• Title/Summary/Keyword: 도시공간빅데이터

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Development of the Guidelines for Expressing Big Data Visualization (공간빅데이터 시각화 가이드라인 연구)

  • Kim, So-Yeon;An, Se-Yun;Ju, Hannah
    • The Journal of the Korea Contents Association
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    • v.21 no.2
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    • pp.100-112
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    • 2021
  • With the recent growth of the big data technology market, interest in visualization technology has steadily increased over the past few years. Data visualization is currently used in a wide range of disciplines such as information science, computer science, human-computer interaction, statistics, data mining, cartography, and journalism, each with a slightly different meaning. Big data visualization in smart cities that require multidisciplinary research enables an objective and scientific approach to developing user-centered smart city services and related policies. In particular, spatial-based data visualization enables efficient collaboration of various stakeholders through visualization data in the process of establishing city policy. In this paper, a user-centered spatial big data visualization expression request method was derived by examining the spatial-based big data visualization expression process and principle from the viewpoint of effective information delivery, not just a visualization tool.

A Study on the Spatial Patterns of Tweet Data for Urban Areas by Time - A Case of Busan City - (도시 지역 트윗 데이터의 시간대별 공간분포 특성 - 부산광역시를 사례로 -)

  • Ku, Cha Yong
    • Journal of Cadastre & Land InformatiX
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    • v.46 no.2
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    • pp.269-281
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    • 2016
  • The process of spatial big data, such as social media, is being paid more attention in the field of spatial information in recent years. This study, as an example of spatial big data analysis, analyzed the spatial and temporal distribution of Tweet data based on the location and time information. In addition, the characteristics of its spatial pattern by times were identified. Tweet data in Busan city are collected, processed, and analyzed to identify the characteristics of the temporal and spatial pattern. Then, the results of Tweet data analysis were compared with the characteristics of the land type. This study found that spatial pattern of tweeting in the city was associated with given time periods such as daytime and nighttime in both weekdays and weekends. The spatial distribution patterns of individual time periods were compared with the characteristics of the land for the spatially concentrated area. The results of this study showed that tweeted data would be related to different spatial distribution depending on the time, which potentially reflects the daily pattern and characteristics of the land type of urban area to some extent. This study presented the possible incorporation of social media data, e. g. Tweet data, into the field of spatial information. It is expected that there will be more advantage to use a variety of social media data in areas such as land planning and urban planning.

A Study on the Change of Smart City's Issues and Perception : Focus on News, Blog, and Twitter (스마트도시의 이슈와 인식변화에 관한 연구 : 뉴스, 블로그, 트위터 자료를 중심으로)

  • Jang, Hwan-Young
    • Journal of Cadastre & Land InformatiX
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    • v.49 no.2
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    • pp.67-82
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    • 2019
  • The purpose of this study is to analyze the issues and perceptions of smart cities. First, based on the big data analysis platform, big data analysis on smart cities were conducted to derive keywords by year, word cloud, and frequency of generation of smart city keywords by time. Second, trend and flow by area were analyzed by reclassifying major keywords by year based on meta-keywords. Third, emotional recognition flow for smart cities and major emotional keywords were derived. While U-City in the past is mostly centered on creating infrastructure for new towns, recent smart cities are focusing on sustainable urban construction led by citizens, according to the analysis. In addition, it was analyzed that while infrastructure, service, and technology were emphasized in the past, management and methodology were emphasized recently, and positive perception of smart cities was growing. The study could be used as basic data for the past, present and future of smart cities in Korea at a time when smart city services are being built across the country.

A Time Series Analysis of Urban Park Behavior Using Big Data (빅데이터를 활용한 도시공원 이용행태 특성의 시계열 분석)

  • Woo, Kyung-Sook;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.48 no.1
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    • pp.35-45
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    • 2020
  • This study focused on the park as a space to support the behavior of urban citizens in modern society. Modern city parks are not spaces that play a specific role but are used by many people, so their function and meaning may change depending on the user's behavior. In addition, current online data may determine the selection of parks to visit or the usage of parks. Therefore, this study analyzed the change of behavior in Yeouido Park, Yeouido Hangang Park, and Yangjae Citizen's Forest from 2000 to 2018 by utilizing a time series analysis. The analysis method used Big Data techniques such as text mining and social network analysis. The summary of the study is as follows. The usage behavior of Yeouido Park has changed over time to "Ride" (Dynamic Behavior) for the first period (I), "Take" (Information Communication Service Behavior) for the second period (II), "See" (Communicative Behavior) for the third period (III), and "Eat" (Energy Source Behavior) for the fourth period (IV). In the case of Yangjae Citizens' Forest, the usage behavior has changed over time to "Walk" (Dynamic Behavior) for the first, second, and third periods (I), (II), (III) and "Play" (Dynamic Behavior) for the fourth period (IV). Looking at the factors affecting behavior, Yeouido Park was had various factors related to sports, leisure, culture, art, and spare time compared to Yangjae Citizens' Forest. The differences in Yangjae Citizens' Forest that affected its main usage behavior were various elements of natural resources. Second, the behavior of the target areas was found to be focused on certain main behaviors over time and played a role in selecting or limiting future behaviors. These results indicate that the space and facilities of the target areas had not been utilized evenly, as various behaviors have not occurred, however, a certain main behavior has appeared in the target areas. This study has great significance in that it analyzes the usage of urban parks using Big Data techniques, and determined that urban parks are transformed into play spaces where consumption progressed beyond the role of rest and walking. The behavior occurring in modern urban parks is changing in quantity and content. Therefore, through various types of discussions based on the results of the behavior collected through Big Data, we can better understand how citizens are using city parks. This study found that the behavior associated with static behavior in both parks had a great impact on other behaviors.

4차산업혁명과 게임이론에 관한 연구

  • Gwon, Chang-Hui
    • Journal of Integrative Natural Science
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    • v.15 no.1
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    • pp.49-53
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    • 2022
  • 본 논문은 기존의 도시개발정책에서 경제적 관점에서 가치의 중심을 두었다면 4차산업혁명시대에는 서비스적 가치변환을 추구하고 있다. 시공간을 공유하는 사람 중심의 공간 서비스요, 가치의 용광로가 메타버스라고 한다면, 오징어게임과 같은 게임이론이 접목된 도시의 미래상을 고려할 필요가 있다. 4차산업 기술과 서비스가 사회로 침투되면서 도시의 공간 인프라, 동산 부동산, 객체들을 물리적공간과 가상공간에서 인공지능과 빅데이터 분석이 개입된 각종 형태와 형식의 컨텐츠가 입체적으로 생동감을 얻게 되었다. 특히, 코로나19을 맞아 메타버스기반 서비스가 대중들에게도 접근하기 시작하면서 지금까지 경험하지 못했던 메타버스 시민의 역할에 대한 필요성이 대두하게 되었다. 4차산업혁명시대의 스마트도시, 메타버스와 게임이론을 연구하였다.

Crime Incident Prediction Model based on Bayesian Probability (베이지안 확률 기반 범죄위험지역 예측 모델 개발)

  • HEO, Sun-Young;KIM, Ju-Young;MOON, Tae-Heon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.4
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    • pp.89-101
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    • 2017
  • Crime occurs differently based on not only place locations and building uses but also the characteristics of the people who use the place and the spatial structures of the buildings and locations. Therefore, if spatial big data, which contain spatial and regional properties, can be utilized, proper crime prevention measures can be enacted. Recently, with the advent of big data and the revolutionary intelligent information era, predictive policing has emerged as a new paradigm for police activities. Based on 7420 actual crime incidents occurring over three years in a typical provincial city, "J city," this study identified the areas in which crimes occurred and predicted risky areas. Spatial regression analysis was performed using spatial big data about only physical and environmental variables. Based on the results, using the street width, average number of building floors, building coverage ratio, the type of use of the first floor (Type II neighborhood living facility, commercial facility, pleasure use, or residential use), this study established a Crime Incident Prediction Model (CIPM) based on Bayesian probability theory. As a result, it was found that the model was suitable for crime prediction because the overlap analysis with the actual crime areas and the receiver operating characteristic curve (Roc curve), which evaluated the accuracy of the model, showed an area under the curve (AUC) value of 0.8. It was also found that a block where the commercial and entertainment facilities were concentrated, a block where the number of building floors is high, and a block where the commercial, entertainment, residential facilities are mixed are high-risk areas. This study provides a meaningful step forward to the development of a crime prediction model, unlike previous studies that explored the spatial distribution of crime and the factors influencing crime occurrence.

An Analysis of Keywords Related to Neighborhood Healing Gardens Using Big Data (빅데이터를 활용한 생활밀착형 치유정원 연관키워드 분석)

  • Huang, Zhirui;Lee, Ai-Ran
    • Land and Housing Review
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    • v.13 no.2
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    • pp.81-90
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    • 2022
  • This study is based on social needs for green healing spaces assumed to enhance mental health in a city. This study proposes development directions through the analysis of modern social recognition factors for neighborhood gardens. As a research method, web information data was collected using Textom among big data tools. Text Mining was conducted to extract elements and analyze their relationship through keyword analysis, network analysis, and cluster analysis. As a result, first, the healing space and the healing environment were creating an eco-friendly healthy environment in a space close to the neighborhood within the city. Second, neighborhood gardens included projects and activities that involved government, local administration, and citizens by linking facilities as well as living culture and urban environments. These gardens have been reinforced through green welfare and service programs. In conclusion, friendly gardens in the neighborhood for the purpose of public interest, which are beneficial to mental health, are green infrastructures as a healing environment that can produce positive effects.

Interactive Map-based Spatio-Temporal Visualization of Typhoon Situation using Web News BigData (웹 뉴스 빅데이터를 이용한 태풍 상황정보의 인터렉티브 지도 기반 시공간 시각화 방안)

  • Lee, Jiae;Kim, Junchul
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.773-776
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    • 2020
  • 웹 뉴스 기사는 태풍과 같은 재해 발생상황에 대한 신속하고 정확한 정보를 포함하고 있다. 예를 들어, 태풍의 발생시점, 이동·예측경로, 피해·사고 현황 등 유용한 정보를 텍스트, 이미지, 동영상의 형태로 관련 상황정보를 전달한다. 그러나 대부분의 재해재난 관련 뉴스 기사는 특정 시점의 정보만을 웹페이지 형태로 제공하므로, 시계열 측면의 연결성을 지니는 기사들에 대한 정보를 전달하기 어렵다. 또한 시간적 변화에 따라 기사 내용에 포함된 장소, 지역, 건물 등의 지명에 대한 공간적 정보를 지도와 연계하여 정보를 전달하는데 한계가 있어, 시공간적 변화에 따른 특정 재해재난 상황정보에 대한 전체적인 현황파악이 어렵다. 따라서, 본 논문에서는 데이터 시각화 측면에서 이러한 한계를 극복하기 위해, 1) 웹크롤링을 통해 구축된 뉴스 빅데이터를 자연어 처리를 통해 태풍과 관련된 뉴스 기사들을 추출하였고, 2) 시공간적 관련 정보를 지식그래프로 구축하였고, 이를 통해 최근 발생한 태풍 사건들과 관련된 뉴스 정보를 시계열 특성을 고려하여 3) 인터렉티브 지도 기반의 태풍 상황정보를 시각화하는 방안을 연구하였다.

A Study on the Regionally Customized Urban Regeneration and Maintenance of Small and Medium Cities Using Spatial Big-Data - Focused on the Residential Census Output Area - (공간 빅데이터를 활용한 중소도시 지역맞춤형 도시재생·유지관리 연구 - 주거지역 집계구를 중심으로 -)

  • Han, Da-Hyuck;Lee, Min-Seok
    • Journal of the Korean Institute of Rural Architecture
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    • v.23 no.2
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    • pp.9-16
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    • 2021
  • The purpose of this study is to maintain the existing characteristics of the city by utilizing the physical decline status and floating population in small and medium cities residential areas. In addition, it intends to present the direction of flexible urban regeneration and maintenance by reflecting regional characteristics and current status. A total of three data were used in this study. Building data, floating population data, and census output area data were used. Building data and floating population data were classified into five classes. The graded data were joined to the census output area data and analyzed by overlapping the two data. As a result of analysis of 17 residential areas in 5 small and medium cities in Jeollanam-do, 4 types, 2 management models, and 4 indicators could be presented by grade and regional characteristics. This study is meaningful in that it is possible to plan regionally customized urban regeneration/maintenance management plans and projects through the typology of the current status and characteristics of the region, which is an important step in the bottom-up form.

Interview - "From January next year, we will set up a system of cooperation by operating a Pool of 'green-light architects' and concentrate our efforts on enhancing space welfare (인터뷰 - "내년부터 아틀리에나 신진건축사 등용문 프로그램 만들 예정")

  • Jang, Yeong-Ho
    • Korean Architects
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    • s.596
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    • pp.28-44
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    • 2018
  • "SH공사(서울주택도시공사)가 내년 1월부터 '청신호 건축사'라는 이름으로 전문가 인력풀(Pool)을 운영하고, 매입임대를 늘려 신축 리모델링에서 역할을 할 수 있도록 제도화할 계획입니다. 그동안 SH공사가 '주거복지'에 주력해 왔는데, 인공지능과 빅데이터 등을 결합해 앞으로는 한 단계 발전한 '공간복지'로 정책기조를 확대하려 합니다. 이 일을 수행키 위해서 도시설계가, 조경가도 투입될 것입니다." 김세용 SH공사 사장은 최근 서울시 강남구 개포로 SH공사 사옥에서 본지와 인터뷰를 하고, '디자인건축'을 표방한 '청신호 건축사' 전문가인력풀(Pool)을 운영하겠다고 밝혔다. SH공사는 20 30대 청년과 신혼부부에게 공급하는 임대주택에는 내년부터 '청신호'라는 자체 브랜드를 적용한다. 올 1월 취임한 김세용 SH공사 사장은 서울시의 캠퍼스타운조성 시범사업을 총괄 지휘한 바 있다. 이 같은 경험을 토대로 ▲ SH공사 브랜드 가치 제고 ▲ 주택품질 개선 ▲ 임대주택사업 추진 방식 다양화 등을 위한 사업들을 이끌고 있는데, 특히 기존에는 단순히 주거기능만 제공하던 공공아파트를 공동체 생활기능이 접목된 커뮤니티로 발전시키는 '공간복지'를 강화하는데 역량을 집중하고 있다.

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