• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.82-98
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• 2021

In recent years, as the number of ground subsidence has increased nationwide, the latest and usefulness of underground information for underground space development and underground safety management has become more important than ever. However, the 3D Underground Geospatial Map project, which started in 2015, has a problem with the manual-based long-term update system. This research paper overcomes these limitations and automatically updates the 3D CAD/GIS-based integrated management of underground structures that can be managed automatically from a full-cycle perspective of underground structure data management such as processing, transformation, updating, management, and visualization of 2D/3D underground structure data. If this technology is applied, it is possible to integrate processing and update management of the existing complex 3D construction logic of underground structures in one system, and it is expected that it can be used for underground space development and underground safety management as a foundation technology for automatic update of underground structures data.

• Annual Conference of KIPS
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• 2007.05a
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• pp.1508-1511
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• 2007

부동산문제등과 관련하여 지적(地籍) 및 용도지역지구 자료의 중요성이 부각되면서, 복잡한 법적 절차를 갖춘 시스템이 구축되고 있다. 그 중 한국토지정보시스템(KLIS)은 각 지자체별 지적 및 도시계획 관련 데이터 구축, 업무시스템 및 건축 인허가등의 민원발급, 부동산 관련 다양한 통계 등을 제공하고 있다. 그러나, 이 시스템이 설치되어 있는 시군구 중 일반구(區)를 포함한 시(市)의 경우는 법적인 편집 권한이 다른 기관에서 공통 데이터베이스의 편집에 따른 데이터 무결성 문제와 네트워크 장애에 따른 업무 지연 등의 업무 연속성 문제를 야기할 수 있다. 본 논문에서는 일반구가 포함된 시(市)에서의 지적도편집, 용도지역지구도 편집 등 이종의 기관에서 이루어지는 분산 환경 데이터베이스편집에 따른 동기화의 문제점을 제기하고, 이러한 문제점을 보완할 수 있도록 트랜잭션 단위로 공간 및 속성 데이터의 복제를 담당하는 Replicator를 이용한 분산 데이터베이스 동기화 아키텍처를 제안하고, 동기화부분과 표준화부분, 트랜잭션관리부분으로 구성되어 있는 Replicator의 구성요소를 설계 및 구현하고 Replicator를 이용한 분산 데이터베이스의 변경부분을 미반영 데이터베이스에 반영하는 처리절차와 처리 후 결과를 제시하여, 지적 및 용도지역관련 데이터를 두 개 이상의 기관에서 동시에 편집한 내용이 실시간으로 두 기관의 분산 데이터베이스에 변경 분이 반영되어 모두 동기화 되어 있는 것을 공간데이터 편집기로 확인해 볼 수 있었다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.1
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• pp.115-123
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• 2005

Quantitative understanding of spatial characteristics of the study site is a prerequisite to investigate water and carbon cycles in agricultural and forest ecosystems, particularly with complex, heterogeneous landscapes. The spatial characteristics of variables related with topography, vegetation and soil in Gwangneung forest watershed are quantified in this study. To characterize topography, information on elevation, slope and aspect extracted from DEM is analyzed. For vegetation and soil, a land-cover map classified from LANDSAT TM images is used. Four satellite images are selected to represent different seasons (30 June 1999, 4 September 2000, 23 September 2001 and 14 February 2002). As a flux index for CO₂ and water vapor, normalized difference vegetation index (NDVI) is calculated from satellite images for three different grid sizes: MODIS grid (7km x 7km), intensive observation grid (3km x 3km), and unit grid (1km x 1km). Then, these data are analyzed to quantify the spatial scale of heterogeneity based on semivariogram analysis. As expected, the scale of heterogeneity decreases as the grid size decreases and are sensitive to seasonal changes in vegetation. For the two unit grids where the two 40 m flux towers are located, the spatial scale of heterogeneity ranges from 200 to 1,000m, which correspond well to the climatology of the computed tower flux footprint.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.10a
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• pp.106-112
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• 2008

Personalization is user oriented dynamic method based on user preferences for easy access to what users want to view or get. It has become more important in mobile domain with rapid growth of wireless Internet and mobile phone market after success of web based market and therefore, it can be applied to service of spatial analysis result. In this paper, spatial analysis using user profile and notification service methods are proposed as one of personalized spatial data service methods for mobile users. A service system for spatial analysis with user profile is designed to prove possibility of spatial analysis based on user preferences and notification service is also designedto show generated output can be sent to user's mobile devices efficiently to make users informed of preferred information. Prototype system is implemented and it is applied to real estate data that has many selectable conditions by users. Information service based on user preferences can be applied to spatial data by using proposed system and it is efficient when cache module is used to shorten response time. Various user models for application domains and performance evaluation methods need to be developed in the future.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.63-79
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• 2008

With the recent development of advanced GIS and complex spatial analysis technologies, the more sophisticated technologies are being required to support the advanced knowledge for solving geographical or spatial problems in various decision support systems. In addition, necessity for research on scientific crime investigation and forensic science is increasing particularly at law enforcement agencies and investigation institutions for efficient investigation and the prevention of crimes. There are active researches on geographic profiling to predict the base location such as criminals' residence by analyzing the spatial patterns of serial crimes. However, as previous researches on geographic profiling use simply statistical methods for spatial pattern analysis and do not apply a variety of spatial and temporal analysis technologies on serial crimes, they have the low prediction accuracy. Therefore, this paper identifies the typology the spatio-temporal patterns of serial crimes according to spatial distribution of crime sites and temporal distribution on occurrence of crimes and proposes STA-BLP(Spatio-Temporal Analysis based Base Location Prediction) algorithm which predicts the base location of serial crimes more accurately based on the patterns. STA-BLP improves the prediction accuracy by considering of the anisotropic pattern of serial crimes committed by criminals who prefer specific directions on a crime trip and the learning effect of criminals through repeated movement along the same route. In addition, it can predict base location more accurately in the serial crimes from multiple bases with the local prediction for some crime sites included in a cluster and the global prediction for all crime sites. Through a variety of experiments, we proved the superiority of the STA-BLP by comparing it with previous algorithms in terms of prediction accuracy.

• Journal of the Korean Geographical Society
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• v.39 no.5 s.104
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• pp.804-818
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• 2004

As spatial data resources become more abundant, the potential for conflict among them increases. Those conflicts can exist between two or many spatial datasets covering the same area and categories. Therefore, it becomes increasingly important to be able to effectively relate these spatial data sources with others then create new spatial datasets with matching geometry and topology. One extensive spatial dataset is US Census Bureau's TIGER file, which includes census tracts, block groups, and blocks. At present, however, census maps often carry information that conflicts with municipally-maintained detailed spatial information. Therefore, in order to fully utilize census maps and their valuable demographic and economic information, the locational information of the census maps must be reconciled with the more accurate municipally-maintained reference maps and imagery. This paper formulates a conceptual framework and two map models of map conflation to make geometrically and topologically consistent source maps according to the reference maps. The first model is based on the cell model of map in which a map is a cell complex consisting of 0-cells, 1-cells, and 2-cells. The second map model is based on a different set of primitive objects that remain homeomorphic even after map generalization. A new hierarchical based map conflation is also presented to be incorporated with physical, logical, and mathematical boundary and to reduce the complexity and computational load. Map conflation principles with iteration are formulated and census maps are used as a conflation example. They consist of attribute embedding, find meaning node, cartographic 0-cell match, cartographic 1-cell match, and map transformation.

• Spatial Information Research
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• v.23 no.2
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• pp.1-9
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• 2015

Graphical processing unit (GPU) contains many arithmetic logic units (ALUs). Because many ALUs can be exploited to process parallel processing, GPU provides efficient data processing. The spatial data require many geographic coordinates to represent the shape of them in a map. The coordinates are usually stored as geodetic longitude and latitude. To display a map in 2-dimensional Cartesian coordinate system, the geodetic longitude and latitude should be converted to the Universal Transverse Mercator (UTM) coordinate system. The conversion to the other coordinate system and the rendering process to represent the converted coordinates to screen use complex floating-point computations. In this paper, we propose a parallel processing technique that processes the conversion and the rendering using the GPU to improve the performance. Large spatial data is stored in the disk on files. To process the large amount of spatial data efficiently, we propose a technique that merges the spatial data files to a large file and access the file with the method of memory mapped file. We implement the proposed technique and perform the experiment with the 747,302,971 points of the TIGER/Line spatial data. The result of the experiment is that the conversion time for the coordinate systems with the GPU is 30.16 times faster than the CPU only method and the rendering time is 80.40 times faster than the CPU.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.235-252
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• 2008

Many cartographers have for many years searched for a way to construct cartograms in which the sizes of geographic areas such as states, counties or census tracts are reseated in proportion to their population or some other socio-economic properties. While many techniques and algorithms for creating cartograms have been proposed, some of them are still extremely complex to generate in a proper manner, and many of them suffer either from this lack of readability or from seamless integration with GIS software. This paper, therefore, presents a simple population cartogam technique based on the Circular Cartogram Algorithm(CCA) by Dorling(1996) to tackle these drawbacks by drawing the areas as simple circles for use as a base map and linking the construction with GIS mapping processes. For an automated approach in the cartogram generation, this paper proposes a close coupling method of ArcView GIS 3.3. package in order for users to access to the cartopam algorithm. Then, they will be available through an interface that the ArcView GIS system allows user-written routines to be accessed easily. The CCA and its coupling architecture ensure to improve the potential applicability of the use of cartograms to census mapping at practical levels. As the cartogram examples, cartograms of population and property types in 2005 Korea census data sets are illustrated in the end, by which viewers can easily identify the residential concentration and their relative ratio in Seoul metropolitan area.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.127-136
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• 2009

This paper proposes an on-line mining algorithm of moving trajectory patterns in RFID data streams considering changing characteristics over time and constraints of single-pass data scan. Since RFID, sensor, and mobile network technology have been rapidly developed, many researchers have been recently focused on the study of real-time data gathering from real-world and mining the useful patterns from them. Previous researches for sequential patterns or moving trajectory patterns based on stream data have an extremely time-consum ing problem because of multi-pass database scan and tree traversal, and they also did not consider the time-changing characteristics of stream data. The proposed method preserves the sequential strength of 2-lengths frequent patterns in binary relationship table using the time-evolving graph to exactly reflect changes of RFID data stream from time to time. In addition, in order to solve the problem of the repetitive data scans, the proposed algorithm infers candidate k-lengths moving trajectory patterns beforehand at a time point t, and then extracts the patterns after screening the candidate patterns by only one-pass at a time point t+1. Through the experiment, the proposed method shows the superior performance in respect of time and space complexity than the Apriori-like method according as the reduction ratio of candidate sets is about 7 percent.