• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.45-56
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• 2010

This paper suggests constraint data modeling based on constraint data presentation techniques to perform complex spatial database operation naturally. We were able to identify the limitation of extendibility of dimension and non-equal framework via relevant research for former schema of spatial database and query processing. Therefore we described generalized tuple of spatial data and the definition of suggested constraint data modeling. Also we selected MLPQ/PReSTO tool among constraint database prototype and compare standard functionality of ARC/VIEW. Then we design scenario for spatial operation using MLPQ/PReSTO and we suggested application effect after query processing. Based on above explanation, we were able to identify that we can process spatial data naturally and effectively using simple constraint routine on same framework via constraint data modeling.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.166.2-166.2
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• 2011

Incheon Bay of Korea is one of the most famous regions for high tidal range. Ministry of Land, Transport and Maritime Affairs(MLTM) has implemented preliminary investigation for tidal power energy development in this area since 2006. Through field observations, various kinds of marine data consisting of depth and geography, marine weather, tidal currents, wave, seawater characteristics, geology, marine ecosystem and marine environment were gathered. To use these data efficiently for the determining of feasibility of developing and appropriateness of project scale, spatial data management and application system is essential. Therefore, in this study, the concept, methodology and procedure of spatial data modeling are defined for tidal energy development. Spatial data modeling consists of essential model relating to tidal energy directly and optional model including environmental factors. Essential model is composed with fundamental elements like as depth, geography, and several numerical modeling results(tide, tidal current, wave).

• 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.

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.868-876
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• 2006

2D input data have to be converted into 3D data by means of some functions and menu system in 2D input modeling system. But data in 3D input system for virtual spatial design can be directly connected to the 3D modeling data. Nevertheless, efficient surface modeling and deformation algorithm for the 3D input modeling system are not proposed yet. In this paper, problems of conventional NURBS surface deformation methods which can occur when applied in the 3D input modeling system are introduced. And NURBS surface deformation by 3D target curves, in which the designer can easily approach, are suggested. Designer can efficiently implement the virtual spatial sketching and design by using the proposed deformation algorithm.

• Spatial Information Research
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• v.22 no.6
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• pp.33-43
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• 2014

As the number of people who live indoor space has been increased, the interest in 3D indoor spatial information has been grown. Object-Oriented 3D indoor space modeling including indoor spatial information has performed in level of detail 4, and modeling data is able to be constructed based on various raw data which are as-built drawing, laser scanning, BIM data, and camera. 3D indoor space modeling has been worked based on established indoor space modeling process, and the result can be used for various application fields such as indoor space pedestrian navigation, facility management, disaster management, and so on. However, the modeling process has limitations to perform indoor space modeling efficiently, because the process is complicated and wastes time at modeling work. In this paper, we propose evaluation on practical use of raw data for 3D indoor space modeling purpose on supporting efficient indoor space modeling through analyzing the established process. Therefore, we define the requirements to evaluate the practical use of raw data and propose the verification method. In addition, as-built drawing which has been used in Seoul 3D indoor space modeling project will be applied to proposed method as a raw data.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.139-145
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• 2018

In this paper, we propose the methodology and system to show weather information to spatial system. When using the spatial information system, it is easy and convenient to show information such as target location, mission contents, enemy threats and so on. However, drawing 1-dimensional weather information on 3-dimensional space in spatial information system is hard task. To fuse data, we need to add a spatial layer including weather information to spatial layers and perform space modeling for showing weather information as spatial data in a virtual space. The virtual space is shown by receiving meteorological data and then changing in real time through weather database linkage.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.2
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• pp.61-72
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• 2000

The maturation of the Web technology has reshaped the ways in which data are accessed, disseminated, and shared. Thanks to its popularity along with the advance of spatial information technology, four major changes have been further made in traditional geographic information systems (GIS) in relation to access to data, distribution of data, access to GIS functionality, and visualization of multimedia data. Although access to and dissemination of spatial data over the Web has in recent years been addressed in the literature, little research effort has addressed the issue of access to and processing of GIS analysis functions over the Web. This research explores the potential use of Web-based GIS in improving accessibility to distributed spatial data and spatial modeling tools. A prototype Web-based GIS developed in this study focuses on Web-based location-allocation modeling for spatial decision support, and employs a hybrid approach that uses the Arc/Info software as a GIS server and CGM viewer as a client-side plug-in. This research shows that Web-based GIS is a useful vehicle in conducting spatial modeling in the particular user community. In addition, this study represents the possibility of Web-based GIS in developing open spatial decision supporting systems.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.425-433
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• 2009

Spatial models suitable for describing the evolving random fields in climate and environmental systems have been developed by many researchers. In general, rainfall in South Korea is highly variable in intensity and amount across space. This study characterizes the monthly and regional variation of rainfall fields using the spatial modeling. The main objective of this research is spatial prediction with the Bayesian hierarchical modeling (kriging) in order to further our understanding of water resources over space. We use the Bayesian approach in order to estimate the parameters and produce more reliable prediction. The Bayesian kriging also provides a promising solution for analyzing and predicting rainfall data.

• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.49-77
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• 2007

Role-based access control (RBAC) models are recently receiving considerable attention as a generalized approach to access control. In line with the increase in applications that deal with spatial data. an advanced RBAC model whose entities and constraints depend on the characteristics of spatial data is required. Even if some approaches have been proposed for geographic information systems. most studies focus on the location of users instead of the characteristics of spatial data. In this paper. we extend the traditional RBAC model in order to deal with the characteristics of spatial data and propose new spatial constraints. We use the object-oriented modeling based on open GIS consortium geometric model to formalize spatial objects and spatial relations such as hierarchy relation and topology relation. As a result of the formalization for spatial relations. we present spatial constraints classified according to the characteristics of each relation. We demonstrate our extended-RBAC model called OOGIS-RBAC and spatial constraints through case studies. Finally. we compare our OOGIS-RBAC model and the DAC model in the management of access control to prove the efficiency of our model.

• Journal of Ecology and Environment
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• v.43 no.2
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• pp.191-201
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• 2019

Macroecologists and biogeographers continue to predict the distribution of species across space based on the relationship between biotic processes and environmental variables. This approach uses data related to, for example, species abundance or presence/absence, climate, geomorphology, and soils. Researchers have acknowledged in their statistical analyses the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a degree of dependence between pairs of nearby observations. It has been agreed that residual spatial autocorrelation (rSAC) can have a substantial impact on modeling processes and inferences. However, more attention should be paid to the sources of rSAC and the degree to which rSAC becomes problematic. Here, we review previous studies to identify diverse factors that potentially induce the presence of rSAC in macroecological and biogeographical models. Furthermore, an emphasis is put on the quantification of rSAC by seeking to unveil the magnitude to which the presence of SAC in model residuals becomes detrimental to the modeling process. It turned out that five categories of factors can drive the presence of SAC in model residuals: ecological data and processes, scale and distance, missing variables, sampling design, and assumptions and methodological approaches. Additionally, we noted that more explicit and elaborated discussion of rSAC should be presented in species distribution modeling. Future investigations involving the quantification of rSAC are recommended in order to understand when rSAC can have an adverse effect on the modeling process.