• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.345-352
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• 2022

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.193-198
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• 2021

In this study, the rheological characteristics and of 3D printing composite materials and the compressive strength characteristics according to the lamination patterns were evaluated. As a result of rheology test, rapid material change was observed after 60 minutes of extrusion, yielding stress 1.4 times higher than immediately after mixing, and plastic viscosity was 14.94-25.62% lower. The compressive strength of the specimens manufactured in the mold and the laminated specimens were compared, and the lamination pattern of the laminated specimens were 0°, 45°, and 90° as variables. The compressive strength of the mold casting specimen and the laminated specimen from 1 to 28 days of age showed similar performance regardless of the lamination pattern. In particular, at the age of 28 days, the modulus of elasticity, maximum compressive strength, and strain at maximum stress of all specimens were almost the same. In order to analyze the interface of the laminated specimens, X-ray CT analysis of the specimen whose compressive strength were measured was performed. Through CT analysis, it was confirmed that cracks did not occur at the lamination interface, which can be judged that the interface in the laminated specimen behaved in an integrated manner.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.589-601
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• 2022

Although drought is a natural phenomenon, its damage occurs in combination with regional physical and social factors. Especially, related to the supply and demand of various waters, drought causes great socio-economic damage. Even meteorological droughts occur with similar severity, its impact varies depending on the regional characteristics and water supply system. Therefore, this study assessed regional drought risk considering regional socio-economic factors and water supply system. Drought hazard was assessed by grading the joint drought management index (JDMI) which represents water shortage. Drought vulnerability was assessed by weighted averaging 10 socio-economic factors using Entropy, Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM). Drought response capacity that represents regional water supply factors was assessed by employing Bayesian networks. Drought risk was determined by multiplying a cubic root of the hazard, vulnerability, and response capacity. For the drought hazard meaning the possibility of failure to supply water, Goesan-gun was the highest at 0.81. For the drought vulnerability, Daejeon was most vulnerable at 0.61. Considering the regional water supply system, Sejong had the lowest drought response capacity. Finally, the drought risk was the highest in Cheongju-si. This study identified the regional drought risk and vulnerable causes of drought, which is useful in preparing drought mitigation policy considering the regional characteristics in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.11-21
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• 2022

Drought occurs extensively over a long period and causes great socio-economic damage. Since drought risk consists of social, environmental, physical, and economic factors along with meteorological and hydrological factors, it is important to quantitatively identify their impacts on drought risk. This study investigated the relationship among drought hazard, vulnerability, response capacity, and risk in Chungcheongbuk-do using a structural equation model and evaluated their impacts on drought risk using Bayesian networks. We also performed sensitivity analysis to investigate how the factors change drought risk. Overall results showed that Chungju-si had the highest risk of drought. The risk was calculated as the largest even when the hazard and response capacity were changed. However, when the vulnerability was changed, Eumseong-gun had the greatest risk. The sensitivity analysis showed that Jeungpyeong-gun had the highest sensitivity, and Jecheon-si, Eumseong-gun, and Okcheon-gun had highest individual sensitivities with hazard, vulnerability, and response capacity, respectively. This study concluded that it is possible to identify impact factors on drought risk using regional characteristics, and to prepare appropriate drought countermeasures considering regional drought risk.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.17-28
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• 2022

This study is to develop the direction of the development of the next-generation mapping of marine information required to develop a base of the utilization localization of maritime production tools. The GIS data-processing products and technologies currently used in the Korea's marine sector depend on external applications which is renewal costs, technical updates, and unreflected characteristics. Meanwhile, the S-100 standard, the next generation hydrographic data model that complements S-57's problems in marine GIS data processing, was adopted as a new marine data standard. This study aims to present the current status and problems of marine GIS technology in Korea and to suggest the development direction of GIS software based on the next generation hydrogrphic data model S-100 standard of IHO(International Hydrographic Organization). S-100-based marine GIS localization technology development and industrial ecosystem development research is expected to scientific decision-making on policy issues that occur with other countries such as marine territory management and development and use of marine resources.

• Journal of Environmental Impact Assessment
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• v.31 no.4
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• pp.214-225
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• 2022

This study emphasized the soil of environmental impact assessment to devise measures to minimize the negative impact of project implementation on the environment. As a series of efforts for impact assessment procedures, a national inventory-based database was established for urban development projects, and three machine learning model performance evaluation as well as soil pollutant concentration distribution mapping were conducted. Here, nine soil pollutants were mapped to the metropolitan area of South Korea using the Random Forest model, which showed the best performance. The results of this study found that concentrations of Zn, F, and Cd were relatively concerned in Seoul, where urbanization is the most active. In addition, in the case of Hg and Cr6+, concentrations were detected below the standard, which was derived from a lack of pollutants such as industrial and industrial complexes that affect contents of heavy metals. A significant correlation between land cover and pollutants was inferred through the spatial distribution mapping of soil pollutants. Through this, it is expected that efficient soil management measures for minimizing soil pollution and planning decisions regarding the location of the project site can be established.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.693-702
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• 2022

The purpose of this study is to present the problems of urban ecosystem imbalance in Seoul and the need to restore housing functions through comparison with Manhattan, New York, which grew earlier than Seoul and has been striving to solve urban problems and restore urban ecosystems. The residential status in urban commercial use areas was investigated through analysis of the total amount of residential space, characteristics of each type of residential building, and distribution of residential buildings. Through this, it can be seen that most of the space in Seoul's historic city center is biased toward commercial roads, and there are significantly insufficient high- and high-density mixed-use buildings suitable for urban dwellings compared to Manhattan's. In addition, it can be seen that the complex building in the historical city center of Seoul is located adjacent to the outskirts of the target site. In conclusion, Seoul's historical city center does not provide an appropriate residential space for creating an urban ecosystem, and it is necessary to come up with measures to restore housing functions.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.855-863
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• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.333-342
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• 2022

Due to climate change, increased heavy rainfalls result in flood damage every year. To investigate the storm-runoff reduction effects of Low Impact Development (LID), this study performed runoff analyses using the U.S. Environmental Protection Agency (EPA) Storm Water Management Model (SWMM) for past and future representative storm events of the Yongdu Rainwater Pumping Station basin. As a result, the infiltration loss for representative future rainfalls increased by 3.17 %, and the surface runoff and peak runoff rate increased significantly by 32.50 %, and 128.77 %, respectively. To reduce the increased surface runoff and peak runoff rates, this study investigated the applicability of LID approaches, including a permeable pavement, green roof, and rain garden, by adjusting the LID parameters and the ratio of installation area. We identified the ranges of LID parameters that decreased peak runoff rate and surface runoff, and increased infiltration. In addition, when the application ratio of permeable pavement, green roof, and rain garden was 2:1:3, best performance was attained, leading to a reduction of peak runoff of 26.85 %, infiltration loss 12.01 %, surface runoff 15.11 %, and storage 509.47 %. Based on analyzing the effect of storm runoff reductions for various return periods, it was found that as the return period increased, the proportion of peak runoff and surface runoff increased and the proportion of infiltration loss and storage decreased.