• Journal of Korean Society of Rural Planning
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• v.25 no.3
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• pp.1-9
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• 2019

Population is important as a fundamental element of local industry and economy, and census data is essential to regional planning and policy making. Although there have been many researches on population and regional planning, there are few studies on population considering spatial unit. In this study, the population of three spatial scales were compared in order to establish the spatial unit suitable for the rural planning. The study area is Gangwon, Chungcheong-Nam, Chungcheong-Buk, Jeolla-Nam, Jeolla-Buk, Gyeonsang-Nam, Gyeonsang-Buk and Jeju province. Population were compared using statistical data analysis, GIS visualization, and spatial statistics. The mean, maximum, minimum, and variance of population were calculated and the coefficient of variation according to spatial unit was compared. The mean, maximum, minimum, and variance of population were calculated and the coefficient of variation according to spatial unit was compared. As the results, the census output area unit is difficult to interpret spatial analysis results. Administrative district unit has the limit that includes areas where the population does not live. The grid unit is well suited to the geographical characteristics but has many disadvantages of the grid with small population. Therefore, It is necessary to complement the limits of the Eup and Myeon-dong administrative district through the grid unit data.

• Economic and Environmental Geology
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• v.28 no.3
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• pp.271-277
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• 1995

The geological information analysis based on spatial statistical techniques have been studied in relation to mineral exploration. The applicability of outlier detection using moving-window statistics and directional cross-variography analysis have been verified by using geochemical data sets surveyed in the Taebaek area for mineral exploration. The directional variogram analysis has been basically known as a geostatistical method for spatial continuity measures. In this study, the application of this proposed method was extended to measure spatial correlation or similarity problems between two geochemical elements. For the appraisal of the usefulness of this scheme, five kinds of variogram functions were computed for original data and revised data, obtained by removing outliers detected by moving-window statistics and the results were compared. It is concluded that these advanced spatial statistical methods at the interpretation stage of spatial similarity provide us with valuable quantitative results as decision-supporting information for regional mineral exploration task.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.350-369
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• 2018

The aim of this study is to investigate foreigner's spatial change and relations to industrial workers in the sixteen districts of Busan metropolitan city from 2000 year to 2015 year. To achieve the goal, the data published in Pusan Statistical Yearbook was analyzed by descriptive and inferential statistics. The results are summarized in the followings. Firstly, the spatial changes of foreigners as a whole during 2000~2015 year are different based on their nationality. Secondly, foreigner's spatial change based on nationality and gender is much complex. The meaning of foreigner's spatial change in each district tested by nonparametric statistics is different according to a time scale. Thirdly, the relationality between foreigners as a whole and industrial workers in the sixteen districts is different by nationality and gender. The study method can be utilized at other cities or regions, and the results of those studies can be helpful to solve various problems due to increasing foreigners.

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.865-875
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• 2012

In this study, we identify the variables that affect the number of crime and spatial correlation in the Seoul metropolitan area, in addition, we measure the relative risk on the incidence of crime by a Poisson regression model. We suggest a statistical methodology to make a risk map for crime based on relative risk instead of the total event of crime by region using the Geographic Information System. To demonstrate the use and advantages of this methodology, this study presents an analyses of the total crime count in 25 wards in the Seoul metropolitan area.

• 대한예방의학회:학술대회논문집
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• 1998.10b
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• pp.72-73
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• 1998

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.6_2
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• pp.601-609
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• 2013

Standard lots, which are used to assess values of individual lots in Korea, have been criticized for their improper distribution. However, there has been very little evaluation for the spatial distribution of standard lots, and an evaluation method has never been developed. In order to overcome this situation, we attempt to assess the appropriateness of the spatial distribution of standard lots using the L-index and Monte Carlo simulation. The L-index is a well-known indicator of the complete spatial randomness (CSR) of points in spatial statistics. If the L-index of standard lots is similar to that of individual lots, the former is considered to be randomly distributed according to the latter. By analyzing L-indices of two study areas, Gangnam and Seongdong, we find a statistically significant difference in Gangnam area and a relatively small difference in Seongdong area. We confirm that the spatial distribution of standard lots is not CSR and that the L-index is useful as an evaluation method. These results suggest that the standard lot selection and management guidelines need to be modified to apply the spatial distribution of individual lots to the standard lot selection process.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1141-1150
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• 2006

In this study, we performed spatial cluster analysis which considered spatial information using earthquake data for Korean peninsula occurred on 1978 year to 2005 year. Also, we look into how to be clustered for regions using earthquake magnitude and frequency based on spatial scan statistic. And, on the basis of the results, we constructed earthquake map by earthquake outbreak risk and gave a possible explanation for the results of spatial cluster analysis.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.991-993
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• 2003

The 4 sets of environmental variables dealing with meteorology, hydrology and physiography were analyzed to generate a spatial drought risk index of Phitsanulok province of Thailand. The analysis of K-mean and discriminant were applied to the set of the selective drought variables for grouping each of spatial variable set into 4 classes. The obtained 4 classes, based on group statistics, were thus recoded in the meaning of no risk, low risk, moderate risk, and high risk. The regression coefficient between recoded classes and a set of the selective environmental variables were then applied as spatial variable weighting on thematic dataset in GIS spatial analysis. The results showed that the weighting score of drought variable was highest in meteorological variable compared to other variables.

• Journal of Preventive Veterinary Medicine
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• v.41 no.2
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• pp.79-83
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• 2017

In this study, we used a choropleth map to explore the spatial variation of the risk of cattle herds being bovine tuberculosis (BTB) positive in Gangwon-do in 2015. The map shows that the risk of being BTB-positive was lower in provinces located in the middle of Gangwon-do (Wonju, Youngwol, Peongchang, and Kangneung) than in other provinces. In addition, one province located in the north (Goseong) had a low risk of BTB. The estimate for the intercept of the spatial lag model was 0.66, and the spatial autocorrelation coefficient (lambda) was 0.20 (Table 1). The Moran's I was 0.33 with p-value of 0.02. In 2015, provinces located in the North West (Hwacheon) and East (Donghae) of Gangwon-do had a higher BTB risk. We identified some specific provinces at low BTB-positive risk, information that may prove useful for control of BTB in the study area.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.637-645
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• 2003

Small area estimation had been studied using data-based methods such as Direct, Indirect, Synthetic methods. However recently, model-based such as based on regression or time series estimation methods are applied to the study. In this paper we investigate a model-data based small area estimation which takes into account the spatial relation among the areas. The Economic Active Population Survey in 2001 are used for analysis and the results from the model based and model-data based estimation are compared with using MSE(Mean squared error), MAE(Mean absolute error) and MB(Mean bias).