• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.39-45
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• 2015

The housing market is transformed by a variety of socio-economic characteristics, also appeared differently according to regional characteristics. This study aims to draw out the change factors influencing on the housing market structure and to analyze the drawn factors' distribution pattern by area. For this purpose, First, targeting 251 areas in the units of city, county and districts nationwide, this study drew out demographic, socio-economic variables influencing on the housing market structure for 5 years ranging 2005 to 2010. For that, the factor analysis was conducted. Second, this study grasped the change factors of the housing market structure's spatial patterns using the kriging method, a spatial statistical method. Third, this study used the Moran I, one of spatial autocorrelation analysis methods in order to grasp whether the factors had statistically significant concentration or dispersion or showed a random distribution pattern.

• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.28-36
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• 2013

Motion-compensated frame interpolation (MCFI) techniques in video signal processing have many application areas. Frame rate up-conversion (FRUC) or distributed video coding (DVC) technique needs an effective MCFI algorithm. For these applications, it is necessary to develop an effective post-processing technique to improve visual qualities or to reduce virtual channel noises, resulting in the reduced channel bit rate. This paper proposes a reliability evaluation method based on spatio-temporal characteristics for motion-compensated interpolated blocks. The proposed algorithm investigates the temporal matching characteristics for current frame and then is designed in such a way that it can measure temporal characteristics as well as the spatial ones. Through computer simulations, it is shown that the proposed method outperforms the conventional temporal matching method.

• Spatial Information Research
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• v.8 no.2
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• pp.213-232
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• 2000

It is important to scrutinize spatial patterns in crime analysis since crime data has geographical attribute in itself. We focus on the development of ¨Crime Analysis GIS¨ prototype which can discover spatial patterns in crime data by integrating mapping functions of GIS and spatial analysis techniques. The structure of this system involves integration of DBMS and GIS, and the major functions of the system include (i) exploring spatial distribution of point data, (ii) mapping hot-spot, (iii) clustering analysis of crime occurrence, and (iv) analyzing aggregated areal data. The process of design and implementation of this system is based on object-oriented methodologies. A web-based extension of the prototype using 3-tier architecture is currently under development.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.163-175
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• 1997

Randomization of the run order within a block is a technique commonly employed by the experimenters of block designs to avoid biases in the estimates of the effects of interest. In practice, however the experimental responses are sometimes affected by the spatial or temporal position of the experimental units within a block. In such cases, it is preferable to use a systematic ordering of the treatments. It is often possible to find an ordering which will allow the estimation of treatment effects independently of any trend is known as a trend-free block designs. In many idustrial and agricultural experiments, treatments are applied to experimental units sequentially in time or space. This paper begins with a review of concepts and properties of trend-free designs. We, then devise algorithms to generate linear trend-free designs. We extend and modify the existing algorithm which is given by Bradley and Odeh(1988). Also, the algorithm which generate all possible linear trend-free designs in provided.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.663-671
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• 2006

This study was performed for exploring the spatial distribution pattern of Pinus densiflora and Quercus spp. in Korea. Firstly, the spatial distribution map of Pinus densiflora and Quercus spp. was prepared in grid of $100m{\times}100m$ at national level, using digital forest type map and actual vegetation map. And thematic maps for topography, climate, and soil were also prepared in the raster form of $100m{\times}100m$. Through GIS based spatial analysis of the digital distribution map of Pinus densiflora and Quercus spp. and thematic maps, the spatial characteristics of Pinus densiflora and Quercus spp. distribution was explored in relation to the environmental factors such as topography, climate, and soil. And the occurrence frequency models of Pinus densiflora and Quercus spp. were derived. Pinus densiflora occurs more often than Quercus spp. at low elevation, low slope gradient, and high temperature areas. In addition, Pinus densiflora is mainly distributed at shallow and well-drained loamy soil from igneous rocks. In contrast, Quercus spp. is more common at shallow and well-drained loamy soil from metamorphic rocks. As a result, the prediction model for the spatial distribution of Pinus densiflora and Quercus spp. by topographical variables has proven successful with high statistical significance. The result of this study can contribute to rational management of Pinus densiflora and Quercus spp. stand in Korea, considering environmental factors such as topography, climate, and soil.

• Korean Journal of Legislative Studies
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• v.26 no.2
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• pp.113-140
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• 2020

This study is meaningful in that it is the first analysis of Korean elections using the concept of spatial autocorrelation. Spatial autocorrelation means that an event occurring in one location in space has a high correlation with an event occurring in the surrounding area. The voter turnout rate in the 21^st general election of Seoul area was divided into the early-voting turnout and voting-day turnout, and the spatial pattern of the turnout was examined. Most of the previous studies were based on the unit of the precinct and personal data, but this study analyzed on the basis of the lower unit, Eup-myeon-dong, and analyzed using spatial data and aggregate data. Moran I index showed a fairly high spatial autocorrelation of 0.261 in the voting-day turnout, while the index of the early-voting turnout was low at 0.095, indicating that there was little spatial autocorrelation despite statistical significance. The voting-day turnout, which showed strong spatial autocorrelation, was compared and analyzed using the OLS regression model and the spatial statistics model. In the general regression model, the coefficient of determination R² rose from 0.585261 to 0.656631 in the spatial error model, showing an increase in explanatory power of about 7 percentage points. This means that the spatial statistical model has high explanatory power. The most interesting result is the relationship between the early-voting turnout and the voting-day turnout. The higher the early-voting turnout is, the lower the voting-day turnout is. When the early-voing turnout increases by about 2%, the voting-day turnout drops by about 1%. In this study, the variables affecting the early-voting turnout and the voting-day turnout are very different. This finding is different from the previous researches.

• Journal of the Korean Geographical Society
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• v.45 no.6
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• pp.806-819
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• 2010

Population data has been essential and fundamental in spatial analysis and commonly aggregated into political boundaries. A conventional method for population distribution estimation was a regression model with land use data, but the estimation process has limitation because of spatial autocorrelation of the population data. This study aimed to improve the accuracy of population distribution estimation by adopting a Regression-Kriging method, namely RK Model, which combines a regression model with Kriging for the residuals. RK Model was applied to a part of Seoul metropolitan area to estimate population distribution based on the residential zones. Comparative results of regression model and RK model using RMSE, MAE, and G statistics revealed that RK model could substantially improve the accuracy of population distribution. It is expected that RK model could be adopted actively for further population distribution estimation.

• Journal of Convergence for Information Technology
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• v.8 no.4
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• pp.247-253
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• 2018

This study was designed to analyze the difference in attendance and academic achievement based on spatio-temporal data relate to e-Learning patterns of university e-Learning learners. This study collected e-Learning data from 68 e-Learning classes, 13,611 learners during 3 years. Collected data were analyzed by t-test and two-way ANOVA. Major study findings were as follows. Firstly, e-Learning learners in school received higher than those of learners outside school both in attendance and academic achievement, while that academic achievement showed statistical significance. Secondly, the attendance and academic achievement by the day was in the order of e-Learning learners mainly in the morning, those in the afternoon and those at night, in addition there was statistical significance. Lastly e-Learning learners in the weekdays appeared higher than those of learners in the weekends both in attendance and academic achievement, also both of them showed statistical significance.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2009.04a
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• pp.262-264
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• 2009

국내 마케팅 시장은 전체 분야에 걸쳐 출혈경쟁이 이뤄지고 있다. 이와 같은 환경에서 기업들이 올바른 의사결정을 통해 경쟁력을 확보하려면 시장의 잠재력을 정량적으로 파악하는 노력이 필요하다. 특히, 배후지의 인구, 직장인, 그리고 유동인구 규모 등은 시장의 잠재력을 판단하는 기본 정보다. 배후지의 인구와 직장인 정보는 국가통계 자료 등을 활용하거나 기타 추정방법에 의해 산정되어 활용되고 있다. 하지만, 유동인구에 관한 정보는 실제 거리에 나가 인구를 측정하여 활용하는 방안 외에는 마땅한 추정방법이 없는 실정이다. 이러한 이유로 유동인구가 매출에 직접적인 영향을 주는 기업들은 많은 시간과 인력을 투입하여 유동인구 수를 측정하고 있다. 하지만, 비용적인 측면에서 한계가 있다. 본 연구에서는 Point 기반의 인문사회 Spatial DB를 활용하여 전국단위의 유동인구를 추정하는 방법론을 제안했다. 또한, 유동인구 정보에는 연령 및 성별 비율까지 추정하여 다양한 활용이 가능하도록 하였다.

• Proceedings of the Korea Information Processing Society Conference
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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.