• Spatial Information Research
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• v.20 no.6
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• pp.23-32
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• 2012

This study applied an exploratory analysis based on Self Organizing Map and GIS to cause specific age-standardized regional death rates data related to ten types of male cancers to find meaning patterns in the data. Then the patterns revealed from the exploratory analysis was evaluated to investigate possible relationship between these patterns and regional socio-economic status represented by regional educational attainment levels of head of household. The results from this analysis show that SI-GUN-GUs in Korea can be clustered to eighteen unique clusters in the stand point of male cancer death rates and these clusters are also spatially clustered. Also, the results reveal that regions with higher socio-economic status show lower level of the death rates compared with the regions with lower socio-economic status. However, for some cancer types, the regions with higher socio-economic status show relatively higher death rates. These patterns imply that the prevention, detection, and treatment of male cancers might be strongly affected by regional factors such as socio-economic status, environmental factors, and cultures and norms in Korea. Especially, one of the eighteen clusters, which includes Gangnam-Gu and Seocho-Gu, shows lower death rates in many of male cancer types. This implies that socio-economic status may be one of the most influential factors for regional cancer control.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.27-27
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• 2019

본 연구는 멸종위기 아고산수종 구상나무의 보존 복원을 위한 유전다양성을 고려한 표본추출전략을 구명하는데 그 목적이 있다. 2019년 9월에 한라산 영실 집단($14,000m^2$)에서 총 152개체를 대상으로 선발된 10개의 nSSR 마커를 이용하여 유전다양성 및 공간적 유전구조를 분석하였다. 평균 유전다양성은 관찰된 대립유전자수(A)가 7.2개, 유효대립유전자수($A_e$)가 3.6개, 이형접합도 관찰치($H_o$)가 0.528, 이형접합도 기대치($H_e$)가 0.595이며, 고정지수(F)는 0.071 이었다. 조사구내 구상나무 성목 152개체는 평균 수고 3.6 m, 흉고직경 17.3 cm로 나타났다. 구상나무의 개체목간 평균거리는 3.94 m, 임분밀도는 700 본/ha 이며 개체의 공간적 분포는 임의분포 형태로 나타났다. 구상나무의 유전변이에 대한 공간적 자기상관성(spatial autocorrelation) 분석 결과, 조사구의 구상나무는 약 15 m 이내에서 분포하는 개체들 간 유전적 유사성이 있게 분포하는 것으로 나타났으며 임분밀도가 높고 수고가 낮은 특성으로 인하여 비교적 작은 유전군락이 형성된 것으로 사료된다. 결과적으로 영실의 구상나무 집단의 보존 복원을 위한 표본추출전략은 15 m의 간격을 두고 개체를 선발하는 것이 타당한 것으로 나타났다.

• Journal of Korea Planning Association
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• v.54 no.7
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• pp.89-102
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• 2019

The growth of vacant housing has been problematic in both Korea and other countries as it causes various socio-economic problems and negatively affects residential environments. Despite the importance of effectively managing vacant housing, few studies have been undertaken regarding spatial patterns of vacant housing growth. This study aims to examine spatial dependence in vacant housing growth. We used 2005 and 2015 Population and Housing Census and employed spatial modeling. The empirical analysis shows that there is spatial dependence in vacant housing growth. Also, the spatial clusters of growing vacant housing are present in the non-capital region and nearby cities while the spatial clusters of declining vacant housing are present in the capital region. The policy implications of this study are as follows: First, local governments should make collaborate efforts with geographically proximate cities for more effective management of vacant housing. Second, given that vacant housing is more prevalent and growing in the non-capital region, it is necessary to employ differential policies to manage housing vacancy between the capital and non-capital regions.

• 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 the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.43-51
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• 2012

The OLS(ordinary least squares) method is widely used in hedonic housing models. One of the assumptions of the OLS is an independent and uniform distribution of the disturbance term. This assumption can be violated when the spatial autocorrelation exists, which in turn leads to undesirable estimate results. An alterative to this, spatial econometric models have been introduced in housing price studies. This paper describes the comparisons between OLS and spatial econometric models using housing transaction prices of Busan, Korea. Owing to the approaches reflecting spatial autocorrelation, the spatial econometric models showed some superiority to the traditional OLS in terms of log likelihood and sigma square(${\sigma}^2$). Among the spatial models, the SAR(Spatial Autoregressive Models) seemed more appropriate than the SAC(General Spatial Models) and the SEM(Spatial Errors Models) for Busan housing markets. We can make sure the spatial effects on housing prices, and the reconstruction plans have strong impacts on the transaction prices. Selecting a suitable spatial model will play an important role in the housing policy of the government.

• Journal of the Korean Geotechnical Society
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• v.21 no.3
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• pp.5-17
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• 2005

Spatial uncertainty of Busan marine clay ground, which commonly occurs during site investigation testing, data analysis and transformation modeling, has been described. In this paper geotechnical uncertainty of shear strength indicator $N_k$ has been quantified in both horizontal direction and vertical direction using geostatistical Kriging method. Most of soil data used are from 25 boring tests, 75 laboratory tests, 124 field vane tests and 25 cone penetration tests (CPT). CPT-$N_k$ data for undrained shear strength determination, which are the most important properties in geotechnical design stages, have been analysed. Comparison between cone factor from conventional CPT-based method and that of geostatistical method shows that geostatistical Kriging method is an ideal tool to quantify the spatial variability of uncertainty from self-correlation of soil property of interest, and can be recommended to identify the spatial distribution of consolidation .md shear strength of soils at any sites concerned.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.310-323
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• 2023

Urbanization and income distribution issues are global interest, and the results of studies on the impact of urbanization on income inequality are different for each country and period. This study analyzes the impact of urbanization on income inequality using regional data from 2000-2021. In particular, serial correlation, spatial dependence, and common factor effects of the Gini coefficient are confirmed and analyzed through a dynamic spatial panel regression model. As a result, urbanization has a positive effect on reducing income inequality. Therefore, it is necessary to continuously promote regional urbanization to improve the income distribution problem. Areas with already high urbanization rates should reduce income inequality by narrowing the wage gap by expanding training opportunities for low-skilled workers, and need to come up with measures to prevent counter-urbanization.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.12-25
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• 2009

The aim of this study is to analyze the periodical and spatial characteristics of urban crime and to find out the factors that affect the crime occurrence. For these, crime data of Masan City was examined and crime occurrence pattern is ploted on a map using crime density and criminal hotspot analysis. The spatial relationship of crime occurrence and factors affecting crime were also investigated using ESDA (Exploratory Spatial Data Analysis) and SAR (Spatial Auto-Regression) model. As a result, it was found that crimes had strong tendency of happening during a certain period of time and with spatial contiguity. Spatial contiguity of crimes was made clear through the spatial autocorrelation analysis on 5 major crimes. Especially, robbery revealed the highest spatial autocorrelation. However as a autocorrelation model, Spatial Error Model(SEM) had statistically the highest goodness of fit. Moreover, the model proved that old age population ratio, property tax, wholesale-retail shop number, and retail & wholesale number were statistically significant that affect crime occurrence of 5 most major crimes and theft crime. However population density affected negatively on assault crime. Lastly, the findings of this study are expected to provide meaningful ideas to make our cities safer with U-City strategies and services.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.202-222
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• 2023

This study traces the growth and changes in the spatial distribution and characteristics of media cluster in Seoul by focusing on the co-evolution of film and TV production. To identify the spatial distribution and aggregation of film and broadcast TV production, we measure their spatial auto-correlation based on Moran's I and LISA, using the data from the Census on Establishments of the National Statistical Office. In addition, the eleven semi-structured interviews conducted with workers in the media industries, such as film crews and TV drama producers, help to clarify the complexity and dynamics of diverse factors that affect spatial distribution of media cluster. This multi-method study shows the increasing polycentricity of media cluster in the last decade. Gangnam, Mapo, Yeouido, Gangseo-Yeongdeungpo, and Seongsu have emerged as key hubs for media industries, particularly in light of changes in the transportation system and the real estate market. The finding indicates the co-evolution of film and broadcast TV production, demonstrating how the characteristics of the creative industry and metropolitan changes are intertwined with each other in shaping the geographical pattern of the media cluster.