• Title/Summary/Keyword: spatial data structure

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Deriving Basic Living Service Items and Establishing Spatial Data in Rural Areas (농촌 생활권 기초생활서비스 항목 설정 및 공간데이터 구축을 위한 기초연구)

  • Kim, Suyeon;Kim, Sang-Bum
    • Journal of the Korean Institute of Rural Architecture
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    • v.24 no.3
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    • pp.39-46
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    • 2022
  • This study aims to derive basic living service facility items in rural areas and construct related spatial data. To do this, a literature review on the laws and systems related to the residential environment and services in rural areas, rural spatial planning, and the 'Rural Convention' strategic plan reports for the Jeolla and Gyeongsang Region in 2021 was conducted. Primary data collection and review on the list of basic living service items in rural areas derived from the analysis were conducted. After data collection, 12 sectors and 44 types of rural basic living service items were derived; the data selection was carried out based on the clarity of the subject of data management, whether it was established nationwide, whether it was disclosed and provided, whether it was periodically updated, and whether it was an underlying law. Afterwards, data on the derived rural basic living service items were constructed. Afterwards, spatial data on the derived rural basic living service items were constructed. Because open data provided through various institutions were employed, data structure unification such as data attribute values and code names was needed, and abnormal data such as address errors and omissions were refined. After that, the data provided in text form was converted into spatial data through geocoding, and through comparative review of the distribution status of the converted data and the provided address, spatial data related to rural basic living services were finally constructed for about 540,000 cases. Finally, implications for data construction for diagnosing rural living areas were derived through the data collection and construction process. The derived implications include data unification, data update system establishment, the establishment of attribute values necessary for rural living area diagnosis and spatial planning, data establishment plan for facilities that provide various services, rural living area analysis method, and diagnostic index development. This study is meaningful in that it laid the foundation for data-based rural area diagnosis and rural planning, by selecting the basic rural living service items, and constructing spatial data on the selected items.

Construction of Spatial Information Big Data for Urban Thermal Environment Analysis (도시 열환경 분석을 위한 공간정보 빅데이터 구축)

  • Lee, Jun-Hoo;Yoon, Seong-Hwan
    • 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.

The Effects of Spatial Patterns in Low Resolution Thematic Maps on Geostatistical Downscaling

  • Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.27 no.6
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    • pp.625-635
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    • 2011
  • This paper investigates the effects of spatial autocorrelation structures in low resolution data on downscaling without ground measurements or secondary data, as well as the potential of geostatistical downscaling. An advanced geostatistical downscaling scheme applied in this paper consists of two analytical steps: the estimation of the point-support spatial autocorrelation structure by variogram deconvolution and the application of area-to-point kriging. Point kriging of block data without variogram deconvolution is also applied for a comparison purpose. Experiments using two low resolution thematic maps derived from remote sensing data showing very different spatial patterns are carried out to discuss the objectives. From the experiments, it is demonstrated that the advanced geostatistical downscaling scheme can generate the downscaling results that well preserve overall patterns of original low resolution data and also satisfy the coherence property, regardless of spatial patterns in input low resolution data. Point kriging of block data can produce the downscaling result compatible to that by area-to-point kriging when the spatial continuity in block data is strong. If heterogeneous local variations are dominant in input block data, the treatment of the low resolution data as point data cannot generate the reliable downscaling result, and this simplification should not be applied to donwscaling.

Designing Database Contents of Spatial Data Warehouse and its Data Synchronization with Distributed Geographic Information Systems in Seoul Metropolitan Government (서울시 공간데이터웨어하우스의 내용설계 및 GIS데이터 연동에 관한 연구)

  • 김학열;김윤종;김준기
    • Spatial Information Research
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    • v.11 no.2
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    • pp.119-130
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    • 2003
  • Since GIS strategic implementation plan was prepared in 1995, Seoul Metropolitan Government (SMG) has implemented the distributed GIS at department level, which prevents various SMG organizations from data-sharing and its common utilization. To solve those problems due to the fragmented GIS structure, SMG developed an action plan for the evolution of enterprise GIS with Spatial Data Warehouse (SDW). In this context, this paper initially analyzed the conceptual architecture of SDW structure and then provided the following guidelines for 1) determining the common GIS data and framework data stored at SDW to satisfy the demand for various GIS data from many SMG departments and sub-organizations, 2) developing the data synchronization process and techniques to make effective data-sharing possible, and 3) making an action plan for enterprise GIS of other self-governmental organizations.

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Structure of Particle Clusters Formed in Gas-Solid flows

  • Tanaka, Toshitsugu;Ito, Akihito;Tsuji, Takuya
    • 한국전산유체공학회:학술대회논문집
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    • 2006.10a
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    • pp.26-27
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    • 2006
  • Characteristics of spatial structure of particle clusters are investigated by using the flow field data obtained from three-dimensional numerical simulations. Eulerian/Lagrangian approach with two-way coupling is applied and individual particle-particle collisions are taken into account by using the hard-sphere model. More than 16 million particles are traced in the maximum case. The results show that the cluster is consisted from the multiple-spatial scale components while the low wave-number, hence the large-scale structure, is dominant. Three-dimensional structure reconstructed from the low-pass filtered data enables us to investigate the essential dynamics of particle clusters in detail.

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Analysis of Changes in Urban Spatial Structure for Balanced Urban Development (도시균형발전을 위한 도시공간구조 변화 진단)

  • KIM, Ho-Yong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.2
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    • pp.40-51
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    • 2021
  • The purpose of this study is to diagnose urban spatial structures using spatial modeling techniques for balanced urban development as part of sustainable urban growth management. Since urban spatial structure is an interaction of various activities, it is necessary to interpret the analysis results in conjunction with the analysis of changes in spatial structural elements. In this study, population and transportation were approached for research purposes. Population data were applied to the Getis-Ord Gi* method, a spatial statistical technique, to analyze the concentration-decreasing region of the population. Traffic data analyzed the trend of centrality change by applying commuting traffic O-D data to Social Network Analysis techniques. The analysis showed that urban imbalance was growing, and the centrality of transportation was changing. The results of the analysis of spatial structure elements could be interpreted by linking the results of each factor to each neighborhood unit, predicting changes in urban spatial structure and suggesting directions for sustainable urban growth management.These results could also be used as a decision-making tool for various urban growth management policies introduced to cope with rapid urban development and uncontrollable development in many cities around the world.

Identifying Urban Spatial Structure through GIS and Remote Sensing Data -The Case of Daegu Metropolitan Area- (지리정보시스템과 원격탐사자료를 이용한 도시공간구조의 파악 -대구광역권 사례연구-)

  • Kim, Jae-Ik;Kwon, Jin-Hwi
    • Journal of the Korean Association of Geographic Information Studies
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    • v.12 no.2
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    • pp.44-51
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    • 2009
  • The main purpose of this study is to identify urban spatial structure by applying geographic information system and remote sensing data. This study identifies the urban spatial structure of non-megalopolis by analyzing the spatial distribution of population and employment in the case of Daegu metropolitan area. For this purpose, multi-temporal satellite image data (Landsat TM; 1995, 2000 and 2005) were utilized through the geographic information system. The distance-decay estimations in terms of population and employment density show that Daegu region as a whole shows monocentric urban characteristics. However, some evidences of polycentricism such as low explanation power of monocentric urban model, rises in multiple employment centers, decentralization of employment are emerging.

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A study on the Spatial Sampling Method to Minimize Spatial Autocorrelation of Spatial and Geographical Data (공간·지리적 자료의 공간자기상관성을 최소화하는 공간샘플링 기법에 관한 연구)

  • Lee, Youn Soo;Lee, Man Choul;Lah, Kyung Beom;Kang, Jun Mo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.4
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    • pp.1317-1325
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    • 2014
  • The study focused on analyzing spatial sampling by minimizing autocorrelation of spatial based on spatial and geographical data. The study concluded two different ways of minimizing autocorrelation. First, it was important to use suitable spatial sampling method to alienate spatial autocorrelation from spatial or geographical data. The shear distribution rate of public transportation in Seoul resulted in high rate of autocorrelation. However, the study showed samples eliminated autocorrelation when samples were extracted with reasonable distance(above 400m) apart. Without spatial sampling the distortion of spatial data leads to false results; therefore, spatial sampling is indispensable. Second, factors which fluctuates shear distribution of public transportation spatial sampling changed before and after spatial sampling. This was caused by incapable of controling inherent spatial autocorrelation of the data.

Spatial Database Modeling based on Constraint (제약 기반의 공간 데이터베이스 모델링)

  • Woo, Sung-Koo;Ryu, Keun-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.12 no.1
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    • pp.81-95
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    • 2009
  • The CDB(Constraint Database) model is a new paradigm for massive spatial data processing such as GIS(Geographic Information System). This paper will identify the limitation of the schema structure and query processing through prior spatial database research and suggest more efficient processing mechanism of constraint data model. We presented constraint model concept, presentation method, and the examples of query processing. Especially, we represented TIN (Triangulated Irregular Network) as a constraint data model which displays the height on a plane data and compared it with prior spatial data model. Finally, we identified that we were able to formalize spatial data in a simple and refined way through constraint data modeling.

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Design & Performance Evaluation of Storage and Index Structures for Spatial Network Databases (공간 네트워크 데이터베이스를 위한 저장 및 색인 구조의 설계 및 성능평가)

  • Um Jung-Ho;Chang Jae-Woo
    • The KIPS Transactions:PartD
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    • v.13D no.3 s.106
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    • pp.325-336
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    • 2006
  • For supporting LBS service, recent studies on spatial network databases (SNDB) have been done actively. In order to gain good performance on query processing in SNDB, we, in this paper. design efficient storage and index structures for spatial network data, point of interests (POIs), and moving objects on spatial networks. First, we design a spatial network file organization for maintaining the spatial network data itself consisting of both node and edges. Secondly, we design a POI storage and index structure which is used for gaining fast accesses to POIs, like restaurant, hotel, and gas station. Thirdly, we design a signature-based storage and index structure for efficiently maintaining past, current, and expected future trajectory information of moving objects. Finally, we show that the storage and index structures designed in this paper outperform the existing storage structures for spatial networks as well as the conventional trajectory index structures for moving objects.