• Journal of Climate Change Research
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• v.7 no.1
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• pp.69-75
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• 2016

Recently, many countries all over the world have been suffered from disaster caused by climate change. Especially in case of developed countries, the disaster is concentrated in the industry sector. In this research, we analyzed industrial vulnerable homogeneous hotspot for the climate change using spatial autocorrelation analysis on the south Korea. Homogeneous hot spot areas through autocorrelation analysis indicate the spatial pattern of areas interacted each other. Industry sector have responsibility of green house gas emissions, and should adapt to the climate change caused by greenhouse gas already released. So, we integrated the areas sensitive to mitigation option with the areas hardly adapt to climate change because of vulnerable infrastructure. We expected that the result of this research could contribute to the decision-making system of climate change polices.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.162-174
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• 2012

To visualize the characteristics of vertical seawater temperature data, in the ocean having 3D spatial characteristics, 2D thematic maps like horizontal seawater temperature distribution map at each depth layer and 3D volume model using 3D spatial interpolation are used. Although these methods are useful to understand oceanographic phenomena visually, there is a limit to analyze the spatial pattern of vertical temperature distribution or the relationship between vertical temperature characteristics and other oceanic factors (seawater chemistry, marine organism, climate change, etc). Therefore, this study aims to determine the spatial distribution characteristics of vertical temperature profiles in the South Sea of Jeju by quantifying the characteristics of vertical temperature profiles by using an algorithm that can extract the thermocline parameters, such as mixed layer depth, maximum temperature gradient and thermocline thickness. For this purpose spatial autocorrelation index (Moran's I) was calculated including mapping of spatial distribution for three parameters representing the vertical temperature profiles. Also, after grouping study area as four regions by using cluster analysis with three parameters, the characteristics of vertical temperature profiles were defined for each region.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.169-186
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• 2018

The social influence of the elderly population will accelerate in a rapidly aging society. The purpose of this study is to establish a methodology for extracting vulnerable districts of the welfare of the aged through machine learning(ML), artificial neural network(ANN) and geospatial analysis. In order to establish the direction of analysis, this progressed after an interview with volunteers who over 65-year old people, public officer and the manager of the aged welfare facility. The indicators are the geographic distance capacity, elderly welfare enjoyment, officially assessed land price and mobile communication based on old people activities where 500 m vector areal unit within 15 minutes in Yongin-city, Gyeonggi-do. As a result, the prediction accuracy of 83.2% in the support vector machine(SVM) of ML using the RBF kernel algorithm was obtained in simulation. Furthermore, the correlation result(0.63) was derived from ANN using backpropagation algorithm. A geographically weighted regression(GWR) was also performed to analyze spatial autocorrelation within variables. As a result of this analysis, the coefficient of determination was 70.1%, which showed good explanatory power. Moran's I and Getis-Ord Gi coefficients are analyzed to investigate spatially outlier as well as distribution patterns. This study can be used to solve the welfare imbalance of the aged considering the local conditions of the government recently.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.295-304
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• 2020

The IPCC (Intergovernmental Panel on Climate Change) recommended the importance of preventive measures against extreme weather, and heat waves are one of the main themes for establishing preventive measures. In this study, we tried to analyze the heat vulnerable areas by considering not only spatial characteristics but also social characteristics. Energy consumption, popu lation density, normalized difference vegetation index, waterfront distance, solar radiation, and road distribution were examined as variables. Then, by selecting a suitable model, SLM (Spatial Lag Model), available variables were extracted. Then, based on the Fuzzy theory, the degree of vulnerability to heat waves was analyzed for each variable, and six variables were superimposed to finally derive the heat vulnerable area. The study site was selected as the Daegu area where the effects of the heat wave were high. In the case of vulnerable areas, it was confirmed that the existing urban areas are mainly distributed in Seogu, Namgu, and Dalseogu of Daegu, which are less affected by waterside and vegetation. It was confirmed that both spatial and social characteristics should be considered in policy support for reducing heat waves in Daegu.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.73-85
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• 2016

Systematic and efficient forestry management is required because of the long-term low profitability of timber production and forest products. In this situation, non-timber forest products can be the solution to secure stable sources of income for workers in the forestry field. However, the existing studies for non-timber forest products focus on effective production and economic analysis and provide plans for increasing the income and improving the marketing system. Therefore, this research intends to analyze the spatial distribution as well as quantitative concentration of non-timber forest production. To achieve this goal, this study examined the regional concentration and dispersion of non-timber forest production in 2001, 2007, and 2014 using the coefficient of localization(CL) and location quotient(LQ) and investigated the change in spatial distribution using spatial statistics. The production of chestnuts generally showed a concentrated pattern in 2014 based on the outputs of the CL and LQ, but the result of spatial autocorrelation indicated a decrease in the spatial concentration. In addition, astringent persimmon showed more concentration from the output of CL than oak mushroom, but Moran's I suggests the opposite. Therefore, it is necessary to examine the spatial distribution to understand and improve the marketing system and intensify the production of forest products.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.761-771
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• 2016

The GloSea5 (Global Seasonal forecasting system version 5) is provided and operated by the KMA (Korea Meteorological Administration). GloSea5 provides Forecast (FCST) and Hindcast (HCST) data and its horizontal resolution is about 60km ($0.83^{\circ}{\times}0.56^{\circ}$) in the mid-latitudes. In order to use this data in watershed-scale water management, GloSea5 needs spatial-temporal downscaling. As such, statistical downscaling was used to correct for systematic biases of variables and to improve data reliability. HCST data is provided in ensemble format, and the highest statistical correlation ($R^2=0.60$, RMSE = 88.92, NSE = 0.57) of ensemble precipitation was reported for the Yongdam Dam watershed on the #6 grid. Additionally, the original GloSea5 (600.1 mm) showed the greatest difference (-26.5%) compared to observations (816.1 mm) during the summer flood season. However, downscaled GloSea5 was shown to have only a -3.1% error rate. Most of the underestimated results corresponded to precipitation levels during the flood season and the downscaled GloSea5 showed important results of restoration in precipitation levels. Per the analysis results of spatial autocorrelation using seasonal Moran's I, the spatial distribution was shown to be statistically significant. These results can improve the uncertainty of original GloSea5 and substantiate its spatial-temporal accuracy and validity. The spatial-temporal reproducibility assessment will play a very important role as basic data for watershed-scale water management.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.68-79
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• 2021

The recent occurrence of vacant houses in urban areas is a remarkable social problem. One of the physical declines, the occurrence of vacant houses, accelerates various social and economic declines, such as a decline in population and a slump in the commercial district. Vacant houses have regional characteristics and spatial influence, and it is necessary to approach them locally in order to grasp the exact status of vacant houses. Therefore, in this study, the effect of urban decline on the occurrence of vacant homes was examined by region using global Moran's I and Geographic Weighted Regression(GWR) model. As a result of the analysis, there were spatial autocorrelation and heterogeneity in the occurrence of vacant houses in each eup·myeon·dong, Busan metropolitan city. In addition, there is a difference in the influence of each variable of urban decline on the occurrence of vacant houses, and even the same variable of urban decline has different effects on the occurrence of vacant houses in different regions. Therefore, it is expected that a more efficient vacant home management plan can be presented if the GWR model is used to analyze the coefficient values differentiated by region and categorize the occurrence of vacant houses.

• 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.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.500-509
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• 2003

A land-speculation is to occur on a space. A purpose of this study interprets land speculation in a viewpoint of spatial, and to carry out effective decision-making about areas that land-speculation can be arise At the time of this, the focus of spatial interpretation Is recognition of a spatial continuity and consideration of a spatial association. In this study, I used fuzzy sets in order to recognize spatial continuity and. therefore a value in 0-1 was granted all area. And in order to consider spatial associations. carried out a local spatial association (Local Moran's I). Also. I introduced the spatial expert support systems (SESS) one of the computer-based decision support systems to dr efficient decision-making about a land-speculation in an object area. After that, as a case study I carried out decision-making about land-speculation's occurrence in the Seoul-Kyeonggi (2/4 quarter in 2001)

• Journal of Gifted/Talented Education
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• v.25 no.5
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• pp.711-729
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• 2015

The purposes of this study are to derive the regions in Seoul that lack gifted education units by analyzing the spatial distribution of the units and to investigate the factors related to the unit locations. The gifted education units are divided into the three following types: the first type is a gifted class at a school, the second type is a gifted education center at a provincial office of education, and the third type is a gifted education center at a university. The results of using a GIS-based spatial analysis were as follows. First, a buffering analysis showed that even though there were gifted educational blind spots in Jongno-gu and in parts of the outskirts of Seoul, the spatial distribution of gifted education units in Seoul seemed homogeneous because they were too small. Second, a special quotient analysis showed that there was a hub unit of gifted education in Guro-gu. Third, an analysis of local Moran's Index showed that Jung-gu was a cold spot and Songa-gu was a hot spot. Fourth, a correlation analysis investigated that the number of gifted education units had generally no statistically significant relationship with economic factors. These results will help to improve the efficiency and equity of the management of the gifted education units in Seoul that will be established or expanded in the future.