• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.4
• /
• pp.217-233
• /
• 2020

This study evaluated the urban vitality of Daegu metropolitan city in 2018 using emerging geographic data such as spatial big data, Wi-Fi AP(access points) and nighttime light satellite image. The emerging geographic data were used in this research to quantify human activities in the city more directly at various spatial and temporal scales. Three spatial big data such as mobile phone data, credit card data and public transport smart card data were employed to reflect social, economic and mobility aspects of urban vitality while public Wi-Fi AP and nighttime light satellite image were included to consider virtual and physical aspects of the urban vitality. With PCA (Principal Component Analysis), five indicators were integrated and transformed to the urban vitality index at census output area by temporal slots. Results show that five clusters with high urban vitality were identified around downtown Daegu, Daegu bank intersection and Beomeo intersection, Seongseo, Dongdaegu station and Chilgok 3 district. Further, the results unveil that the urban vitality index was varied over the same urban space by temporal slots. This study provides the possibility for the integrated use of spatial big data, Wi-Fi AP and nighttime light satellite image as proxy for measuring urban vitality.

• Journal of Korea Water Resources Association
• /
• v.54 no.2
• /
• pp.81-91
• /
• 2021

Synthetic Apreture Radar (SAR) is attracting attentions with its possibility of producing high resolution data that can be used for soil moisture estimation. High resolution soil moisture data enables more specific observation of soil moisture than existing soil moisture products from other satellites. It can also be used for studies of wildfire, landslide, and flood. The SAR based soil moisture estimation should be conducted considering vegetation, which affects backscattering signals from the SAR sensor. In this study, a SAR based soil moisture estimation at regions covered with various vegetation types on the middle area of Korea (Cropland, Grassland, Forest) is conducted. The representative backscattering model, Water Cloud Model (WCM) is used for soil moisture estimation over vegetated areas. Radar Vegetation Index (RVI) and in-situ soil moisture data are used as input factors for the model. Total 6 study areas are selected for 3 vegetation types according to land cover classification with 2 sites per each vegetation type. Soil moisture evaluation result shows that the accuracy of each site stands out in the order of grassland, forest, and cropland. Forested area shows correlation coefficient value higher than 0.5 even with the most dense vegetation, while cropland shows correlation coefficient value lower than 0.3. The proper vegetation and soil moisture conditions for SAR based soil moisture estimation are suggested through the results of the study. Future study, which utilizes additional ancillary vegetation data (vegetation height, vegetation type) is thought to be necessary.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.24 no.4
• /
• pp.31-46
• /
• 2021

In South Korea, there is a growing domestic need for a biotope map which contains ecological and environmental geographic information of a city. After the production of a Urban Ecological Maps(biotope map) by the Seoul metropolitan government in 2000, Natural Environment Conservation Act was revised in 2017 to make it mandatory for a local government to draw up its own urban ecological map. The aim of the present study was to find out ways to utilize an urban ecological map as a mean of communication between natural environment planning and urban planning sectors in a preliminary stage before introducing a big framework of 'environmental and ecological planning.' The northern area of Incheon metropolitan city was selected as the target area for this study. The major research content includes a comparative analysis of special-purpose zones, urban planning zones, restricted development zones, and conservation forests with focus on biotope types and Grades 1 of 'Biotope Type Assessment.' Farmland biotopes and forest biotopes within an area designated as an urban zone (residential, commercial and industrial zones) need to be redesignated as a zone which can conserve them. Especially considering a high possibility of damage to a large scale of natural green areas, these areas need to be readjusted immediately. If the entire area designated as an urban planning zone is to be developed, it is likely to cause serious damage to natural biotopes in the area (56.2%), including farmland biotope (30.4%), forest biotope (15.0%) and grassland biotope (10.8%), and thus, readjustment is needed. In case of a conservation forest, as it can possibly be damaged by the designation of special-purpose zones, it is necessary to match the designation of conservation forests or a special-purpose zones with their biotope types. In conclusion, we present a variety of thematic maps for utilization of an urban ecological map and propose a phase-specific environmental and ecological plan. Phase 1 is the establishment of a urban plan in consideration of ecological status; Phase 2 is the independent establishment of an environmental and ecological plan by an environment department; Phase 3 is an integrated management of ecological planning system and urban planning system.

• Journal of Navigation and Port Research
• /
• v.46 no.3
• /
• pp.269-279
• /
• 2022

With the development of artificial intelligence, artificial intelligence is being introduced to automate systems throughout the industry. In the maritime industry, artificial intelligence is being applied step by step, through the paradigm of autonomous ships. In line with this trend, ABS and DNV have published guidelines for autonomous vessels. However, there is a possibility that the risk of artificial intelligence has not been sufficiently considered, as the classification guidelines describe the requirements from the perspective of ship operation and marine service. Thus in this study, using the standards established by the ISO/ IEC JTC1/SC42 artificial intelligence division, classification requirements are classified as the causes of risk, and a measure that can evaluate risks through the combination of risk causes and artificial intelligence metrics want to use. Through the combination of the risk causes of artificial intelligence proposed in this study and the characteristics to evaluate them, it is thought that it will be beneficial in defining and identifying the risks arising from the introduction of artificial intelligence into the marine system. It is expected that it will enable the creation of more detailed and specific safety requirements for autonomous ships.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1047-1056
• /
• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.

• The Korean Society of Law and Medicine
• /
• v.23 no.2
• /
• pp.119-139
• /
• 2022

Brain stimulation technology that administers electrical and magnetic stimulation to a brain has shown a significant level of possibility for treating a wide range of various neurological and psychiatric disorders. Depending on its nature, the technology is defined either as invasive or non-invasive, and deep brain stimulation (DBS) is one of the most well-known invasive brain stimulation technologies. Currently categorized as grade 4 medical device in accordance with Guideline On Medical Devices And Their Grades, a Notification of Ministry of Food and Drug Safety (MFDS), the DBS has been used as a stable treatment for several diseases. At the same time, the DBS technology has recently achieved substantial advancement, encouraging active discussions for its use from various perspectives. On the contrary, debates over legal regulation related to the use of DBS has relatively been smaller in numbers. In this context, this article aims to 1) introduce the DBS technology and its safety in setting out the tone; 2) touch upon major legal issues that would potentially rise from its use for four different purposes of treatment, clinical study, areas of non-standard treatment where no other methods are available, and enhancement; and finally 3) highlight disputes concerning common emerging issues observed in the aforementioned four purposes from the viewpoint of legal responsibility and liability of using the DBS, which are benefit-risk assessment, physicians' duty of information, patients' capacity to consent, control for device, and insurance coverage.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.26 no.5
• /
• pp.30-42
• /
• 2022

Due to the increase in construction of tunnels, the burdens of maintenance works for tunnel structures have been increasing in Korea. In addition, the increase of traffic volume and aging of materials also threatens the safety of tunnel facilities, therefore, maintenance costs are expected to increase significantly in the future. Accordingly, automated condition assessment technologies like image-based tunnel scanning system for inspection and diagnosis of tunnel facilities have been proposed. For image-based tunnel scanning system, it is key to create a planar image through stitching of multiple images captured by tunnel scanning system. In this study, performance of feature-based stitching algorithms suitable for stitching tunnel scanning images was evaluated. In order to find a suitable algorithm SIFT, ORB, and BRISK are compared. The performance of the proposed algorithm was determined by the number of feature extraction, calculation speed, accuracy of feature matching, and image stitching result. As for stitching performance, SIFT algorithm was the best in all parts of tunnel image. ORB and BRISK also showed satisfactory performance and short calculation time. SIFT can be used to generate precise planar images. ORB and BRISK also showed satisfactory stitching results, confirming the possibility of being used when real-time stitching is required.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_1
• /
• pp.571-585
• /
• 2022

As the threat of natural disasters such as droughts, floods, forest fires, and landslides increases due to climate change, social demand for high-resolution soil moisture retrieval, such as Synthetic Aperture Radar (SAR), is also increasing. However, the domestic environment has a high proportion of mountainous topography, making it challenging to retrieve soil moisture from SAR data. This study evaluated the usability of Sentinel-1 SAR, which is applied with the Artificial Neural Network (ANN) technique, to retrieve soil moisture. It was confirmed that the backscattering coefficient obtained from Sentinel-1 significantly correlated with soil moisture behavior, and the possibility of stand-alone use to correct vegetation effects without using auxiliary data observed from other satellites or observatories. However, there was a large difference in the characteristics of each site and topographic group. In particular, when the model learned on the mountain and at flat land cross-applied, the soil moisture could not be properly simulated. In addition, when the number of learning points was increased to solve this problem, the soil moisture retrieval model was smoothed. As a result, the overall correlation coefficient of all sites improved, but errors at individual sites gradually increased. Therefore, systematic research must be conducted in order to widely apply high-resolution SAR soil moisture data. It is expected that it can be effectively used in various fields if the scope of learning sites and application targets are specifically limited.

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

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.23 no.6
• /
• pp.403-421
• /
• 2021

Most of the urban tunnels in Korea, which are represented by the 1st to 3rd subways, use the drainage tunnel by NATM. Recently, when a construction project that actively utilizes large-scale urban space is promoted, negative effects that do not conform to the existing empirical rules of urban tunnels may occur. In particular, there is a high possibility that groundwater fluctuations and hydrodynamic behavior will occur owing to the practice of tunnel technology in Korea, which has mainly applied the drainage tunnel. In order to solve the problem of the drainage tunnel, attempts are being made to control groundwater fluctuations. For this, the establishment of tunnel groundwater management standard concept and the analysis of the tunnel hydraulic behavior were performed. To prevent the problem of groundwater fluctuations caused by the construction of large-scale tunnels in urban areas, it was suggested that the conceptual transformation of the empirical technical practice, which is applied only in the underground safety impact assessment stage, to the direction of controlling the inflow in the tunnel, is required. And the relationship between the groundwater level and the inflow of the tunnel required for setting the allowable inflow when planning the tunnel was derived. The introduction of a tunnel groundwater management concept is expected to help solve problems such as groundwater fluctuations, ground settlement, depletion of groundwater resources, and decline of maintenance performance in various urban deep tunnel construction projects to be promoted in the future.