• Journal of Climate Change Research
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• v.3 no.4
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• pp.245-257
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• 2012

Vulnerability assessment has been required for establish climate adaptation plan to prevent damage from climate change. In this study we assessed vulnerability with 1 km resolution and determined which sectors have the highest priority in each municipality of Gangwon province based on the result of vulnerability assessment. All sectors of vulnerability assessment are composed of three criteria; sensitivity, exposure and adaptation capacity. And suitable indicators of each sector were selected and spatial data set was prepared using GIS. Priority of vulnerability was classified with the degree of vulnerability in present and variation in vulnerability between present and future. The results of vulnerability assessment were different among municipalities due to the contribution of indicators. Present and future trends in vulnerability showed similar results but high vulnerable area was predicted to expand in the future. In addition increase in temperature led whole area to be more vulnerable generally. The result of prioritizing sectors of vulnerability indicated the most considerable sectors within a municipality. Also, the municipalities which have similar geographic, climatic and social conditions tended to be classified as the same priority class. The method of vulnerability assessment and determining priorities suggested in this study could be used to support decision makers to establish adaptation plan of local area.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.348-356
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• 2018

Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behavior and its spread. Thus, meteorological factors as well as topographical and forest factors were considered in the fire danger rating systems. This study aims to develop an advanced national integrated daily weather index(DWI) using weather data in the spring and fall to support forest fire prevention strategy in South Korea. DWI represents the meteorological characteristics, such as humidity (relative and effective), temperature and wind speed, and we integrated nine logistic regression models of the past into one national model. One national integrated model of the spring and fall is respectively $[1+{\exp}\{-(2.706+(0.088^*T_{mean})-(0.055^*Rh)-(0.023^*Eh)-(0.014^*W_{mean}))\}^{-1}]^{-1}$, $[1+{\exp}\{-(1.099+(0.117^*T_{mean})-(0.069^*Rh)-(0.182^*W_{mean}))\}^{-1}]^{-1}$ and all weather variables significantly (p<0.01) affected the probability of forest fire occurrence in the overall regions. The accuracy of the model in the spring and fall is respectively 71.7% and 86.9%. One integrated national model showed 10% higher accuracy than nine logistic regression models when it is applied weather data with 66 random sampling in forest fire event days. These findings would be necessary for the policy makers in the Republic of Korea for the prevention of forest fires.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.658-673
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• 2018

Social conflicts with extremely low frequency magnetic field(ELF-MF) exposures are expected to exacerbate due to continued increase in electric power demand and construction of high voltage transmission lines(HVTL). However, in current environmental impact assessment(EIA) act, specific guidelines have not been included concretely about EIA of ELF-MF. Therefore, this study conducted a standardization study on EIA method through case analysis, field measurement, and expert consultation of the EIA for the ELF-MF near HVTL which is the main cause of exposures. The status of the EIA of the ELF-MF and the problem to be improved are derived and the EIA method which can solve it is suggested. The main contents of the study is that the physical characteristics of the ELF-MF affected by distance and powerload should be considered at all stages of EIA(survey of the current situation - Prediction of the impacts - preparation of mitigation plan ? post EIA planning). Based on this study, we also suggested the 'Measurement method for extremely low frequency magnetic field on transmission line' and 'Table for extremely low frequency magnetic field measurement record on transmission line'. The results of this study can be applied to the EIA that minimizes the damage and conflict to the construction of transmission line and derives rational measures at the present time when the human hazard to long term exposure of the ELF-MF is unclear.

• Journal of Korean Society of Disaster and Security
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• v.12 no.2
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• pp.73-82
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• 2019

Recently, as the occurrence frequency of sudden floods due to climate change increased, the flood damage on riverside social infrastructures was extended so that there has been a threat of overflow. Therefore, a rapid prediction of potential flooding in riverside social infrastructure is necessary for administrators. However, most current flood forecasting models including hydraulic model have limitations which are the high accuracy of numerical results but longer simulation time. To alleviate such limitation, data driven models using artificial neural network have been widely used. However, there is a limitation that the existing models can not consider the time-series parameters. In this study the water surface elevation of the Hangang River bridge was predicted using the NARX model considering the time-series parameter. And the results of the ANN and RNN models are compared with the NARX model to determine the suitability of NARX model. Using the 10-year hydrological data from 2009 to 2018, 70% of the hydrological data were used for learning and 15% was used for testing and evaluation respectively. As a result of predicting the water surface elevation after 3 hours from the Hangang River bridge in 2018, the ANN, RNN and NARX models for RMSE were 0.20 m, 0.11 m, and 0.09 m, respectively, and 0.12 m, 0.06 m, and 0.05 m for MAE, and 1.56 m, 0.55 m and 0.10 m for peak errors respectively. By analyzing the error of the prediction results considering the time-series parameters, the NARX model is most suitable for predicting water surface elevation. This is because the NARX model can learn the trend of the time series data and also can derive the accurate prediction value even in the high water surface elevation prediction by using the hyperbolic tangent and Rectified Linear Unit function as an activation function. However, the NARX model has a limit to generate a vanishing gradient as the sequence length becomes longer. In the future, the accuracy of the water surface elevation prediction will be examined by using the LSTM model.

• Journal of the Society of Disaster Information
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• v.15 no.3
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• pp.440-449
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• 2019

Purpose: Fire-fighting organizations are the very first agencies that take actions at a disaster scene, and emergency rescue training is carried out for prompt and systematic response. However, there is a need for a change due to the limitations in emergency rescue trainings such as perfunctory trainings or trainings without considering regional or environmental characteristics. Method: This study is to conduct theoretical review with regard to emergency rescue training and present a measure to improve the emergency rescue training through attitude survey targeting fire-fighting organizations in Gangwon area. Result: Facilities that cause difficulties when doing emergency rescue activity were mostly hazardous material storage and processing facilities. In terms of the level of emergency rescue and response task, most respondents answered that the emergency rescue was insufficient. The respondents answered that the effectiveness of emergency rescue training was helpful, but some responses showed that the training was not helpful because of scenario-based training, seeming training, similar training carried out every year, unrealistic training, and lack of competent authorities' interest and perfunctory participations. Most respondents answered for the appropriateness of emergency rescue training and evaluation that they were satisfied, however, they were not satisfied with the evaluation methods irrelevant to the type of training, evaluation methods requiring unnecessary training scale, and evaluation methods leading perfunctory participations of competent authorities. Lastly, respondents mostly answered that training reflecting various damage situations are necessary regarding the demand on the improvement of emergency rescue training. Conclusion: The improvement measures for emergency rescue training are as follows. First, it is necessary to set and prepare various training contents in accordance with regional characteristics by reviewing major disasters occurred in the region. Second, it is necessary to revise the emergency rescue training guidelines and manuals for appropriate training plan for each fire station, provide education and training for working-level staff members, and establish training in a way that types, tactics, and strategies of emergency rescue training could be utilized practically. Third, it is necessary to prepare a scheme that can lead participation and provide incentive or penalty from the planning stage of training in order to increase the participation of supporting and competent authorities when an actual disaster occurs. Fourth, it is necessary to establish support arrangements and cooperative systems by authority through training by fire stations or zones in preparation for disaster situations that may occur simultaneously. Fifth, it is necessary to put emphasis on the training process rather than the result for emergency rescue training and evaluation, pay attention to the identification of supplement points for each disaster situation and make improvements. Especially, type or form of training should be considered rather than evaluating the execution status of detailed processes, and the evaluation measure that can consider the completeness (proficiency) of training and the status of role performance rather than the scale of training should be prepared. Sixth, type and method of training should be improved in accordance with the characteristics of each fire station by identifying the demand of working-level staff members for an efficient emergency rescue training.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.415-426
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• 2021

Purpose: The purpose of this study is to create the deveopment plan for promotion of advanced disaster-safety awareness, which is noted as a major factor in the large disaster. Method: This study is to conduct theoretical review with regard to disaster management and safety awareness. Consciousness surveys on safety awareness and previous disaster case was analyzed to derive the cause of the disaster, and the development plan for promotion of advanced disaster-safety awareness was suggested. Result: In the survey on the public's sense of safety on the disaster management evaluation, 'Response' stage was well performed, but the 'Recovery' stage was not. Especially, it was found that disaster safety education at the 'Prevention' stage was very lacking. In the survey on the public's safety awareness, the awareness level of the evacuation facility was very low, information on infectious diseases and collapse accident was insufficient. Especially, it has been found that the awareness on safety regulation in daily life is very insufficient. Through the case study on previous disaster(COVID-19, Fire in Miryang Sejong Hospital, Forest fire in the east coas at 2004'), it was derived that the lack of safety awareness(such as safety insensitivity) was the main factor of the expansion of the damage scale. Conclusion: The development plan for promotion of advanced disaster-safety awareness are as follow. First, it is necessary to spread the safety culture movement through the expansion of safety education and safety promotion. Second, disaster confrontation training for the public should be implemented to improve the effectiveness of disaster response. Finally, it is necessary to change the individual awareness on safety. When these factors are implemented systematically, advanced disaster-safety awareness can be promoted. Ultimately, disaster accidents in our society can be reduced.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.268-278
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• 2020

Flowering time has been put forward due to the recent abnormally warm winter, which often caused damages of flower buds by late frosts persistently. In the present study, cumulative chill unit and cumulative heat unit of Niitaka pear, which are required for releasing the endogenous dormancy and for flowering after breaking dormancy, respectively, were compared between flowering time prediction models used in South K orea. Observation weather data were collected at eight locations for the recent three years from 2018-2020. The dates of full bloom were also collected to determine the confidence level of models including DVR, mDVR and CD models. It was found that mDVR model tended to have smaller values (8.4%) of the coefficient of variation (cv) of chill units than any other models. The CD model tended to have a low value of cv (17.5%) for calculation of heat unit required to reach flowering after breaking dormancy. The mDVR model had the most accurate prediction of full bloom during the study period compared with the other models. The DVR model usually had poor skills in prediction of full bloom dates. In particular, the error of the DVR model was large especially in southern coastal areas (e.g., Ulju and Sacheon) where the temperature was warm. Our results indicated that the mDVR model had relatively consistent accuracy in prediction of full bloom dates over region and years of interest. When observation data for full bloom date are compiled for an extended period, the full bloom date can be predicted with greater accuracy improving the mDVR model further.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.339-349
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• 2021

In recent years, the occurrence of bacterial diseases of soybean has been increasing due to the continuous rise in spring temperature and the humid weather as a result of rain concentrated at the middle and late stages of crop growth. The resulting severe economic damage is also a concern. Unfortunately, there are no precise data on the occurrence and damage to lay the foundation for bacterial disease control in soybean in the Chungbuk Province. Therefore, the present study investigated the occurrence of major bacterial diseases, namely bacterial pustules, bacterial blight, and wildfire, in different soybean varieties in 410 fields in the Chungbuk Province in 2017. The incidence rate of bacterial pustules in the affected fields was 76.6%, and the incidence rate of infected plants was 29.3%. The incidence rate of bacterial blight in the affected fields was 13.9%, and the incidence rate of infected plants was 4.6%. The incidence rate of wildfire in the affected fields was 23.2%, and the incidence rate of infected plants was 10.1%. The overall incidence rate of bacterial diseases in the soybean fields where the diseases originated was 37.9% for bacterial pustules, 21.0% for bacterial blight, and 25.0% for wildfire, indicating that the disease incidence rate in fields where the disease originated was generally high. Among different varieties, the incidence rate of bacterial pustules was the highest in sprout soybean (88.9%), followed by Seoritae (84.0%) and Daewon (81.2%). The incidence rate of bacterial blight was the highest in the Daewon (19.6%), followed by Seoritae (15.2%) and sprout soybean (12.5%). The incidence rate of wildfire was the highest in sprout soybean (25.0%), followed by Daewon (24.7%) and Seoritae (5.4%). Meanwhile, in Uram, the incidence rate of bacterial pustules (7.1%) was the lowest, and this variety was not affected by bacterial blight or wildfire.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.41-54
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• 2021

It is very essential to estimate the water body area using remote exploration for water resource management, analysis and prediction of water disaster damage. Hydrophysical detection using satellites has been mainly performed on large satellites equipped with optical and SAR sensors. However, due to the long repeat cycle, there is a limitation that timely utilization is impossible in the event of a disaster/disaster. With the recent active development of Micro satellites, it has served as an opportunity to overcome the limitations of time resolution centered on existing large satellites. The Micro satellites currently in active operation are ICEYE in Finland and Capella satellites in the United States, and are operated in the form of clusters for earth observation purposes. Due to clustering operation, it has a short revisit cycle and high resolution and has the advantage of being able to observe regardless of weather or day and night with the SAR sensor mounted. In this study, the operation status and characteristics of micro satellites were described, and the water area estimation technology optimized for micro SAR satellite images was applied to the Daecheong Dam basin on the Korean Peninsula. In addition, accuracy verification was performed based on the reference value of the water generated from the optical satellite Sentinel-2 satellite as a reference. In the case of the Capella satellite, the smallest difference in area was shown, and it was confirmed that all three images showed high correlation. Through the results of this study, it was confirmed that despite the low NESZ of Micro satellites, it is possible to estimate the water area, and it is believed that the limitations of water resource/water disaster monitoring using existing large SAR satellites can be overcome.

• 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.