• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.579-589
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• 2016

This research focuses on accomplishing analysis problems and issues by examining the policies and systems related to geo-spatial big data which have recently arisen, and suggests political and systemic improvement plan for service activation. To do this, problems and probable issues concerning geo-spatial big data service activation should be analyzed through the examination of precedent studies, policies and planning, pilot projects, the current legislative situation regarding geo-spatial big data, both domestic and abroad. Therefore, eight political and systematical improvement plan proposals are suggested for geo-spatial big data service activation: legislative-related issues regarding geo-spatial big data, establishing an exclusive organization in charge of geospatial big data, setting up systems for cooperative governance, establishing subsequent systems, preparing non-identifying standards for personal information, providing measures for activating civil information, data standardization on geo-spatial big data analysis, developing analysis techniques for geo-spatial big data, etc. Consistent governmental problem-solving approaches should be required to make these suggestions effectively proceed.

• Spatial Information Research
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• v.23 no.6
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• pp.19-29
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• 2015

This study was conducted with the purpose of suggesting the improvement plan of political for activating the Geo-Spatial Big Data Services. To this end, we were review the previous research for Geo-Spatial Big Data and analysis domestic and foreign Geo-Spatial Big Data propulsion system and policy enforcement situation. As a result, we have deduced the problem of insufficient policy of reaction for future Geo-Spatial Big Data, personal information protection and political basis service activation, relevant technology and policy, system for Geo-Spatial Big Data application and establishment, low leveled open government data and sharing system. In succession, we set up a policy direction for solving derived problems and deducted 5 policy issues : setting up a Geo-Spatial Big Data system, improving relevant legal system, developing technic related to Geo-Spatial Big Data, promoting business supporting Geo-Spatial Big Data, creating a convergence sharing system about public DB.

• Spatial Information Research
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• v.21 no.5
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• pp.43-51
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• 2013

In this study, the concept of spatial big data and effective ways to build a spatial big data system are presented. Big Data is defined as 3V(volume, variety, velocity). Spatial big data is the basis for evolution from 3V's big data to 6V's big data(volume, variety, velocity, value, veracity, visualization). In order to build an effective spatial big data, spatial big data system building should be promoted. In addition, spatial big data system should be performed a national spatial information base, convergence platform, service providers, and providers as a factor of production. The spatial big data system is made up of infrastructure(hardware), technology (software), spatial big data(data), human resources, law etc. The goals for the spatial big data system build are spatial-based policy support, spatial big data platform based industries enable, spatial big data fusion-based composition, spatial active in social issues. Strategies for achieving the objectives are build the government-wide cooperation, new industry creation and activation, and spatial big data platform built, technologies competitiveness of spatial big data.

• Spatial Information Research
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• v.22 no.6
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• pp.13-21
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• 2014

This study defines concept and service framework of Geo-Spatial Big Data(GSBD). The major concept of the GSBD is formulated based on the 7V characteristics: the general characteristics of big data with 3V(Volume, Variety, Velocity); Geo-spatial oriented characteristics with 4V(Veracity, Visualization, Versatile, Value). GSBD is the technology to extract meaningful information from Geo-spatial fusion data and support decision making responding with rapidly changing activities by analysing with almost realtime solutions while efficiently collecting, storing and managing structured, semi-structured or unstructured big data. The application area of the GSBD is segmented in terms of technical aspect(store, manage, analyze and service) and public/private area. The service framework for the GSBD composed of modules to manage, contain and monitor GSBD services is suggested. Such additional studies as building specific application service models and formulating service delivery strategies for the GSBD are required based on the services framework.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.64-73
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• 2015

Recent emergence of spatial big data attracts the attention of various research groups. This paper analyzes the research trend on spatial big data by text mining the related Scopus DB. We apply topic model and network analysis to the extracted abstracts of articles related to spatial big data. It was observed that optics, astronomy, and computer science are the major areas of spatial big data analysis. The major topics discovered from the articles are related to mobile/cloud/smart service of spatial big data in urban setting. Trends of discovered topics are provided over periods along with the results of topic network. We expect that uncovered areas of spatial big data research can be further explored.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.217-233
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• 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 the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.385-396
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• 2015

The purpose of this study are in selecting a core service and drawing an analysis functions and service sector, based on contents of geo-spatial big data. For the study, the demand survey in the methodology has to be done by reviewing of preceding geo-spatial big data service. The survey has conducted by targeting on those experts in Industry-Academy-Research cooperation. From the survey, we could draw out requirements for the analysis function and the geo-spatial big data service sector. Also, order of priorities in service of four fields(Society, Environment, Economy, Humanities) has been utilized by a QFD(Quality Function Deployment). With the data, the first two priorities and required sectors for each field were selected for the analysis functions. From the result, we could suggest the core service model(plan), and also expect developments following each sectoral core service in the future.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.645-657
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• 2021

Along with the rapid development of the economy, the urban scale has extended rapidly, leading to the formation of different types of urban function districts (UFDs), such as central business, residential and industrial districts. Recognizing the spatial distributions of these districts is of great significance to manage the evolving role of urban planning and further help in developing reliable urban planning programs. In this paper, we propose an automatic UFD division method based on big data analysis of point of interest (POI) data. Considering that the distribution of POI data is unbalanced in a geographic space, a dichotomy-based data retrieval method was used to improve the efficiency of the data crawling process. Further, a POI spatial feature analysis method based on the mean shift algorithm is proposed, where data points with similar attributive characteristics are clustered to form the function districts. The proposed method was thoroughly tested in an actual urban case scenario and the results show its superior performance. Further, the suitability of fit to practical situations reaches 88.4%, demonstrating a reasonable UFD division result.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.53-58
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• 2020

The purpose of this study is to build a database of Spatial information Bigdata of cities using satellite images and spatial information, and to examine the correlations with the surface temperature. Using architectural structure and usage in building information, DEM and Slope topographical information for constructed with 300 × 300 mesh grids for Busan. The satellite image is used to prepare the Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BI), and Land Surface Temperature (LST). In addition, the building area in the grid was calculated and the building ratio was constructed to build the urban environment DB. In architectural structure, positive correlation was found in masonry and concrete structures. On the terrain, negative correlations were observed between DEM and slope. NDBI and BI were positively correlated, and NDVI was negatively correlated. The higher the Building ratio, the higher the surface temperature. It was found that the urban environment DB could be used as a basic data for urban environment analysis, and it was possible to quantitatively grasp the impact on the architecture and urban environment by adding local meteorological factors. This result is expected to be used as basic data for future urban environment planning and disaster prevention data construction.

• Land and Housing Review
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• v.7 no.1
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• pp.19-29
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• 2016

This study proposes the big data policy and case studies in Korea and the application of land and housing of spatial big data to excavate the future business and to propose the spatial big data based application for the government policy in advance. As a result, at first, the policy and cases of big data in Korea were evaluated. Centered on the Government 3.0 Committee, the information from each department of government is being established with the big-data-based system, and the Ministry of Land, Infrastructure, and Transport is establishing the spatial big data system from 2013 to support application of big data through the platform of national spatial information and job creation. Second, based on the information system established and administrated by LH, the status of national territory information and the application of land and housing were evaluated. First of all, the information system is categorized mainly into the support of public ministration, statistical view, real estate information, on-line petition, and national policy support, and as a basic direction of major application, the national territory information (DB), demand of application (scope of work), and profit creation (business model) were regarded. After the settings of such basic direction, as a result of evaluating an approach in terms of work scope and work procedure, the four application fields were extracted: selection of candidate land for regional development business, administration and operation of rental house, settings of priority for land preservation, and settings of priority for urban generation. Third, to implement the application system of spatial big data in the four fields extracted, the required data and application and analytic procedures for each application field were proposed, and to implement the application solution of spatial big data, the improvement and future direction of evaluation required from LH were proposed.