• Communications for Statistical Applications and Methods
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• 제12권1호
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• pp.241-252
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• 2005

In this study we suggest that the spatial correlation structure of the brain fMRI data be used to characterize the functional connectivity of the brain. For some concussion and recovery data, we examine how the correlation structure changes from one step to another in the data analyses, which will allow us to see the effect of each analysis to the spatial correlation or the functional connectivity of the brain. This will lead us to spot the processes which cause significant changes in the spatial correlation structure of the brain. We discuss whether or not we can decompose correlation matrices in terms of its causes of variations in the data.

• 농촌계획
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• 제23권2호
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• pp.43-54
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• 2017

When an age of low growth and population decline, population migration plays an important role in spatial structure of region. There have been many researches on migration and regional spatial structure. The purpose of this study is to examine the changes of Gwangju and Jeonnam region's spatial structure and central area using social network analysis methods. For analysis it was used that population and migration data and passenger OD(Origin and Destination) travel data released by Statistics Korea and Korea Transport Database(KTDB). Using Gephi 0.8.2, migration and passenger OD networks were visualized, and this describe network flow and density. The results of the network centrality analysis show that the most populated village is not always network center though population mass is an important factor of central places. The average eigenvector centrality of 2010 migration is the lowest during 2005-2015, and it means few regions have high centralities. When comparing migration and travel networks, travel data is more effective than migration data in determining the central location considering spatial functions.

• Spatial Information Research
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• 제17권3호
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• pp.277-285
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• 2009

효율적으로 데이터를 관리, 분석, 유지하기 위해서는 각 시스템의 목적에 맞는 데이터 모델이 필요하다. 데이터 모델에 따라 해당하는 활용 시스템의 활용 범위가 결정되며, 각각의 활용 시스템에 맞는 데이터 모델이 개발되고 있는 상황이다. GIS 분야에서도 각 GIS 응용시스템에 맞는 다양한 공간정보 데이터 모델들이 개발 되었으며, 제공하고자 하는 서비스에 따라 공간정보 데이터 모델이 만들어지고 있다. 어플리케이션의 효율적인 활용을 위해서는 공간정보 데이터의 정확성과 최신성등이 중요하지만 특히 공간정보 데이터 구조를 만드는 데이터 모델링이 중요하다. 그러므로 본 연구는 1)국내외 공간정보 데이터 모델의 공간정보를 표현하는데 있어 기하학적 모델, 위상학적 모델과 3차원 공간정보 가시화 방법 등의 항목별로 비교하고 2)각각의 데이터 구조를 분석하여 데이터 모델의 특징을 비교한다. 마지막으로 3)공간정보 데이터 모델을 선정하여 정량적인 분석을 통해 데이터 구조에 따른 특징을 분석한다.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1181-1190
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• 2006

Statistical analyses for spatial data are important features for various types of fields. Spatial data are taken at specific locations or within specific regions and their relative positions are recorded. Lattice data are synoptic observation covering an entire spatial region, like cancer rates corresponding to each county in a state. Until now, the echelon analysis has been applied only to univariate spatial data. As a result, it is impossible to detect the hotspots on the multivariate spatial data In this paper, we expand the spatial data to time series structure. And then we analyze them on the time space and detect the hotspots. Echelon dendrogram has been made by piling up each multivariate spatial data to bring time spatial data. We perform the structural analysis of temporal spatial data.

• Spatial Information Research
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• 제19권4호
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• pp.45-54
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• 2011

본 논문에서는 기존에 제시된 MR-tree와 SQR-tree의 장점을 결합하여 대용량 공간 데이타를 보다 효율적으로 처리할 수 있는 하이브리드 인덱스 구조인 SQMR-tree(Spatial Quad MR-tree)를 제시한다. MR-tree는 R-tree에 R-tree 리프 노드를 직접 접근해주는 매핑 트리를 적용한 인덱스 구조이고, SQR-tree는 SQ-tree (Spatial Quad-tree)와 SQ-tree의 리프 노드마다 실제로 공간 객체를 저장하는 R-tree가 결합된 인덱스 구조이다. SQMR-tree는 SQR-tree를 기본 구조로 SQR-Tree의 R-tree 마다 매핑 트리가 적용된 형태를 가진다. 따라서, SQMR-tree는 SQR-tree와 같이 공간 객체가 여러 R-tree에 분산 저장되며 질의 영역에 해당하는 R-tree만 접근하면 되기 때문에 공간 질의 처리 비용을 줄일 수 있다. 또한, SQMR-tree는 MR-tree와 같이 매핑 트리를 통해 트리 검색 없이 R-tree 리프 노드의 빠른 접근이 가능하기 때문에 검색 성능을 향상시킬 수 있다. 마지막으로 실험을 통해 SQMR-tree의 우수성을 입증하였다.

• 한국공간정보시스템학회 논문지
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• 제12권1호
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• pp.49-56
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• 2010

공간 및 비 공간 데이터에서 알지 못했던 패턴을 탐사하는 빈발 패턴 탐사 기법은 마이닝 분야에서 가장 핵심적인 부분으로 많은 연구가 활발히 진행되고 있다. 기존의 자료구조들은 트리 구조 및 배열 구조로써 밀집 또는 희소 빈발 패턴에서 성능 저하를 보인다. 대용량의 공간 데이터는 밀집 및 희소 빈발 패턴을 둘 다 가지므로 단일 알고리즘으로 빠르게 탐사 하는 것은 중요하다. 본 논문에서는 단일 알고리즘을 사용하면서도 밀집 및 희소 빈발 패턴 모두에 대해 빠르게 빈발 패턴을 마이닝할 수 있는 압축된 패트리샤 빈발 패턴 트리라는 새로운 자료구조와 이를 사용한 빈발 패턴 마이닝 알고리즘을 제안한다. 실험 평가는 제안한 알고리즘이 대용량 희소 및 밀집 빈발 데이터에서 기존의 FP-Growth 알고리즘 보다 약 10배 정도 빠르게 빈발 패턴을 탐사하는 것을 보인다.

• 한국실내디자인학회논문집
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• 제26권1호
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• pp.83-90
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• 2017

The purpose of this study is to investigate the possibilities of architectural planning and expression of the relationship between structure and skin in contemporary architecture. For this purpose, we show interior space images -integration of structure and skin architecture- to students and experts of the related majors, and let them mark their feeling on the questionnaire composed spatial expression vocabulary extracted through the literature study on spatial sensibility, and analysis data. As a result, in contemporary architecture where the structure and the skin are integrated, form elements have a stronger influence on formation of space sense than elements of light and size, and aesthetics, characteristic, and temporality are common in the inner space, Three types of four types showed unique characteristics, and it was confirmed that there is a causal relationship between the spatial feeling factor and the spatial feeling. This means that the relationship between the structure and the skin can be considered as a planning factor, and this study is expected to be used as such basic data.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2000년도 가을 학술발표논문집 Vol.27 No.2 (1)
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• pp.113-115
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• 2000

A GIS software GEO Millennium SystemTM has been developed to integrated with spatial database that combines conventional and spatially related data. As we known well the standard query language lacks the support of spatial data type and predicate, and can not serve as the query language in the spatial database directly; some extended strategies have been proposed, but some of them need their own storage manager, some introfuce new clause into the SELECT-FROM-WHERE structure, and some is very complex and available to us. So we designed our own query language on the conventional storage manager system. It supports the Spatial Data Type and predicate, and provides the full query capabilities of SQL on the non-spatial part of the database while being tightly integrated with the spatial part, without changing the standard SQL structure.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.150-152
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• 2003

Laser scanned lidar data record 3D surface information in detail. Exploring valuable spatial information from lidar data is a prerequisite task for its applications, such as DEM generation and 3D building model reconstruction. However, the inherent spatial information is implicit in the abundant, densely and randomly distributed point cloud. This paper proposes a novel method to organize point cloud data, so that further analysis or feature extraction can proceed based on a well organized data model. The principle of the proposed algorithm is to segment point cloud into 3D planes. A split and merge segmentation based on the octree structure is developed for the implementation. Some practical airborne and ground lidar data are tested for demonstration and discussion. We expect this data organization could provide a stepping stone for extracting spatial information from lidar data.

• Journal of the Korean Data and Information Science Society
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• 제15권1호
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• pp.83-94
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• 2004

In this study we analyze categorical data by means of spatial statistics and echelon analysis. To do this, we first determine the hierarchical structure of a given contingency table by using echelon dendrogram then, we detect candidates of hotspots given as the top echelon in the dendrogram. Next, we evaluate spatial scan statistics for the zones of significantly high or low rates based on the likelihood ratio. Finally, we detect hotspots of any size and shape based on spatial scan statistics.