• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.211-222
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• 2013

Discovering zones which a1re sets of geographically adjacent regions are essential in sophisticated urban developments and people's movement improvements. While there are some studies that separately focus on movements between particular regions and zone discovery, they show limitations to understand people's movements from a wider viewpoint. Therefore, in this research, we propose a clustering based analysis method that aims at discovering movement patterns, which involves zones and their relations, based on a big data of smart card transaction systems. Moreover, the effectiveness of discovered movement patterns is quantitatively evaluated by using the proposed metrics. By using a real-world dataset obtained in Seoul metropolitan subway networks, we investigate and visualize hidden movement patterns in Seoul.

• The Journal of Bigdata
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• v.5 no.1
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• pp.55-63
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• 2020

This study proposed an approach of clustering collective users' activities of location-based social networks using check-in data of Foursquare users in Seoul. In order to cluster the collective activities, we generated sequential rules of the activities using sequential rule mining, and then constructed activity networks based on the rules. We analyzed the activity networks to identify network structure and hub activities, and clustered the activities within the networks. Unlike previous studies that analyzed activity transition patterns of location-based social network users, this study focused on analyzing the structure and clusters of successive activities. Hubs and clusters of activities with the approach proposed in this study can be used for location-based services and marketing. They could also be used in the public sector, such as infection prevention and urban policies.

• Smart Media Journal
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• v.12 no.8
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• pp.26-36
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• 2023

The purpose of this study is to propose ways to revitalize the local economy by analyzing the index changes and tourism big data before and after the opining of the KTX on the Gangneung Line in Gangneung City, where the population continues to decline. For This, the main current status of Gangneung-si and internal operation record data(DTG) of Gangneung-si were analyzed. After that, changes in the movement behavior of public transportation users before and after the opening of the KTX Gangneung Line were compared. As a result, it was possible to observe changes in tourist transportation preferences, demographic shifts, alterations in small-scale business sectors and in the travel patterns of tourists within the city of Gangneung. In particular, changes in the small business sector have shown an increase in general restaurants, leisure food establishments(cafes, etc.), and accommodation facilities following the opening of the KTX Gangneung Line. All three sectors have experienced growth concentrated in the vicinity of Gangneung Station, indicating the influence of Gangneung Station, which opened in the central part of Gangneung city, following the inauguration of the KTX Gangneung Line.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.54-69
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• 2023

This study investigated the distribution of users in urban parks to overcome the limitations of existing research, which made it difficult to determine where data came was collected. It aimed to provide implications for park planning and management based on user distribution using mobile signal data. Five urban parks in Seongdong-gu, Seoul, with various physical characteristics, were selected. Mobile signal data provided by the Seoul Big Data Campus was used to identify the distribution of user inflow through hot spot analysis per park. The relationship between urban context and park influence area was derived. Seoul Forest (P1) and Seongsu Park (P3), which have a high proportion of commercial spaces around the park, showed wider user hotspots compared to Eungbong Park (P2), Dokseodang Park (P4), and Daehyunsan Park (P5), which were located in residential areas. Parks with a significant presence of commercial spaces had a broader influence, while parks with larger sizes and gentle slopes exhibited wider influence areas. This study proposed a novel data-based approach to urban park planning and management based on the inflow distribution of park users. Through this research, valuable insights were derived that could be utilized for urban park planning and management, aiming to enhance the effectiveness and efficiency of park utilization.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.409-422
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• 2017

TOD (Transit-Oriented Development) is one of the urban structure concentrated on the multifunctional space/district with public transportation system, which is introduced for maintaining sustainable future cities. With such trends, the project of building complex transferring centers located at a urban railway station has widely been spreaded and a comprehensive and systematic analytical framework is required to clarify and readily understand the complicated procedure of estimation with the large scale of the project. By doing so, this study is to develop a comprehensive analytical framework for estimating a pedestrian OD matrix using a spatial information and an integrated smart card data, which is so called a data depository and it has been applied to the Samseong station for the model validation. The proposed analytical framework contributes on providing a chance to possibly extend with digitalized and automated data collection technologies and a BigData mining methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.338-338
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• 2023

최근 특정 지역에 짧은 시간동안 많은 강우가 내리는 국지성 집중호우가 빈번히 발생하고 있으나, 이에 대한 예측과 대비에도 불구하고 피해는 지속적으로 증가하고 있다. 지속적인 강우량 증가 추이로 시간최대 및 일최대 강우량 관측기록이 해마다 갱신되고, 도시, 하천 및 주요 홍수방어 시설의 설계용량을 초과하는 피해가 발생하고 있다. 다수의 인구가 거주하고 대규모 기반시설이 집중된 도시지역에서 발생하는 집중호우는 심각한 인명 및 재산피해로 이어질 수 있다. 따라서, 부처별 재난의 저감대책은 정량적인 피해규모의 피해금액 예측보다는 설계 빈도에 대한 규모의 크기로 대책을 마련하고 있다. 국내에서는 풍수해 피해를 저감시키기 위해 개발에 따르는 재해영향요인을 개발 사업 시행 이전에 예측·분석하고 적절한 저감대책안을 수립·시행하고 있으나 설계빈도에 대한 규모일 뿐 정량적인 저감대책으로 예방되는 피해금액은 알 수 없다. 본 연구에서는 재해연보를 기반으로 호우재해(호우, 태풍)에 대한 시군구-재해기간의 피해데이터를 1999년부터 2019년까지 총 20년의 빅데이터와 전국 68개 강우관측소를 대상으로 총 20년(1999년 ~ 2019년)의 강우자료를 구축하였다. 머신러닝의 학습별 알고리즘을 조사하여 호우재해 피해데이터의 적용성이 높고 다양한 분야에 적용이 가능한 Neural networks의 분석기술인 ANN기법을 선정하였다 피해데이터의 재해발생기간별 총강우량, 일최대강우량, 총피해금액에 대하여 1999년 ~ 2018년을 학습하고 2019년에 대하여 강우특성과 피해특성의 분석하였다. 분석결과 Neural Networks의 지도학습은 총 6,902개 중 2019년을 제외한 6,414개를 학습하였으며 분석 타깃은 호우재해의 피해규모를 분석할 수 있는 총강우량, 일최대강우량, 총피해금액에 대하여 은닉노드 5개씩 2계층에 대하여 분석하였다.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.157-171
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• 2021

The purpose of this study is to assess the smart city for major cities in Korea. The assessment indicators are based on the STIM structure (Service, Technology, Infrastructure, and Management Layer Architecture) of the Multi-Layered Smart City Model. Assessment indicators are established through smart city concepts, case analysis, big data analysis, as well as weighted through expert AHP survey. For the assessment, seven major metropolitan cities are selected, including Seoul, and their data such as KOSIS, KISDISTAT from 2017 to 2019 is utilized for the smart city level assessment. The smart city level results show that the service, technology, infrastructure, and management levels were relatively high in Seoul and Incheon, which are metropolitan areas. Whereas, Busan, Daegu, and Ulsan, the Gyeongsang provinces are relatively moderate, while Daejeon and Gwangju, the South Chungcheong region and the Jeolla provinces, were relatively low. The overall STIM ranking shows a similar pattern, as the Seoul metropolitan area smart city level outperforms the rest of the analyzed areas with a large difference. Accordingly, balanced development strategies are needed to reduce gaps in the level of smart cities in South Korea, and respective smart city plans are needed considering the characteristics of each region. This paper will follow the literature review, assessment index establishment, weight analysis of assessment index, major cities assessment and result in analysis, and conclusion.

• Land and Housing Review
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• v.13 no.1
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• pp.99-112
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• 2022

There is growing significance in securing urban parks and enhancing their accessibility due to irrational residential developments and apartment construction. Accordingly, Daejeon Metropolitan City has carried out urban park management projects to improve the quality of parks and create new parks. Daejeon Metropolitan City generates and manages park data for the purpose of management by the administrative district. However, these datasets take different forms in each administrative district. This study integrates the park data in Daejeon, generated by administrative districts, into the same format and generates geographic information data with the area information of each park for analysis. Analysis results show that urban parks are severely imbalanced across administrative districts, requiring new policy measures. In addition, by normalizing the park analysis results and, then, creating their rankings, this study compares them with the actual park information in detail to confirm the soundness of the dataset. The analysis results provide implications to improve the management of urban parks. This study proposes integrated datasets and the continued management of them in each administrative district by including essential data that can feature the objective information of the parks along with park evaluation indicators based on previous studies.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.188-199
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• 2023

CCTV is widely used as a crime prevention method globally; however, there is insufficient evidence regarding its effectiveness. This study assesses the suitability of CCTV locations and their impact on crime prevention. First, to analyze the appropriateness of the location of CCTVs, we overlaid the locations of crimes and CCTV, and found that there are many cases where CCTV were placed where crime rarely occurred. Using various cases, we verified CCTV's crime prevention effectiveness. The WDQ was applied to comprehensively analyze the impact of CCTV surveillance area and surrounding areas to determine the crime prevention effect. As a result of the analysis, CCTV was found to be effective in preventing crime. In 53.09% of the cases, there was a diffusion effect of crime control benefits in the surrounding area, which was four times more than the cases with a transfer effect. Thus, strategically installing CCTV in appropriate locations enhances crime prevention effectiveness based on spatial analysis.