• Spatial Information Research
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• v.20 no.6
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• pp.69-76
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• 2012

In this study, we derived the characteristics of the geo-spatial information industry by using input-output analysis. For this analysis, we classified the geo-spatial information industry and reorganized the input-output table. And we derived the production inducement coefficient, index of the power of dispersion and index of the sensitivity of dispersion in the geo-spatial information industry. We confirmed that geo-spatial information industry has a small production inducement coefficient and a great forward linkage effect. Based on these facts, we suggested the strategy direction as follows: 1) building the industrial eco-system, 2) managing both advance and applicability enhancement, 3) Establishing from a long-term point of view.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.1
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• pp.1-10
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• 2000

Spatial analysis in GIS provides an important way that helps the end-users decision-making. For such a reason, query model for analysis should be able to support the users view conceptually in constructing query statements. The traditional approaches in design of query model used to extend the functionality of model that basically designed for manipulation of attribute-operations by appending operators for spatial operations to the query statements of model. However, by the reason of spatial operation's characteristics that are different from those of attribute operations In nature, the structures of query statements in previous approaches are unnatural, inconsistent, and therefore those query models in previous approaches are not able to support the users view in retrieving analysis. In this paper, we proposed the methodology for constructing of user query and internal processing this query based on object-oriented paradigm, in the view of spatial operations by using the basic concept that spatial query is a methodology for spatial analysis. In addition, we presented a strong possibility of designing spatial query model that might actively have interaction with its user by implementing CIW(Class-Information Window) query interface corresponded with the methodology proposed in this paper.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1474-1474
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• 2003

• Journal of architectural history
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• v.21 no.6
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• pp.19-34
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• 2012

This paper focuses on the spatial analysis of traditional houses in Huizhou during the Ming and Qing period in China. It first reviews the spatial characteristics of the houses in Huizhou. Typical configurations, spatial elements and spatial compositions of the houses are briefly examined. It then discusses how those spatial characteristics are applied to the houses. To do so, the review of existing research and literature on the houses was conducted. For a detailed analysis of the houses, a field survey was performed to collect research materials of the houses and to assess the application of the characteristics in the houses. At times, the plans of the houses were redrawn for a further analysis of the spatial compositions of the houses. Attempts have been made to understand the underlying principles of their spatial organization. For example, Jin (2010) examined the spatial organization of unit plans. Boyd (1989), Berliner (2003) and Dan (2005) similarly categorized the organizational typology of its varying designs. Son(1995) further interpreted the spatial relations of the variety of houses in a comprehensive manner. Nevertheless, their analytic methodology falls short of a complete explanation of the spatial expansion and transformation in the houses. Therefore, this paper examines the basic principles behind the spatial expansion and transformation of a variety of traditional houses in Huizhou. In doing so, it strives to make logical sense of design variations in the houses and reveal the theory behind them.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.67-87
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• 2021

Public library accessibility directly affects library usage, and the disproportionate distribution of accessibility is a decisive factor limiting the equitable provision of library services. In this regard, this study analyzed the spatial accessibility of public libraries in Busan and identified the factors affecting accessibility of public libraries using spatial regression analysis. As a results of the analysis, the accessibility of public libraries in the Busan showed large deviations by region. Also, spatial distribution of public libraries had no correlation with the settled population and use of public transportation, and location of public libraries was inefficient, in terms of social equity. The results of this study will assist to understand the spatial accessibility of public libraries in Busan, to identify factors that affect the accessibility. Moreover, this study is expected to be utilized as fundamental data for releasing disparities of the spatial accessibility and selecting new location of public library in Busan.

• The Journal of Bigdata
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• v.4 no.1
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• pp.83-97
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• 2019

With sensor and communication technology development, spatial data related to business activities is exploding. Spatial data is now evolving into atypical data about space over three dimensions, away from two-dimensional geographic data. In addition to the Fourth Industrial Revolution, which connects the virtual space with the real space, there is a great opportunity for companies to utilize it. The analysis of recent overseas cases shows that it is possible to analyze customized services by understanding the situation of customers and objects located in the space, to manage risk, and furthermore to innovate business processes by analyzing spatial data. In the future, business innovation that combines spatial data from various sources and real-time analysis of relationships and situations between people and objects in space is expected to expand in all business fields.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.3
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• pp.55-63
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• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.

• Spatial Information Research
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• v.20 no.1
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• pp.81-90
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• 2012

When analyzing geographical phenomena, two properties need to be considered. One is the spatial dependence structure and the other is a variation or an uncertainty inhibited in a geographic space. Two problems are encountered due to the properties. Firstly, spatial dependence structure, which is conceptualized as spatial autocorrelation, generates heterogeneous geographic landscape in a spatial process. Secondly, generic statistics, although suitable for dealing with stochastic uncertainty, tacitly ignores location information im plicit in spatial data. GIS is a versatile tool for manipulating locational information, while spatial statistics are suitable for investigating spatial uncertainty. Therefore, integrating spatial statistics to GIS is considered as a plausible strategy for appropriately understanding geographic phenomena of interest. Geographic hot-spot analysis is a key tool for identifying abnormal locations in many domains (e.g., criminology, epidemiology, etc.) and is one of the most prominent applications by utilizing the integration strategy. The article aims at reviewing spatial statistical perspective for analyzing spatial processes in the framework of GIS by carrying out empirical analysis. Illustrated is the analysis procedure of using spatial scan statistic for detecting clusters in the framework of GIS. The empirical analysis targets for identifying spatial clusters of breast cancer incidents in Erie and Niagara counties, New York.

• Spatial Information Research
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• v.13 no.3 s.34
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• pp.253-260
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• 2005

The aim of this study is to analyze the temporal and spatial distribution aspects of red tide using GIS techniques. The damage caused by red tide appears various aspects according to the species, concentration and spatial distribution of red tide plankton. Therefore, in order to prevent the damage of red tide it is important to understand the distribution characteristics of red tide by each species according to time and space. In this perspective, we analyzed the beginning outbreak area, spatial occurrence frequency and spatial migration of red tide. The spatial data used by this study was constructed by digitizing the red tide quick report and coupled with various attributes such as species, concentration and water temperature for construction of red tide database. We used various spatial analysis methods such as union, intersect, tracking, buffer and spatial interpolation for analyzing temporal and spatial characteristics of red tide. From the result of these spatial analyses, we could get the spatial information on the temporal and spatial distribution characteristics of red tide at the Southern Sea.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.194-197
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• 1999

In AVL, GIS analyze the information from the vehicles to provide commercial or other value far user. As spatial analysis functions in GIS make a new valuable information using the vehicle's position and geographic object's location, they perform an important roles to improve the management efficiency of vehicles. Most GIS however are used static data for the spatial analysis, so the research area on AVL used dynamic vehicle location has generated unsuitable result. In this study, we use GPS real time tracking data to perform spatial analysis between moving vehicle and static geographic object. The method proposed in this paper considers the driving direction of vehicle and creates the result which is located in forward of vehicle. In this paper, two spatial analysis functions, near and connectivity, are developed.