• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.63-70
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• 2017

On the spatial information open platform, the national spatial data are released to provide services that the people can use freely. Recently, the demand for high quality 3D geospatial information and indoor spatial information is increasing. However, open platform is not able to provide seamless service because spatial data of indoor and outdoor are composed of different formats and storage structures. In addition, the 3D data format used in the current service does not reflect the recent changes in service environment and new technology. Therefore, in this study, we proposed new format of 3D data used in service to improve interoperability and service of open platform 3D data. The proposed format is lighter than the existing format and the rendering speed is improved.

• Journal of Information Technology Applications and Management
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• v.12 no.1
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• pp.35-48
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• 2005

An architectural framework is developed for integrating geospatial and temporal data with relational information from which a spatio-temporal data warehouse (STDW) system is built. In order to implement the STDW, a generic conceptual model was designed that accommodated six dimensions: spatial (map object), temporal (time), agent (contractor), management (e.g. planting) and tree species (specific species) that addressed the 'where', 'when', 'who', 'what', 'why' and 'how' (5W1H) of the STDW information, respectively. A formal algebraic notation was developed based on a triplet schema that corresponded with spatial, temporal, and relational data type objects. Spatial object structures and spatial operators (spatial selection, spatial projection, and spatial join) were defined and incorporated along with other database operators having interfaces via the generic model.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.151-156
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• 2002

Recently, as the geographic information system (GIS) which searches, manages geographic information is used more widely, there is more requests for some systems which can search and display more actual and realistic information. As a response to these requests, the video geographic information system which connects video data obtained by using cameras and geographic information as it is by displaying the obtained video data is being more popular. However, because most existing video geographic information systems consider video data as an attribute of geographic information or use simple one-way links from geographic information to video data to connect video data with geographic information, they support only displaying video data through searching geographic information. In this paper, we design and implement a video geographic information system which connects video data with geographic information and supports hi-directional search; searching geographic information through searching video data and searching video data through searching geographic information. To do this, we 1) propose an ER data model to represent connection information related to video data, geographic information, 2) propose a process to extract and to construct connection information from video data and geographic information, 3) show a component based system architecture to organize the video geographic information system.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.36-40
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• 2008

SIMS manages data for various spatial and non-spatial as integral management system to support space information administration environment and support several application works. Without being limited to spatial data that existent spatial Data Mining question language advances handling in this paper, did so that can find useful information from various data connected with automatically data collection, artificial satellite side upside service, remote sensing, GPS. Mobile Computing and data about Spatio-Temporal. Also, we designed spatial Data Mining query language that support a spatial Data Mining exclusive use system based on SIMS.

• Journal of KIBIM
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• v.10 no.1
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• pp.1-8
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• 2020

In managing building facilities, spatial information is the basic data for decision making. However, the method of acquiring spatial information is not easy. In many cases, the site and drawings are often different due to changes in facilities and time after construction. In this case, the site data should be scanned to obtain spatial information. The scan data actually contains spatial information, which is a great help in making space related decisions. However, to obtain scan data, an expensive LiDAR (Light Detection and Ranging) device must be purchased, and special software for processing data obtained from the device must be available.Recently, SLAM (Simultaneous localization and mapping), an advanced map generation technology, has been spreading in the field of robotics. Using SLAM, 3D spatial information can be obtained quickly in real time without a separate matching process. This study develops and tests whether SLAM technology can be used to obtain spatial information for facility management. This draws considerations for developing a SLAM device for real-time remote scanning for facility management. However, this study focuses on the system development method that acquires spatial information necessary for facility management through SLAM technology. To this end, we develop a prototype, analyze the pros and cons, and then suggest considerations for developing a SLAM system.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.29-36
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• 2017

In this paper, we implement a spatial big data analysis prototype based on Spark which is an in-memory system and compares the performance by the spatial split algorithm on this basis. In cluster computing environments, big data is divided into blocks of a certain size order to balance the computing load of big data. Existing research showed that in the case of the Hadoop based spatial big data system, the split method by spatial is more effective than the general sequential split method. Hadoop based spatial data system stores raw data as it is in spatial-divided blocks. However, in the proposed Spark-based spatial analysis system, there is a difference that spatial data is converted into a memory data structure and stored in a spatial block for search efficiency. Therefore, in this paper, we propose an in-memory spatial big data prototype and a spatial split block storage method. Also, we compare the performance of existing spatial split algorithms in the proposed prototype. We presented an appropriate spatial split strategy with the Spark based big data system. In the experiment, we compared the query execution time of the spatial split algorithm, and confirmed that the BSP algorithm shows the best performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.485-497
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• 2007

By the rapid development of Information Communication Technology (ICT) and Geo-spatial Technology (GT) and the increased usage of spatial data for planning and infrastructure management, the National Geographic Information System (NGIS) for more efficient and effective utilization of spatial information has been developed by the central government in Korea since 1995. NGIS is the base of Spatial Data Infrastructure (SDI). SDI is developed as one of National Information Infrastructures (NII). Among the hierarchy of SDI, National Spatial Data Infrastructure (NSDI) has very important role in the success of SDI development. Many research articles show that the USA's NSDI initiatives, development strategy have been strongly influenced all over the world. In these viewpoints, to propose the future directions of Korean NGIS, the development of NSDI strategy of USA is reviewed by literature through published book and internet resources. The conclusions of this study are as follow: 1) top-down and bottom-up approach are needed for integrated data sharing and standardization. 2) the creative and evolutionary vision and strategy has to be suggested. 3) the training program and lecture material has to be developed and diffused to the users and providers of spatial data. 4) governance system has to be built for NSDI evaluation. 5) the formation of geo-spatial forum to discuss the spatial-related problems and make research agenda, etc.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1259-1276
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of Internet of Things (IoT) technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatialtemporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.81-91
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• 2007

In this paper, we have proposed the non-duplication loading method for supporting spatio-temporal analysis in spatial data warehouse. SDW(Spatial Data Warehouse) extracts spatial data from SDBMS that support various service of different machine. In proposed methods, it extracts updated parts of SDBMS that is participated to source in SDW. And it removes the duplicated data by spatial operation, then loads it by integrated forms. By this manner, it can support fast analysis operation for spatial data and reduce a waste of storage space. Proposed method loads spatial data by efficient form at application of analysis and prospect by time like spatial mining.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.801-803
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• 2003

In this paper, we present a method for generating and providing spatially encoded video data that can be effectively used by GIS applications. We collect the video data by a mobile mapping system called 4S-Van that is equipped by GPS, INS, CCD camera, and DVR system. The information about spatial object appearing in video, such as occupied region in each frame, attribute value, and geo-coordinate, are generated and encoded. We suggest methods that can generate such data for each frame in semi-automatic manner. We adopt standard MPEG-7 metadata format for representation of the spatially encoded video data to be generally used by GIS application. The spatial and attribute information encoded to each video frame can make visual browsing between map and video possible. The generated video data can be provided and applied to various GIS applications where location and visual data are both important.