• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.6-11
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• 2015

In this paper, we analyzed current states and spatial characteristics of crime occurring in A city of Colombia using big data of crime. The analysis draws on the crime statistics of Colombia National Police Agency from 2013 January to September. We also investigated spatial autocorrelation of crime using global and local Moran's Index. Spatial autocorrelation analysis shows significant spatial autocorrelation in the high frequency of crime. Global Moran's I analysis indicates that there are statistically significant value of crime area. Using local Moran's Index analysis, we also implement Local Indicators of Spatial Association(LISA) map and hot spot analysis helps us identify crime distribution.

• Journal of the Korean association of regional geographers
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• v.21 no.3
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• pp.583-592
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• 2015

As the increase of an environmental disease has become a social problem after industrialization, academic interest in a spatial difference and characteristics of an environmental disease is on rise. The purpose of this study is to analyze the spatial distribution and characteristics of an environmental disease using the data provided by National Health Insurance Corporation in 2009. This research is focusing on atopic dermatitis among a variety of environmental diseases and shows the map that atopic dermatitis patients are distributed. Also, The Local Moran's I show how spatial autocorrelation of atopic dermatitis patients are distributed. First, the distribution of atopic dermatitis patients show the spatial difference. Second, 42 places including the western part of Incheon are hot spots of atopic dermatitis. Third, 39 places including Danyang are cold spot of atopic dermatitis. Forth, Jeju-si and Seogwipo-si are unusually hot spot of atopic dermatitis. These results have important implications that further research need to be done in public health geography.

• Journal of the Korean Geographical Society
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• v.48 no.1
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• pp.56-71
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• 2013

The purpose of this study is to examine the spatial distributional characteristics of industries among the Korean cities and to conduct industry classification using the findings. For this purpose, 82 cities in Korea are investigated with respect to 15 industrial sectors. In the analysis, concentration of and association between industries are recognized using both geographic and non-geographic measures. In order to measure concentration and association, locational Gini coefficient, Moran's I, correlation coefficient, and bivatiate Moran are used and 15 industrial sectors are classified based on these estimates. The findings reveal that the chemical sector shows strong geographic and non-geographic concentrations while the assembly, machinery and electronics sector only shows a strong geographic concentration. Printing and publishing, wholesale, and business services show a strong non-geographic association with other sectors. The remaining ten sectors show no explicit distribution patterns among cities. This study contributes to providing the methodology that analyzes the spatial distribution patterns of industries in a comprehensive way and is able to provide useful information in implementing industrial location policies including industrial clusters.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.1
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• pp.56-70
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• 2020

This study identifies the impact of social network service (SNS) on the spatial characteristics of retail stores locations in the hyper-connected society, which have been closely related to the everyday lives of urban residents. In particular, we focus on the changes in the spatial distribution of restaurants since the information retrieval process was added to the decision-making process of a consumer's restaurant selection. Empirically, we analyze restaurants in Seoul, Korea since the smart-phone was introduced. By applying the kernel density estimation and Moran's I index, we examine the changes in the spatial distribution pattern of restaurants during the last ten years for running, newly-open and closed restaurants as well as SNS popular ones. Finally, we develop a spatial regression model to identify geographic features affecting their locations. As the results, we identified geographical variables and online factors that influence the location of restaurants. The results of this study could provide important groundwork for food and beverage location planning and policy formulation.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.41-48
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• 2009

This study investigated the characteristics of spatial expansion/centralization and the spatial structural change of urban. The data used in analysis were urban population, employment, building floor area, and land price. The analysis was performed for the data of 1995, 2000, and 2005 during 10 years after 1995. The method of research was as follows; The movement of mean center and standard distance/standard deviation ellipse was estimated to investigate the urban growth change. The result of Moran's I analysis showed a clustered pattern, not a dispersed pattern, however; the effect was not significant. The town area requires the well-ordered urban planning such as land use. The contours map demonstrates that a monopole structure was generally transformed into a multicentralization structure. The development of mutural connection axis among central street roads was fragile.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.327-333
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• 2014

To improve thermal environments in urban area, the structural characteristic analysis of thermal environments of the certain area should be preceded to analyze and supplement its problems. With Landsat-8, we measured the centrality estimation, the distribution map, and the spatial statistical analysis of Daegu Metropolitan City in January and August, which of data applied in analyzing the structure of thermal environments following to its spatial property. The thermal infrared band of satellite images has been used to analyze the standard normal deviated scores, which extract the centrality, while the cluster map, based upon Local Local Moran's I, has composed for understanding the autocorrelation of local spatial within environment space structure. Understanding the distribution features as well as the pivot center of thermal environments with satellite images provides principle database for updating urban thermal environments' policies and plans; because those are reference materials that should have precedence over for diverse thermal environment policies.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.119-131
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• 2018

The increase of high-resolution spatial data and methodological developments in recent years has enabled a detailed analysis of individual experiences in space and over time. However, despite the increasing availability of data and technological advances, such individual-level analysis is not always possible in practice because of its computing requirements. To overcome this limitation, there has been a considerable amount of research on the use of high-performance, public cloud computing platforms for spatial analysis and simulation. The purpose of this paper is to empirically evaluate the efficiency and effectiveness of spatial analysis in cloud computing platforms. We compare the computing speed for calculating the measure of spatial autocorrelation and performing geographically weighted regression analysis between a local machine and spot instances on clouds. The results indicate that there could be significant improvements in terms of computing time when the analysis is performed parallel on clouds.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.325-336
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• 2023

In August 2022, even though flood damage occurred in the metropolitan area due to heavy rain, drought warnings were issued in Jeolla province, which indicates that the regional drought is intensified recent years. To cope with regarding intensified regional droughts, many studies have been conducted to identify spatial patterns of the occurrence of meteorological drought, however, case studies of spatial clustering for water shortage are not sufficient. In this study, using the estimations of water shortage in the Han River Basin in 2030 of the Master Plans for National Water Management, the spatial characteristics of water shortage were analyzed to identify the hotspot areas based on the Local Moran's I and Getis-Ord Gi^*, which are representative indicators of spatial clustering analysis. The spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The overall results of for three anayisis periods (S0(1967-1983), S1(1984-2000), S2(2001-2018)) indicated that the lower Imjin River (#1023) was the hotspot for water shortage, and there are moving patterns of water shortage from the east of lower Imjin River (#1023) to the west during S2 compared to S0 and S1. In addition, the Yangyang-namdaecheon (#1301) was the HL area that is adjacent to a high water shortage area and a low water shortage area, and had water shortage pattern in S2 compared to S0 and S1.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.87-97
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• 2024

This study analyzed the water shortage hotspot areas in South Korea using spatial clustering analysis for water shortage estimates in 2030 of the Master Plans for National Water Management. To identify the water shortage cluster areas, we used water shortage data from the past maximum drought (about 50-year return period) and performed spatial clustering analysis using Local Moran's I and Getis-Ord Gi*. The areas subject to spatial clusters of water shortage were selected using the cluster map, and the spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The results indicated that one cluster (lower Imjin River (#1023) and neighbor) in the Han River basin and two clusters (Daejeongcheon (#2403) and neighbor, Gahwacheon (#2501) and neighbor) in the Nakdong River basin were found to be the hotspot for water shortage, whereas one cluster (lower Namhan River (#1007) and neighbor) in the Han River Basin and one cluster (Byeongseongcheon (#2006) and neighbor) in the Nakdong River basin were found to be the HL area, which means the specific area have high water shortage and neighbor have low water shortage. When analyzing spatial clustering by standard watershed unit, the entire spatial clustering area satisfied 100% of the statistical criteria leading to statistically significant results. The overall results indicated that spatial clustering analysis performed using standard watersheds can resolve the variable spatial unit problem to some extent, which results in the relatively increased accuracy of spatial analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.1
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• pp.29-37
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• 2011

The purpose of this research is to measure Quality of Life indices using Factor Analysis and Principle Component Analysis and to analyze the spatial patterns of Quality of life distribution in the Seoul Metropolitan Area in terms of spatial association using spatial statistics and spatial exploratory technique. In order to check the degree of clustering, this study used spatial autocorrelation indices, global Moran's I index. In addition, local scale analysis was conducted using Moran Scatterplot and Local Moran's I to identify the spatial association pattern and the high Quality of life. The analysis based on global statics showed that, in the Seoul Metropolitan Area, QoL Indices had been distributed with positive spatial association. According to the local spatial statistics, the general tendency of clustering H-H clusters which were mainly concentrated on the Seoul, L-H clusters were concentrated on the Kyunggi-Do and L-L Clusters showed the regional extent of lagging behind. However, in case of H-H, L-H Clusters they had been spread out in the Newtown as population increase.