• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.327-336
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• 2004

Many researchers have used the robust variogram to reduce the effect of outliers in spatial data analysis. Recently it is known that estimating the variogram after replacing outliers is more efficient. In this paper, we suggest a new data cleaner for geostatistic data analysis and compare the efficiency of outlier cleaners.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.294-305
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• 2012

The objective of this study is to estimate the chemical compositions and to identify qualitative sources of fall-out particles in study area. Also, this study used a spatial analysis to estimate spatial distributions and average deposition flux. In this study, the chemical compositions of fall-out particle samples collected at Muncheon lake from May 2010 to January 2011 were analyzed by ICP and IC. The monthly trend of deposition fluxes for fall-out particles showed highest in June ($107.61kg/km^2/day$) and lowest in October ($22.22kg/km^2/day$). The average fluxes of Fe, Si, Al, Zn and Ba are 0.44, 0.24, 0.20, 0.17, $0.09kg/km^2/day$, respectively. Also, the average fluxes of $NO_3^-$, $SO_4^{2-}$, $NH_4^+$, $Ca^{2+}$, and $Na^+$ are 6.48, 5.01, 4.96, 1.75, $1.37kg/km^2/day$, respectively. A Factor analysis identified four sources such as 1) nonferrous metal, motor vehicle, and agriculture, 2) soil, 3) field burning, incineration, and 4) road dust and oil burning. The IDW (inverse distance weighting) spatial analysis method was used to estimate spatial distribution and average deposition flux for fall-out particles. A total average deposition fluxes estimated in Muncheon lake were 936.15 kg/month. The spatial distribution trend of deposition flux showed higher at site 1 and 2 than at site 3, 4 because local road is adjacent to the site 1 and 2.

• Journal of Environmental Impact Assessment
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• v.22 no.5
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• pp.467-479
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• 2013

This study was conducted to find out characterization of spatial distribution of birds observed in river areas. Our bird survey was carried out 4 times at 31 sites from January to September in 2011. A total of 1,609 accumulated individuals belonging to 59 species, 28 families and 11 orders were observed. In the result of spatial autocorrelation analysis using the richness index of the maximum counts of each sites, we confirmed that the distribution of birds in Namdaecheon river was clustered and the tendency of spatial autocorrelation was apparent. The area of each sites within a 200m radius was classified in four biotope categories such as agricultural land, forest, residential area and water area, and the spatial autocorrelation was analysed about four types. In the result of spatial autocorrelation analysis for four biotope categories, all types were showed the positive spatial autocorrelation, but the type of water area was higher than other types. The positive correlation was found between the water area and water birds in statistical significance. However, the forest birds had non-significance values. Therefore, it is appropriate to focus on water birds except for forest birds, when researches of bird distribution in river ecosystem is conducted. The number of bird species and individuals increased as the riverside of water area was to widen. Thus, if the areas of riverside offering the feeding and roosting area increase, it will be accommodated many birds. Also, the areas of riverside should be maintained naturally because it is an important habitats of birds. Our study area is on the outskirts the city of higher rates of forest and agricultural land, it may be unreasonable to apply our results to the whole rivers. If the research about the river flowing around the city will be conducted, it is expected to be useful to the relation study area such as ecological river's restoration.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• Korean Journal of Child Studies
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• v.26 no.5
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• pp.217-232
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• 2005

This study examined the effects of an art program based on multiple intelligence theory on children's creativity and spatial ability. The art education program focused on three processes : perception, production and reflection. Subjects were 68 five-year-old children. The experimental design was 'The Untreated Control Group Design with Pretest & Posttest'. ANCOV was employed for statistical analysis. Results were that the children in the experimental group scored significantly higher on creativity and spatial ability than the children in the control group. Results imply that an art education program based on multiple intelligence theory can be an effective teaching model for improving children's creativity and spatial ability.

• KCID journal
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• v.13 no.1
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• pp.39-49
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• 2006

Weather station based PET(Potential Evapotrarspiration) analysis has often been inadequate to meet the needs of regional-scale irrigation planning. A map of continuous PET surface would be better a solution for the spatial interpolation considering spatial variations. Using a normal PET data collected at the 54 meteorological stations in Korea, 10-days spatial distribution PET map was created using universal Kriging(UK). These estimation methods were evaluated by both visual assessments of the output maps and the quantitative comparison of error measures that were obtained from the cross validation. The universal Kriging method showed appropriate results in spatial interpolation from weather station based PET to spatial PET with low statistical errors.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.6
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• pp.650-662
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• 2011

The statistical tools such as empirical orthogonal function (EOF), and singular value decomposition (SVD) have been applied to analyze the characteristic of air pollutant over southeast Asia as well as to evaluate Zimeke's tropospheric column ozone (ZTO) determined by tropospheric residual method. In this study, we found that the EOF and SVD analyses are useful methods to extract the most significant temporal and spatial pattern from enormous amounts of satellite data. The EOF analyses with OMI $NO_2$ and OMI HCHO over southeast Asia revealed that the spatial pattern showed high correlation with fire count (r=0.8) and the EOF analysis of CO (r=0.7). This suggests that biomass burning influences a major seasonal variability on $NO_2$ and HCHO over this region. The EOF analysis of ZTO has indicated that the location of maximum ZTO was considerably shifted westward from the location of maximum of fire count and maximum month of ZTO occurred a month later than maximum month (March) of $NO_2$, HCHO and CO. For further analyses, we have performed the SVD analyses between ZTO and ozone precursor to examine their correlation and to check temporal and spatial consistency between two variables. The spatial pattern of ZTO showed latitudinal gradient that could result from latitudinal gradient of stratospheric ozone and temporal maximum of ZTO in March appears to be associated with stratospheric ozone variability that shows maximum in March. These results suggest that there are some sources of error in the tropospheric residual method associated with cloud height error, low efficiency of tropospheric ozone, and low accuracy in lower stratospheric ozone.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.665-685
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• 2021

This study focused on the a 20-year evaluation of the dynamism of critical thermal anomalies in Busan metropolitan area prompted by unusual infrastructural development and demographic growth rate. Archived Landsat thermal data derived-LST was the major input for UTFVI and hot spot analysis (Getis-Ord Gi^*). Results revealed that the surface urban heat island-affected area has gradually expanded overtime from 23.32% to 32.36%; while the critical positive thermal anomalies (level-3 hotspots) have also spatially increased from 19.88% in 2000 to 23.56% in 2020, recording a net LST difference of > 5℃ between the maximum level-3 hotspot and minimum level-3 coldspot each year. It is been observed that thermal conditions of Busan have gradually deteriorated with time, which is potentially inherent in the rate of urban expansion. Thus, this work serves as an eye-opener to powers that be, to think and act constructively towards a sustainable thermal conform for city dwellers.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.873-885
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• 2016

Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).