming in East Asia generated low and high pressure in the lower and upper troposphere, respectively, over China. The boundary between the lower tropospheric low and upper tropospheric high pressure sloped along the terrain from the Tibetan Plateau to Korea. The eastern China, Yellow Sea, and Korean regions experienced a convergence of warm and humid southwesterly airflows originating from the East China Sea with the development of a northwesterly Pacific high pressure. In June 2020, the highest temperatures were observed since 1973 in Korea. Meanwhile, enhanced warming in East Asia increased the production of PM_2.5 aerosols that travelled long distances from eastern China to Korea. PM_2.5 anomalies, which were derived solely by inputting meteorological and climatic data (1991-2020) into the WRF-Chem model and excluding emission variations, showed a positive distribution extending from eastern China to South Korea across the Yellow Sea as well as over the Pacific Northwest. Thus, the contribution of warming to PM_2.5 aerosols in East Asia during June 2020 was more than 50%. In particular, PM_2.5 aerosols were transported from eastern China to Korea through the Yellow Sea, where the warm and humid southwesterly airflows implied wet scavenging of sulfate but promoted nitrate production.

• Journal of Korean Society of Forest Science
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• v.113 no.1
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• pp.40-50
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• 2024

Pine forests are continuously declining due to competition with broadleaf trees, such as oaks, as a consequence of changes in the natural dynamics of forest ecosystem. This natural decline creates a risk of losing the various benefits pine trees have provided to people in the past. Therefore, it is necessary to prepare future forest management directions by considering the state of pine tree decline in each region. The goal of this study is to understand the characteristics of pine forest changes according to forest dynamics and to predict future regional changes. For this purpose, we evaluated the trend of change in pine forests and extracted various variables(topography, forest stand type, disturbance, and climate) that affect the change, using time-series National Forest Inventory (NFI) data. Also, using selected key variables, a model was developed to predict future changes in pine forests. As a results, it showed that the importance of pine trees in forests across the country has decreased overall over the past 10 years. Also, 75% of the sample points representing pine trees remained unchanged, while the remaining 25% had changed to mixed forests. It was found that these changes mainly occurred in areas with good moisture conditions or disturbance factors inside and outside the forest. In the next 10 years, approximately 14.2% of current pine forests was predicted to convert to mixed forests due to changes in natural forest dynamics. Regionally, the rate of pine forest change was highest in Jeju(42.8%) and Gyeonggi(26.9%) and lowest in Gyeongbuk(8.8%) and Gangwon(13.8%). It was predicted that pine forests would be at a high risk of decline in western areas of the Korean Peninsula, including Gyeonggi, Chungcheong, and Jeonnam. This results can be used to make a management plan for pine forests throughout the country.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.36 no.5
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• pp.407-428
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• 1991

The eastern coastal area having variability of climate is located within Taebaek mountain range and the east coast of Korea. It is therefore ease to cause the wind damages in paddy field during rice growing season. The wind damages to rice plant in this area were mainly caused by the Fohn wind (dry and hot wind) blowing over the Taebaek mountain range and the cold humid wind from the coast. The dry wind cause such as the white head, broken leaves, cut-leaves, dried leaves, shattering of grain, glume discolouration and lodging, On the other hand the cold humid wind derived from Ootsuku air mass in summer cause such symptom as the poor rice growth, degeneration of rachis brenches and poor ripening. To minimize the wind damages and utilize as a preparatory data for wind injury of rice in future, several experiments such as the selection of wind resistant variety to wind damage, determination of optimum transplanting date, improvement of fertilizer application methods, improvement of soils and effect of wind break net were carried out for 8 years from 1982 to 1989 in the eastern coastal area. The results obtained are summarized as follows. 1. According to available statisical data from Korean meteorological services (1954-1989) it is apperent that cold humid winds frequently cause damage to rice fields from August 10th to September 10th, it is therefore advisable to plan rice cultivation in such a way that the heading date should not be later than August 10th. 2. During the rice production season, two winds cause severe damage to the rice fields in eastern coastal area of Korea. One is the Fohn winds blowing over the Taebaek mountain range and the other is the cold humid wind form the coast. The frequency of occurrence of each wind was 25%. 3. To avoid damage caused by typhoon winds three different varieties of rice were planted at various areas. 4. In the eastern coastal area of Korea, the optimum ripening temperature for rice was about 22.2$^{\circ}C$ and the optimum heading date wad August 10th. The optimum transplanting time for the earily maturity variety was June 10th., medium maturity variety was May 20th and that of late maturity was May 10th by means of growing days degree (GDD) from transplanting date to heading date. 5.38% of this coastal area is sandy loamy soil while 28% is high humus soil. These soil types are very poor for rice cultivation. In this coastal area, the water table is high, the drainage is poor and the water temperature is low. The low water temperature makes it difficult for urea to dissolve, as a result rice growth was delayed, and the rice plant became sterile. But over application of urea resulted in blast disease in rice plants. It is therefore advise that Ammonium sulphate is used in this area instead of urea. 6. The low temperature of the soil inhibits activities of microorganism for phosphorus utilization so the rice plant could not easily absorb the phosphorus in the soil. Therefore phosphorus should be applied in splits from transplanting to panicle initiation rather than based application. 7. Wind damage was severe in the sandy loamy soil as compared to clay soils. With the application of silicate. compost and soil from mointain area. the sand loamy soil was improved for rice grain colour and ripening. 8. The use of wind break nets created a mocro-climate such as increased air. soil and water temperature as well as the reduction of wind velocity by 30%. This hastened rice growth, reduced white head and glume discolouration. improved rice quality and increased yield. 9. Two meter high wind break net was used around the rice experimental fields and the top of it. The material was polyethylene sheets. The optimum spacing was 0.5Cm x 0.5Cm. and that of setting up the wind break net was before panicle initiation. With this set up, the field was avoided off th cold humid wind and the Fohn. The yield in the treatment was 20% higher than the control. 10. After typhoon, paddy field was irrigated deeply and water was sprayed to reduce white head, glume discolouration, so rice yield was increased because of increasing ripening ratio and 1, 000 grain weight.

• Korean Journal of Environmental Agriculture
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• v.34 no.2
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• pp.77-90
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• 2015

BACKGROUND: The field margins, which are uncultivated area of permanent vegetation located adjacent to field, play an important role in enhancing biodiversity in the agricultural ecosystem. This study focused on floristic characteristics on dry field margins in Korea Peninsula. METHODS AND RESULTS: This study was conducted at margins of 196 dry fields in 32 areas in 8 provinces in May and September 2013. The vascular plants of the dry field margins were listed 347 taxa which contain 73 families, 219 genera, 311 species, 1 subspecies, 30 varieties and 5 forms. Of these 347 taxa, 48 taxa were woody plants and 299 taxa were herbaceous plants. Among total 73 families, Compositae (17.6%) was the most dominant family, and followed Gramineae (15.9%), Polygonaceae (5.8%), Leguminosae (4.9%) and Cyperaceae (3.8%). Based on relative frequency values of survey fields, the appearance frequency of Digitaria ciliaris (89.8%) was the highest, and followed Acalypha australis (86.2%), Artemisia princeps (82.1%), Commelina communis (80.6%) and Portulaca oleracea (80.6%). Disturbance index of dry field margins was 55.0% at national level, and Gangwon region was the highest among the 8 regions at regional level. Life form spectrum was determined to be $Th-R_5-D_4-etype$. CONCLUSION: These results will be used fundamental data for studies to improve or even stabilize the current state of plant biodiversity in agricultural environments.

• Journal of the Korean earth science society
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• v.32 no.7
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• pp.832-859
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• 2011

The importance of scientific education on accurate oceanic currents and circulation has been increasingly addressed because the currents have played a significant role in climate change and global energy balance. The objectives of this study are to analyze errors of the oceanic current maps in the textbooks, to discuss a variety of error sources, to suggest how to produce a unified oceanic current map of the East Sea for the students. Twenty-seven textbooks based on the 7th National Curriculum were analyzed and quantitatively investigated on the characteristics of the current maps by comparing with both the previous literature and up-to-date scientific knowledge. All the maps in the textbooks with different mappings were converted to digitalized image data with Mercator mapping using geolocation information. Detailed analysis were performed to investigate the patterns of the Tsushima Warm Current (TWC) in the Korea Strait, to examine how closely the nearshore branch of the TWC flows along the Japanese coast, to scrutinize the features of the offshore branch of the TWC south of the subpolar front in the East Sea, to quantitatively investigate the northern range of the northward-propagating East Korea Warm Current and its latitude turning to the east, and lastly to examine the outflow of the TWC near the Tsugaru Strait and the Soya Strait. In addition, the origins, southern limits, and distances from the coast of the Liman Current and the North Korea Cold Current were analyzed. Other erroneous expressions of the currents in the textbooks were presented. These analyses revealed the problems in the present current maps of the textbooks, which might lead the students to misconception. This study also addressed a necessity in a bridge between scientists with up-to-date scientific results and educators who needed educational materials.

• Korean Journal of Environment and Ecology
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• v.31 no.4
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• pp.381-396
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• 2017

Understanding species distribution plays an important role in conservation as well as evolutionary biology. In this study, we applied a species distribution model to predict hotspot areas and habitat characteristics for endangered herpetofauna species in South Korea: the Korean Crevice Salamander (Karsenia koreana), Suweon-tree frog (Hyla suweonensis), Gold-spotted pond frog (Pelophylax chosenicus), Narrow-mouthed toad (Kaloula borealis), Korean ratsnake (Elaphe schrenckii), Mongolian racerunner (Eremias argus), Reeve's turtle (Mauremys reevesii) and Soft-shelled turtle (Pelodiscus sinensis). The Kori salamander (Hynobius yangi) and Black-headed snake (Sibynophis chinensis) were excluded from the analysis due to insufficient sample size. The results showed that the altitude was the most important environmental variable for their distribution, and the altitude at which these species were distributed correlated with the climate of that region. The predicted distribution area derived from the species distribution modelling adequately reflected the observation site used in this study as well as those reported in preceding studies. The average AUC value of the eigh species was relatively high ($0.845{\pm}0.08$), while the average omission rate value was relatively low ($0.087{\pm}0.01$). Therefore, the species overlaying model created for the endangered species is considered successful. When merging the distribution models, it was shown that five species shared their habitats in the coastal areas of Gyeonggi-do and Chungcheongnam-do, which are the western regions of the Korean Peninsula. Therefore, we suggest that protection should be a high priority in these area, and our overall results may serve as essential and fundamental data for the conservation of endangered amphibian and reptiles in Korea.

• Korean Journal of Environment and Ecology
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• v.34 no.5
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• pp.491-499
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• 2020

Increasing impervious surfaces can cause various physical and mental illnesses as well as further problems like deterioration of the thermal environment and disconnection of the water circulation system in the downtown area. This study is intended to suggest baseline data for the future creation or remodelation of large-scaled urban parks in consideration of human health on the aspect of climate by analyzing air ions condition and correlation analysis between air ions and meteorological elements depending on distances from the center in the urban park. The study site was divided into four types by distances from the center of Olympic Park in Songpa-gu, Seoul, then classified as A and B. After selecting 80 points to record, land coverage and vegetation status were investigated, and then meteorological elements and air ions were measured. First, the green space rate by section is A section Center (90%)> Inner (70%)> Outer-inner (10%) = Outer (10%), B section Center (100%)> Inner (60%)> Outer- In order of inner (30%)> Outer (0%). Second, for weather factors, the temperature was analyzed by Outer (24.18℃) > Outer-inner (22.90℃) > Inner (22.43℃) > Center (21.719℃). For relative humidity, center (46.49%) > Inner (43.36%) > Outer-inner (42.41%) > Outer (38.53%) was analyzed. Third, In the case of cations in the air ions, Outer(435.71ea/㎤) > Outer-inner(415.16ea/㎤) > Inner (389.46ea/㎤) > Center (352.64ea/㎤). In the case of negative ions, Center (569.72ea/㎤) > Inner (499.83ea/㎤) > Outer-inner(410.58ea/㎤) > Outer (292.02ea/㎤). It was analyzed to increase toward Center, and analyzed to decrease with increasing distance from road. For the Air ion index, it was analyzed as Center (1.67) > Inner (1.31) > Outer-inner (1.08) > Outer (0.71). Negative irons was analyzed to increase when its measuring points close to the center and decrease with shortening distance to the road. Fourth, as a result of correlation analysis, positive(+) correlation is negative ions and ion index. These were measured to increase as the recording points closing to the center of the park from the road. The negative(-) correlation is temperature, solar radiation, and positive ions. These increased as getting closer to the road.

• 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.