• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.697-705
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• 2020

This paper deals with an analysis of crustal movement for the sourthern part of Korean peninsula using GNSS (Global Navigation Satellite System) data. An earthquake of more than 5.0 occurred in the southeastern region of the Korean Peninsula, and it is necessary to evaluate the risk of earthquakes in various ways.In order to reveal long-term tectonic movement patten in Pohang and Gyeongju provinces, we derived crustal movement parameters related with elastic theory. We used GAMIT/GLOBK for analyzing seven-year interval GNSS data of CORS (Continuously Operating Reference Stations). The azimuth of velocity vectors trended generally about 110° with an mean magnitude of 31mm/yr.The main characteristics of the strain change for seven-year in Korea obtaind from our study. Direction of the principal axis of the maximum compression is ENE-WSW as a whole, through there are some exceptions. The mean rate of the maximum shear strain change is (0.11±0.07)μ/yr, that is approximately one third that of Chubu district, Central Japan. Taking into account our results, the mean rate of maximum shear in southern part of Korean peninsula is considered as reasonable. The mean azimuth of principal strain is about (85.4°±26.8°). There are some exceptions of azimuth because the average azimuth differ from the left and right side in Yangsan fault which are about (73.2°±21.5°) and (105.2°±17.0°) respectively, It is noteworthy that the high seismicity areas in the southern part of Korea peninsula almost coincides with the area of large strain rate. As a conclusion, it could be stated that the our study represents the characteristics of crustal deformation in the southern part of peninsula, and contributes to the researches on earthquake disaster management.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1203-1210
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• 2020

Drought is caused by a combination of various hydrological or meteorological factor, so it is difficult to accurately assess drought event, but various drought indices have been developed to interpret them quantitatively. However, the drought indexes currently being used are calculated from the lack of a single variable, which is a problem that does not accurately determine the drought event caused by complex causes. Shortage of a single variable may not be a drought, but it is judged to be a drought. On the other hand, research on developing indices using unstructured data, which is widely used in big data analysis, is being carried out in other fields and proven to be superior. Therefore, in this study, we intend to calculate the drought index by combining unstructured data (news data) with weather and hydrologic information (rainfall and dam inflow) that are being used for the existing drought index, and to evaluate the utilization of drought interpretation through verification of the calculated drought index. The Clayton Copula function was used to calculate the joint drought index, and the parameter estimation was used by the calibration method. The analysis showed that the drought index, which combines unstructured data, properly expresses the drought period compared to the existing drought index (SPI, SDI). In addition, ROC scores were calculated higher than existing drought indices, making them more useful in drought interpretation. The joint drought index calculated in this study is considered highly useful in that it complements the analytical limits of the existing single variable drought index and provides excellent utilization of the drought index using unstructured data.

• The Journal of Engineering Geology
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• v.31 no.2
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• pp.199-209
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• 2021

This paper is written to evaluate the ground stability according to the construction of Jeju 2nd airport. Sumgol is the unique characteristics of Jeju soil, which is used to evaluate the ground stability of the airport. The research contents are as follows. 1) The geotechnical characteristics for Jeju 2nd airport was analyzed, and the Sumgol and geotechnical properties were calculated based on the existing geotechnical survey data. 2) The divided sections of Jeju 2nd airport were modeled to evaluate the ground stability after determining the section (runway and airport facilities) which have the different soil and loading properties. 3) The stability and deformation ranges of the airport ground were identified through numerical analysis. The entire airport was divided into three sections to analyze the stability of Jeju 2nd airport, and calculated the stresses, settlements, and strains of each section by computer numerical analysis modeling. For modeling, the ground and load conditions were examined, also pavement conditions for each airport ground section were examined. From the analysis results of each section according to the ground conditions, the vertical settlements were analyzed as 0.11~0.18 m and the sum of effective stress and pore water pressure were 92.75~445 kPa. These results were made by taking into account the Sumgol of the bottom ground without reinforcement, also the soil strength parameters of the airport ground were reduced for computer modeling, Therefore, if proper reinforcements are applied to the ground of Jeju 2nd airport, sufficient airport ground stability can be secured.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.268-279
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• 2021

The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1091-1104
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• 2022

Climate change is predicted to increase the frequency and intensity of rainfall worldwide, and the pattern is changing due to inundation damage in urban areas due to rapid urbanization and industrialization. Accordingly, the impact assessment of climate change is mentioned as a very important factor in urban planning, and the World Meteorological Organization (WMO) is emphasizing the need for an impact forecast that considers the social and economic impacts that may arise from meteorological phenomena. In particular, in terms of traffic, the degradation of transport systems due to urban flooding is the most detrimental factor to society and is estimated to be around £100k per hour per major road affected. However, in the case of Korea, even if accurate forecasts and special warnings on the occurrence of meteorological disasters are currently provided, the effects are not properly conveyed. Therefore, in this study, high-resolution analysis and hydrological factors of each area are reflected in order to suggest the depth of flooding of urban floods and to cope with the damage that may affect vehicles, and the degree of flooding caused by rainfall and its effect on vehicle operation are investigated. decided it was necessary. Therefore, the calculation formula of rainfall-immersion depth-vehicle speed is presented using various machine learning techniques rather than simple linear regression. In addition, by applying the climate change scenario to the rainfall-inundation depth-vehicle speed calculation formula, it predicts the flooding of urban rivers during heavy rain, and evaluates possible traffic network disturbances due to road inundation considering the impact of future climate change. We want to develop technology for use in traffic flow planning.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.345-356
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• 2022

A severe flooding occured at a small urban catchment in Daejeon-si South Korea on July 30, 2020 causing significant loss of property (inundated 78 vehicles and two apartments) and life (one casualty and 56 victims). In this study, a retrospective analysis of the inundation event was implemented using a physically-based urban flood model, H12 with high-resolution data. H12 is an integrated 1-dimensional sewer network and 2-dimensional surface flow model supported by hybrid parallel techniques to efficiently deal with high-resolution data. In addition, we evaluated the impact of the flooding barriers which were installed after the flood disaster. As a result, it was found that the inundation was affected by a combination of multiple components including the shape of the basin, the low terrain of the inundation area located in the downstream part of the basin, and lack of pipe capacity to drain discharge from the upstream during heavy rain. The impact of the flooding barriers was analyzed by modeling with and without barriers on the high-resolution terrain input data. It was evaluated that the flood barriers effectively lower the water depth in the apartment complex. This study demonstrates capability of high-resolution physically-based urban modeling to quantitatively assess the past inundation event and the impact of the reduction measures.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.251-260
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• 2022

Although the number of trees affected by pine wilt disease is decreasing, the affected area is expanding across the country. Recently, with the development of deep learning technology, it is being rapidly applied to the detection study of pine wilt nematodes and dead trees. The purpose of this study is to efficiently acquire deep learning training data and acquire accurate true values to further improve the detection ability of U-Net models through learning. To achieve this purpose, by using a filtering method applying a step-by-step deep learning algorithm the ambiguous analysis basis of the deep learning model is minimized, enabling efficient analysis and judgment. As a result of the analysis the U-Net model using the true values analyzed by period in the detection and performance improvement of dead pine trees of wilt nematode using the U-Net algorithm had a recall rate of -0.5%p than the U-Net model using the previously provided true values, precision was 7.6%p and F-1 score was 4.1%p. In the future, it is judged that there is a possibility to increase the precision of wilt detection by applying various filtering techniques, and it is judged that the drone surveillance method using drone orthographic images and artificial intelligence can be used in the pine wilt nematode disaster prevention project.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.555-562
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• 2021

Recently, in the field of geospatial information construction, unmanned aerial vehicles have been increasingly used because they enable rapid data acquisition and utilization. In this study, photogrammetry was performed using fixed-wing, rotary-wing, and VTOL (Vertical Take-Off and Landing) unmanned aerial vehicles, and geospatial information was constructed using two types of unmanned aerial vehicle LiDAR (Light Detection And Ranging) sensors. In addition, the accuracy was evaluated to present the utility of spatial information constructed through unmanned aerial photogrammetry and LiDAR. As a result of the accuracy evaluation, the orthographic image constructed through unmanned aerial photogrammetry showed accuracy within 2 cm. Considering that the GSD (Ground Sample Distance) of the constructed orthographic image is about 2 cm, the accuracy of the unmanned aerial photogrammetry results is judged to be within the GSD. The spatial information constructed through the unmanned aerial vehicle LiDAR showed accuracy within 6 cm in the height direction, and data on the ground was obtained in the vegetation area. DEM (Digital Elevation Model) using LiDAR data will be able to be used in various ways, such as construction work, urban planning, disaster prevention, and topographic analysis.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.629-659
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• 2021

This study compared the influences of Korean psycho-social experiences on emotional-distress(stress, depression, anxiety, anger) of Koreans between two-periods during COVID-19. First, an online survey was conducted among 600 participants between April 13, 2020 and 21, while WHO had declared the pandemic, and Daegu-Gyungbuk were declared as a special-disaster area. Second, an online survey was conducted among 482 participants out of 600 study participants from the first study during August 21 to September 2, while COVID-19 re-spreaded around the world, and total confirmed cases were over 1,000 for a week in Seoul-Gyeonggi province. Hierarchical-regression analysis was used to determine the influence of personal characteristics, fear and social constraints, relationship conflict and income-decreasing factors on stress, depression, anxiety, anger in the two-time points. Results suggest that gender, quality-of-life, 'frequent information-checking about COVID-19', 'fear of unpredictability' and 'difficulties on hospital treatment access' predicted distress(stress, depression, anxiety, anger) at both Time1 and 2. 'Difficulties with official schedule' predicted distress at Time 1, and age, vulnerability to infection and difficulties with personal schedules predicted distress(stress, depression, anxiety, anger) at Time 2. Based on the reseults, implications and recommendations were presented.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.30-30
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• 2023

This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.