• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.689-698
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• 2009

SOLAP system integrates and complements the functions of both OLAP and GIS systems. This enables users not only to easily access geospatial data but also to analyze and extract information for decision making. In this study a SOLAP system was designed and implemented to provide urban planners with GIS information when making urban planning decisions. Rapid urbanization in Korea has brought about ill-balanced urban structure as the result of development without detailed analysis of urban plans. Systematic urban planning procedures and automated systems are crucial for detail analysis of future development plans. Data regarding the development regulations and current status of land use need to be assessed precisely and instantly. Multi-dimensional aspects of a suggested plan must be formulated instantly and examined thoroughly using 'what if' scenarios to come up with a best possible plan. The SOLAP system presented in this study designed the dimension tables and the fact tables for supplying timely geospatial information to the planners when making decisions regarding urban planning. The database was implemented using open source DBMS and was populated with necessary attribute data which was freely available from the Statistics Korea bureau homepage. It is anticipated the SOLAP system presented in this study will contribute to better urban planning decisions in Korea through more timely and accurate provision of geospatial information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.287-294
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• 2012

The spread of infectious diseases in the event of livestock is getting faster and the route of spread gets more varied. It is important for the responsible agency to detect early and establish a prevention and surveillance system. If the spread cannot be contained effectively, great damage and loss will be inevitable in terms of social, environment and economic aspects as well as the welfare of the farmers. At present in Korea, a web-based Infectious Livestock Diseases Statistics System (AIMS: Animal Infectious Disease Data Management System) has been already implemented for this purpose and the service is available to the general public. But this system does not provide geospatial information and does not provide support for decision making and does not provide multi-dimensional information. In this study, an open source-based SOLAP (Spatial On-Line Analytical Processing) technology is applied to enable many diverse forms of data analysis from many aspects to support decision making. The SOLAP system was designed to integrate geospatial information and the analysis of information has been largely divided into map-based analysis and table-based analysis.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1421-1434
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• 2006

Spatial data warehouses provide analytical information for decision supports using SOLAP (Spatial On-Line Analytical Processing) operations. Many researches have been studied to reduce analysis cost of SOLAP operations using pre-aggregation methods. These methods use the index composed of fixed size nodes for supporting the concept hierarchy. Therefore, these methods have many unused entries in sparse data area. Also, it is impossible to support the concept hierarchy in dense data area. In this paper, we propose a dynamic pre-aggregation index method based on the spatial hierarchy. The proposed method uses the level of the index for supporting the concept hierarchy. In sparse data area, if sibling nodes have a few used entries, those entries are integrated in a node and the parent entries share the node. In dense data area, if a node has many objects, the node is connected with linked list of several nodes and data is stored in linked nodes. Therefore, the proposed method saves the space of unused entries by integrating nodes. Moreover it can support the concept hierarchy because a node is not divided by linked nodes. Experimental result shows that the proposed method saves both space and aggregation search cost with the similar building cost of other methods.

• Journal of Information Technology Applications and Management
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• v.13 no.1
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• pp.137-147
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• 2006

Spatiotemporal data are records of the spatial changes of moving objects over time. Most data in corporate databases have a spatiotemporal nature, but they are typically treated as merely descriptive semantic data without considering their potential visual (or cartographic) representation. Businesses such as geographical CRM, location-based services, and technologies like GPS and RFID depend on the storage and analysis of spatiotemporal data. Effectively handling the data analysis process may be accomplished through spatiotemporal data warehouse and spatial OLAP. This paper proposes a multidimensional model for spatiotemporal data analysis, and cartographically represents the results of the analysis.