• 한국지구과학회지
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• 제25권1호
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• pp.10-21
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• 2004

Recently, spatial data integration for geoscientific application has been regarded as an important task of various geoscientific applications of GIS. Although much research has been reported in the literature, quantitative assessment of the spatial interrelationship between input data layers and an integrated layer has not been considered fully and is in the development stage. Regarding this matter, we propose here, methodologies that account for the spatial interrelationship and spatial patterns in the spatial integration task, namely a multi-buffer zone analysis and a statistical analysis based on a contingency table. The main part of our work, the multi-buffer zone analysis, was addressed and applied to reveal the spatial pattern around geological source primitives and statistical analysis was performed to extract information for the assessment of an integrated layer. Mineral potential mapping using multi-source geoscience data sets from Ogdong in Korea was applied to illustrate application of this methodology.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.622-625
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• 2004

This paper presents multi-source spatial data integration models based on probability theory for landslide hazard assessment. Four probabilistic models such as empirical likelihood ratio estimation, logistic regression, generalized additive and predictive discriminant models are proposed and applied. The models proposed here are theoretically based on statistical relationships between landslide occurrences and input spatial data sets. Those models especially have the advantage of direct use of continuous data without any information loss. A case study from the Gangneung area, Korea was carried out to quantitatively assess those four models and to discuss operational issues.

• 대한원격탐사학회지
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• 제21권5호
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• pp.393-404
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• 2005

As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.

• Spatial Information Research
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• 제12권3호
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• pp.239-249
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• 2004

다중축척 데이터베이스는 동일한 공간을 다른 축척으로 표현하는 공간데이터베이스의 집합이다. 이 다중축척 데이터베이스는 소축척의 정밀한 공간데이터베이스로부터 유도될 수 있다. 본 논문은 유도된 다중축척 데이터베이스의 갱신문제를 다루고자 한다. 다중축척 데이터베이스의 갱신은 수정된 원시데이터로부터 직접 유도된 데이터뿐만 아니라 갱신되지 않은 원시데이터로부터 유도된 데이터들까지 갱신해야 한다. 이것은 현재 데이터 갱신방법들을 다중축척 데이터베이스에 그대로 적용할 수 없는 이유가 되는데, 현재 방법들은 수정된 원시데이터로부터 직접 유도된 데이터만을 갱신하기 때문이다. 이 다중축척 데이터베이스의 갱신관리는 공간 데이터베이스 관리시스템(혹은 GIS)에서 제공되어야 할 중요한 기능이다. 이 논문에서는 다중축척 데이터 베이스 갱신을 위한 규칙 및 알고리즘을 제안하고, 이것을 ESRI의 ArcObject를 이용하여 개발한 프로토타입을 소개한다. 본 연구에서 제공하는 갱신방법은 다중축척 데이터베이스들간의 일관성을 유지시켜주고, 유도된 다중축척 데이터베이스의 무결성을 보장해 줄 수 있다는 점에서 의의가 있다.

• 한국산학기술학회논문지
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• 제16권12호
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• pp.8370-8377
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• 2015

공간 데이터 스트림 관리 시스템에 실시간으로 입력되는 공간 데이터 스트림은 제한된 주기억장치의 용량을 초과할 수 있으므로 부하를 제한할 필요가 있다. 그러나 기존의 연구에서는 부하 제한을 위해 공간 데이터 스트림을 생성하는 데이터 소스의 특성이나 입력 변화, 그리고 공간 데이터 이용 정도를 효율적으로 적용하지 못함으로써 질의 처리의 정확도와 성능을 감소시키는 문제를 갖고 있다. 이에 본 연구에서는 공간 데이터 스트림 질의 관리 시스템에서 발생할 수 있는 부하를 제한하고 공간 질의 처리의 성능과 정확도를 높이기 위한 다단계 부하제한 기법을 제안한다. 제안 기법에서는 먼저 데이터를 수집하는 단계에서 데이터의 수량과 입력 빈도 변화를 이용하여 부하를 제한하고, 과부하 발생시 공간 이용도에 따라 질의 참여 확률이 낮은 데이터를 대상으로 추가적인 부하제한을 수행한다. 실험 결과에서 제안 기법은 기존 부하제한 기법에 비해 11% 이상의 부하 제한 발생 빈도를 감소시키면서 입력 데이터 스트림의 증가와 질의 영역에 증가에 따른 질의 처리 결과의 정확도는 0.04% 이상의 우위를 보였다. 또한, 질의 처리 성능에서도 기존 기법에 비해 3% 이상의 향상을 나타냈다.

• 한국지구과학회지
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• 제26권2호
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• pp.114-128
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• 2005

Fuzzy information representation of multi-source spatial data is applied to landslide hazard mapping. Information representation based on frequency ratio and non-parametric density estimation is used to construct fuzzy membership functions. Of particular interest is the representation of continuous data for preventing loss of information. The non-parametric density estimation method applied here is a Parzen window estimation that can directly use continuous data without any categorization procedure. The effect of the new continuous data representation method on the final integrated result is evaluated by a validation procedure. To illustrate the proposed scheme, a case study from Jangheung, Korea for landslide hazard mapping is presented. Analysis of the results indicates that the proposed methodology considerably improves prediction capabilities, as compared with the case in traditional continuous data representation.

• 한국측량학회지
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• 제34권2호
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• pp.207-215
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• 2016

The demand for spatial data service technologies is increasing lately with the development of realistic 3D spatial information services and ICT (Information and Communication Technology). Research is being conducted on the real-time provision of spatial data services through a variety of mobile and Web-based contents. Big data or cloud computing can be presented as alternatives to the construction of spatial data for the effective use of large volumes of data. In this paper, the process of building HLM (Hyper Live Map) using multi-source data to acquire stereo CCTV and other various data is presented and a big data service architecture design is proposed for the use of flexible and scalable cloud computing to handle big data created by users through such media as social network services and black boxes. The provision of spatial data services in real time using big data and cloud computing will enable us to implement navigation systems, vehicle augmented reality, real-time 3D spatial information, and single picture based positioning above the single GPS level using low-cost image-based position recognition technology in the future. Furthermore, Big Data and Cloud Computing are also used for data collection and provision in U-City and Smart-City environment as well, and the big data service architecture will provide users with information in real time.

• 정보처리학회논문지D
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• 제12D권6호
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• pp.837-848
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• 2005

다중축척 공간데이터베이스란 동일한 현실 공간을 여러 축척으로 저장한 것으로, 기존에 구축된 원시 공간 데이터베이스로부터 유도될 수 있다. 이 유도과정에서 원시 데이터베이스에 있던 기하 및 위상관계는 변형이 되고, 이 관계 변형은 유도된 데이터베이스의 무결성을 보장하지 못하는 원인이 되므로, 유도과정이 수행된 후에는 반드시 유도된 데이터베이스와 원시 데이터베이스의 관계 일관성을 조사해야한다. 이 논문에서는 원시 데이터베이스와 유도된 다중축척 데이터베이스간의 위상 관계 일관성을 평가하는 방법을 제시하겠다. 특히, 2차원 공간객체가 1차원으로 축소되었을 때 위상관계의 일관성을 평가하는 방법을 제한할 것이며, 이 평가 방법들의 구현에 대해서 기술하고, 사례를 이용하여 구현결과를 기술하겠다.

• 한국지구과학회:학술대회논문집
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• 한국지구과학회 2003년도 추계학술발표회 및 정기총회
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• pp.144-148
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• 2003

• Asian Journal of Atmospheric Environment
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• 제2권1호
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• pp.34-46
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• 2008

Emissions inputs for use in air quality modeling of Korea were generated with the emissions inventory data from the National Institute of Environmental Research (NIER), maintained under the Clean Air Policy Support System (CAPSS) database. Source Classification Codes (SCC) in the Korea emissions inventory were adapted to use with the U.S. EPA's Sparse Matrix Operator Kernel Emissions (SMOKE) by finding the best-matching SMOKE default SCCs for the chemical speciation and temporal allocation. A set of 19 surrogate spatial allocation factors for South Korea were developed utilizing the Multi-scale Integrated Modeling System (MIMS) Spatial Allocator and Korean GIS databases. The mobile and area source emissions data, after temporal allocation, show typical sinusoidal diurnal variations with high peaks during daytime, while point source emissions show weak diurnal variations. The model-ready emissions are speciated for the carbon bond version 4 (CB-4) chemical mechanism. Volatile organic carbon (VOC) emissions from painting related industries in area source category significantly contribute to TOL (Toluene) and XYL (Xylene) emissions. ETH (Ethylene) emissions are largely contributed from point industrial incineration facilities and various mobile sources. On the other hand, a large portion of OLE (Olefin) emissions are speciated from mobile sources in addition to those contributed by the polypropylene industry in point source. It was found that FORM (Formaldehyde) is mostly emitted from petroleum industry and heavy duty diesel vehicles. Chemical speciation of PM2.5 emissions shows that PEC (primary fine elemental carbon) and POA (primary fine organic aerosol) are the most abundant species from diesel and gasoline vehicles. To reduce uncertainties in processing the Korea emission inventory due to the mapping of Korean SCCs to those of U.S., it would be practical to develop and use domestic source profiles for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources when VOC emissions from the sources are more than 90% of the total.