• Horticultural Science & Technology
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• v.32 no.1
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• pp.84-90
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• 2014

Berchemia racemosa var. magna is only found in Anmyeon Island of South Korea. Genetic diversity and the spatial genetic structure of B. racemosa var. magna in Anmyeon Island were studied by I-SSR marker system. Fifty I-SSR amplicons were produced from 8 selected primers. We used 13 polymorphic markers to analyze the genetic structure. Distribution of 39 individuals in the study plot($90m{\times}70m$) showed aggregate pattern (aggregation index = 0.706). Total 21 genets were observed from 39 individuals through I-SSR genotyping. Proportion of distinguishable genotype (G/N), genotype diversity (D) and genotype evenness (E) were 53.8%, 0.966 and 0.946, respectively. In spite of the small number and the narrow distribution, Shannon's diversity index (I = 0.598) was relatively high as compared with those of the other plant species. For ex situ genetic conservation of B. racemosa var. magna, the sampling strategy based on spatial autocorrelation using Tanimoto distance is efficient at choosing the conserved individuals with a 6 meter interval between individual trees.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.45-55
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• 2018

The purpose of this study was to provide the necessary data to explore the development plans of consumer organizations by looking at the spatial distribution of consumer organizations. This is because community-based consumer organizations can propose concrete measures to solve consumer problems more effectively. In this study, data of 11 consumer organizations and 815 branches were collected and analyzed using local indicators of spatial distribution and spatial lag model. First, it was difficult to find patterns according to the geographical characteristics of the spatial distribution of consumer organizations. Second, consumer organizations were more distributed in areas with large populations and businesses and large areas. Third, there is a discrepancy between the demand and supply of consumer organizations when compared with the number of consumer counseling. Based on this, it is necessary to constantly seek concrete development plans by supplementing the qualitative data on the activities of consumer organizations.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.193-204
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• 2010

Recently, researchers of the various fields where the spatial analysis is needed have more interested in spatial statistics. In case of data with spatial correlation, methodologies accounting for the correlation are required and there have been developments in methods for spatial data analysis. Lattice data among spatial data is analyzed with following three procedures: (1) definition of the spatial neighborhood, (2) definition of spatial weight, and (3) the analysis using spatial models. The present paper shows a spatial statistical analysis method superior to a general statistical method in aspect estimation by using the trimmed mean squared error statistic, when we analysis the spatial lattice data that outliers are included. To show validation and usefulness of contents in this paper, we perform a small simulation study and show an empirical example with a criminal data in BusanJin-Gu, Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.95-104
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• 2018

This study has the purpose of suggesting the method to analyze the spatiotemporal change of satisfaction concerning the officially assessed land price using geostatistical analysis. Analyzing the spatial distribution characteristic of officially assessed land price using present GIS (Geographic Information System) or is staying at qualitatively suggesting the improvement method of the officially assessed land price system. Grouping the appeal strength based on the official price and opinion price of officially assessed land price, GIS DB (Database) was constructed and the time seriate satisfaction were analyzed and compared through spatial density analysis and spatial autocorrelation analysis. As a result, it was found that the difference between the official price and the applicant's price differed depending on individual land, but most of the respondents requested the increase or the reduction of the average land price, which resulted in a large number of request. Analyzing the satisfaction of the officially assessed land price by using GIS, it was known that satisfaction of officially assessed land price could be analyzed by using the difference of the opinion price and not only the officially assessed land price. Spatiotemporal change of officially assessed land price satisfaction was known to be possible through spatiotemporal pattern analysis method such as spatiotemporal auto-corelation analysis and hotspot analysis etc using GIS. In short, regionally positive or negative significant relationship was investigated through spatiotemporal analysis using annual data.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.251-261
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• 2005

The quality of MT (magnetotellurics) data highly depends on the level of artificial noise form industrial sources. We have conducted the feasibility study of MT noise modelling using digital spatial data and spatial modelling through the comparison between the predicted and the measured MT noises. A simple noise model predicting the intensity of electromagnetic field radiated from the latent noise sources, that is, the electric facilities in the building, road and high-voltage powerline, is developed in consideration of the propagation property of electromagnetic waves. From the analysis of correlation between the predicted and the measured noise power, the correlation coefficients of electric field are higher than those of magnetic field in whole frequency band. The magnetic field component has the high correlation in the narrow band near 60 Hz only. The spatial noise modelling proposed in this study would provide some useful informations for the MT surveys in the noisy environment like urban area.

• Korea journal of population studies
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• v.32 no.2
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• pp.59-85
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• 2009

본 연구는 최근 인구학에서 공간적 접근을 시도하는 논의들이 활발해지는 경향과 함께 지역 적합적 저출산 대응정책의 필요성의 대두라는 정책적 수요에 부합하고자 자녀출산계획에 있어 지역의 공간적 효과가 미치는 효과를 분석하였다. 또한, 기혼여성의 연령, 출산한 자녀의 수가 자녀를 출산할 계획을 가질 확률에 대한 비선형적 효과를 실증적으로 분석하였다. 다층모형과 같이 최근 지역연구에서 이용되고 있는 실증분석방법들의 한계점을 살펴보고, 그 대안으로 Geo-Additive Model을 적용하였다. 동 방법론은 한 모형 내에서 공간의 구조적 효과와 비구조적 효과, 연속형 변인의 비선형효과 등을 동시에 추정할 수 있다. 이를 위한 분석자료로 통계청의 2005년도 인구주택총조사의 마이크로데이터 중 2% B형 자료를 이용하였다. 분석결과 기혼여성이 자녀를 출산할 계획을 가질 확률에 기혼여성의 연령과 출산한 자녀의 수는 비선형적 효과를 주었으며, 특히 각 개인들은 현재의 출산 상태에서 자녀 한명을 추가로 출산하는 것이 동일한 부담으로 작용하지 않음을 알 수 있었다. 이를 통해 기혼여성들의 첫출산 시점이 결혼연령에 따라 차이가 있고 결혼코호트에 따라 다르더라도 첫출산 자체가 여전히 보편적인 현상이라는 가정을 받아들인다면, 출산율 제고를 위한 정책의 대상은 첫째아를 이미 출산한 여성들이 되어야 할 것으로 보인다. 또한, 자녀를 출산할 계획을 가질 확률에 지역의 구조적 공간효과가 유의미한 영향을 주는 것으로 분석되었다. 지역별 합계출산율의 공간 자기상관분석 결과와 비교해 본 결과 출산계획의 구조적 공간효과가 양의 효과를 미치는 지역에서는 실제 출산행위인 합계출산율도 높지만, 구조적 공간효과가 부적인 효과를 가지고 있는 지역에서는 합계출산율도 낮게 나타남을 알 수 있었다. 따라서 각 지방자치단체에서는 지자체들의 정책수요나 자원 및 재정의 부담능력 등 지역별 차이를 고려하지 않은 일률적인 정책의 추진을 지양하고, 지역 특수성을 고려하여 지역에 적합한 출산정책을 추진해야 할 것이다.

• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.630-633
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• 2010

입지분석은 공간 및 비공간적 특성이 중요하게 다루어져야 함에도 불구하고 공간데이터 타입(spatial data type), 공간관계(spatial relationship), 그리고 공간 자기상관성(spatial autocorrelation)의 복잡성에 기인한 처리의 어려움으로 인해 기하학적거리나 공간적 위치와 같은 단순 공간적 특성만 이용되었다. 본 연구에서는 서울시 대형할인점을 사례로하여로 GIS에 의한 공간데이터와 비공간데이터(인구통계 등)를 통합 구축한 후, 공간데이터마이닝 기법을 이용하여 입지패턴(location pattern)을 분석 추출하여 보고자 한다.

• Survey Research
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• v.10 no.3
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• pp.1-19
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• 2009

This study investigates the utilities of spatial analysis in the context of survey research using Geographical Information System(GIS) and Geographically Weighted Regression (GWR) which take account of spatial heterogeneity. Many social phenomena involve spatial dimension, and with the development of GIS, GPS receiver, and online location-based services, spatial information can be collected and utilized more easily, and thus application of spatial analysis in the survey research is getting easier. The traditional OLS regression models which assume independence of observations and homoscedasticity of errors cannot handle spatial dependence problem. GWR is a spatial analysis technique which utilizes spatial information as well as attribute information, and estimated using geographically weighted function under the assumption that spatially close cases are more related than distant cases. Residential survey data from a Primary Autonomous District are used to estimate a model of public service satisfaction. The findings show that GWR handles the problem of spatial auto-correlation and increases goodness-of-fit of model. Visualization of spatial variance of effects of the independent variables using GIS allows us to investigate effects and relationships of those variables more closely and extensively. Furthermore, GIS and GWR analyses provide us a more effective way of identifying locations where the effect of variable is exceptionally low or high, and thus finding policy implications for social development.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.581-590
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• 2017

This study analyzes the effect of floating population, locational characteristics and spatial autocorrelation on foodservice sales using big data provided by the Seoul Institute. Although big data provided by public sector is growing recently, research difficulties are occurred due to the difference of aggregation units of data. In this study, the aggregation unit of a dependent variable, sales of foodservice is SKT unit but those of independent variables are various, which are provided as the aggregation unit of Korea National Statistical Office, administration dong unit and point. To overcome this problem, we convert all data to the SKT aggregation unit. The spatial error model, SEM is used for analysing spatial autocorrelation. Floating population, the number of nearby workers, and the area of aggregation unit effect positively on foodservice sales. In addition, the sales of Jung-gu, Yeongdeungpo-gu and Songpa-gu are less than that of Gangnam-gu. This study provides implications for further study by showing the usefulness and limitations of converting aggregation units of heterogeneous spatial data.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.153-159
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• 1996

Linear models for spatial data are proposed by example in the paper. This method was introduced to Korea for the first time in the early part of 1990's. The correlation of spatial patterns is computed by Moran Index., and then correlogram is proposed as the method to identify correlation of spatial patterns. Due to computational difficulties with ML, an alternative estimator has been used as an eigenvalue method.