• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.387-397
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• 2008

Recently many researches on data analysis using spatial statistics have been studied in various field and the studies on small area estimations using spatial statistics are in actively progress. In analysis of lattice data, defining the neighborhood information system is the most crucial procedure because it also determines the result of the analysis. However the used neighborhood informal ion system is generally defined by sharing the common border lines of small areas. In this paper the other neighborhood information systems are introduced and those systems are compared with Moran's I statistic and for the comparisons, Economic Active Population Survey (2001) is used.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.271-280
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• 2005

Kriging methods as traditional spatial data analysis methods and geographical weighted regression models as statistical analysis methods are compared. In this paper, we apply data from the Ministry of Environment to spatial analysis for practical study. We compare these methods to performance with monthly carbon monoxide observations taken at 116 measuring area of air pollution in 1999.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.855-866
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• 2008

Recently many small area estimation methods using the lattice data analysis have been studied and known that they have good performances. In the case of using the lattice data which is mainly used for small area estimation, the choice of better neighborhood information system is very important for the efficiency of the data analysis. Recently Lee and Shin (2008) compared and analyzed some neighborhood information systems based on GIS methods. In this paper, we evaluate the effect of various neighborhood information systems which were suggested by Lee and Shin (2008). For comparison of the estimators, MSE, Coverage, Calibration, Regression methods are used. The number of unemployment in Economic Active Population Survey(2001) is used for the comparison.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.403-414
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• 2009

Many researches have been devoted to the small area estimation related with the area level statistics. Almost all of the small area estimation methods are derived based on minimization of mean squared error(MSE). Recently Hwang and Shin (2008) suggested an alternative small area estimation method by minimizing mean squared percentage error. In this paper we apply this small area estimation method to the labor statistics, especially monthly wages by a branch area of labor department. The Monthly Labor Survey data (2007) is used for analysis and comparison of these methods.

• Journal of Fashion Business
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• v.10 no.1
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• pp.148-163
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• 2006

The purpose of this study is to examine differences in university students' spatial behavior and time for purchasing weekdays or weekends according to trading areas they use to purchase casual wears. Theoretical background examined trading areas, in Busan, consumers' spatial behavior. An empirical research developed a questionnaire as a measuring tool to conduct a preliminary survey and a main survey. Data collection was implemented with 507 students from four universities in Busan; and for data analysis, descriptive statistics, cross-tabulation analysis, correspondence analysis, and McNemar test were carried out by using the SPSS for Windows 12.0K program. This study obtained the main results as follows: The characteristics of university students' spatial behavior according to trading areas show significant difference in reasons of trading area selection, time slots for visiting. University students who visited the Seomyeon trading area were found to consider comparison-based purchasing and prominence of the trading area, regardless of the time for purchasing weekdays or weekends. As for trading areas around Busan National University, visits were mainly due to accessibility. Students visited trading areas in Nampo-Gwangbok-dong regardless of the time for purchasing in diverse reasons of trading area selection, time slots. As for trading areas around Kyungsung University, students were visited due to accessibility.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.89-113
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• 2023

This study aimed to identify heat wave vulnerable areas and discuss spatial typology and policy directions through spatial coincidence analysis of heat wave damage. By utilizing the climate change vulnerability assessment of the Intergovernmental Panel on Climate Change (IPCC) and Spatial Statistics Comparison Analysis, this study examined cities, counties, and districts in South Korea for five years (2015-2019), including 2018, when the heat wave was most extreme. It was determined that the number of heat wave days (exposure) was the most impactful among various factors for heat wave vulnerability. Sensitivity and adaptive capacity to heat waves were found to vary according to regional characteristics. The relationship between heat wave vulnerability and damage was categorized into four types through spatial coherence. Hot to Hot and Cold to Cold types have a positive relationship between vulnerability and damage, while Hot to Cold and Cold to Hot types have a negative relationship. The findings suggest that since different types of regions have distinct characteristics and conditions, policies and research for improvement should be directed to address each region separately. This study may be used as basic data for establishing heat-related policies in the future, as it categorizes regions by considering both heat vulnerability and damage and examines the direction of response by type.

• Journal of Korea Water Resources Association
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• v.43 no.11
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• pp.933-944
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• 2010

This study compares the CEM and SGS methods which are geostatistical stochastic simulation methods for assessing the uncertainty by spatial variability in the estimation of the spatial distribution of probability rainfall. In the stochastic simulations using CEM and SGS, two methods show almost similar results for the reproduction of spatial correlation structure, the statistics (standard deviation, coefficient of variation, interquartile range, and range) of realizations as uncertainty measures, and the uncertainty distribution of basin mean rainfall. However, the CEM is superior to SGS in aspect of simulation efficiency.

• Korean Journal of Veterinary Research
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• v.53 no.1
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• pp.49-54
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• 2013

To investigate the transmission pattern of geographical area and temporal trends of the 2010~2011 foot-and-mouth disease (FMD) outbreaks in Korea, and to explore temporal intervals at which spatial clustering of FMD cases space-time analysis based on georeferenced database of 3,575 burial sites, from 30 November 2010 to 23 February 2011, was performed. The cases represent approximately 98.1% of all infected farms (n = 3,644) during the same period. Descriptive maps of spatial patterns of the outbreaks were generated by ArcGIS. Spatial Scan Statistics, using SaTScan software, was applied to investigate geographical clusters of FMD cases across the country. Overall, spatial heterogeneity was identified, and the transmission pattern was different by province. Cattle have more clusters in number but smaller in size, as compared to the swine population. In addition, spatiotemporal analysis and the comparison of clustering patterns between the first 7 days and days 8 to 14 of the outbreak revealed that the strongest spatial clustering was identified at the 7-day interval, although clustering over longer intervals (8~14 days) was also observed. We further discussed the importance of time period elapsed between FMD-suspected notice and the date of confirmation, and emphasized the necessity of region-specific and species-specific control measures.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.1093-1107
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• 2008

In this study, we considered linear regression model with various spatial dependency structures in order to make more reliable prediction of precipitation in South Korea. The prediction approaches are based on semi-variogram models fitted by least-squares estimation method and restricted maximum likelihood estimation method. We validated some candidate models from the two different estimation methods in terms of cross-validation and comparison between predicted values and observed values measured at different locations.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.15 no.2
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• pp.18-24
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• 2007

The high ionospheric spatial gradient during ionospheric storm is the most concern when applying GNSS(Global Navigation Satellite System) augmentation systems for aircraft precision approach. Since the ionospheric gradient level depends on geographical location as well as the storm, understanding the ionospheric gradient statistics over a specific regional area is necessary for operating the augmentation systems. This paper compares three ionosphere gradient computation methods, direct differentiation between two receivers' ionospheric delay signal for a common satellite, derivation from a grid ionosphere map, and derivation from a plate ionosphere map. The plate map method provides a good indication on the gradient variation behavior over a regional area with limited number of GNSS receivers. The residual analysis for the ionosphere storm detection is discussed as well.