• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.60-74
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• 2007

For quantitative analysis of spatio-temporal distribution pattern on marine environment, spatial autocorrelation statistics on the both global and local aspects was applied to the observed data obtained from Gwangyang Bay in South Sea of Korea. Global indexes such as Moran's I and General G were used for understanding environmental distribution pattern in the whole study area. LISAs (local indicators of spatial association) such as Moran's I ($I_i$) and $G_i{^*}$ were considered to find similarity between a target feature and its neighborhood features and to detect hot spot and/or cold spot. Additionally, the significance test on clustered patterns by Z-scores was carried out. Statistical results showed variations of spatial patterns quantitatively in the whole year. Then all of general water quality, nutrients, chlorophyll-a and phytoplankton had strong clustered pattern in summer. When global indexes showed strong clustered pattern, the front region with a negative $I_i$ which means a strong spatial variation was observed. Also, when global indexes showed random pattern, hot spot and/or cold spot were/was found in the small local region with a local index $G_i{^*}$. Therefore, global indexes were useful for observing the strength and time series variations of clustered patterns in the whole study area, and local indexes were useful for tracing the location of hot spot and/or cold spot. Quantification of both spatial distribution pattern and clustering characteristics may play an important role to understand marine environment in depth and to find the reasons for spatial pattern.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.115-127
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• 2018

This study aims to propose management strategies of ventilation paths for improving urban thermal environments. For this purpose, Gimhae-si in Gyeongsangnamdo was selected as a study area. We analyzed hot spots and cool spots in Gimhae by using Landsat 8 satellite image data and spatial statistical analysis, and finally derived the vulnerable areas to thermal environment. In addition, the characteristics of ventilation paths including wind direction and wind speed were analyzed by using data of the wind resource map provided by Korea Meteorological Administration. As a result, it was found that a lot of hot spots were similar to those with weak wind such as Jinyoung-eup, Jillye-myeon, Juchon-myeon and the downtown area. Based on the analysis, management strategies of ventilation paths in Gimhye were presented as follows. Jinyoung-eup and Jillye-myeon with hot spot areas and week wind areas have a strong possibility that hot spot areas will be extended and strengthened, because industrial areas are being built. Hence, climate-friendly urban and architectural plans considering ventilation paths is required in these areas. In Juchon-myeon, where industrial complexes and agricultural complexes are located, climate-friendly plans are also required because high-rise apartment complexes and an urban development zone are planned, which may induce worse thermal environment in the future. It is expected that a planning of securing and enlarging ventilation paths will be established for climate-friendly urban management. and further the results will be utilized in urban renewal and environmental planning as well as urban basic plans. In addition, we expect that the results can be applied as basic data for climate change adaptation plan and the evaluation system for climate-friendly urban development of Gimhye.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.39-53
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• 2014

The Korean population is aging rapidly and a disproportionate share of older people(aged 65 and older) lives in rural areas. The rural population is aging more rapidly than the population in urban area. However, the majority of studies on aging population focuses on an urban area rather than a rural area. Rural areas have been alienated from the priority of the national policy. For these reasons, this study is to show the level of population aging and to analyze the spatial spillover patterns of aging population in rural areas for the establishment of localized policy on population aging. The main findings of this study can be summarized as follows. First, the level of population aging varies in different localities such as socio-economic and locational characteristics. Secondly, there are distinct differences between hot spot region(clustering of high aging index) and cold spot region(clustering of low aging index) in spatio-temporal spillover patterns. This study intends to suggest an useful information to establish the area-specific policy on aging population through the results of analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.100-109
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• 2022

Large-scale urban concentration of population and vehicles due to economic growth in Korea has been causing serious urban transport problems. Although the collection of congestion pricing has been evaluated as the most effective transportation policy to alleviate traffic demand, its effectiveness is very limited as it was just executed around congested points or along main arterial roads. This study derived dynamic congestion zones with the average travel speed of 206 traffic analysis zones in Busan Metropolitan City to propose a dynamic congestion pricing collection system by employing Space-Time Cube Analysis and Emerging Hot Spot Analysis. As a result, dynamic hot spots were formed from 7h to 24h and particularly, traffic congestion was severely deteriorated from 18h to 20h around Seomyeon and Gwangbok-dong. Therefore, it is expected that the effect of dynamic congestion pricing will be maximized in managing traffic demand in the city center.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.100-118
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• 2015

This study established a land-cover classification method on objects using satellite images, and figured out distributional patterns of land cover according to categories through spatial statistics techniques. Object-based classification generated each land cover classification map by spectral information, texture information, and the combination of the two. Through assessment of accuracy, we selected optimum land cover classification map. Also, to figure out spatial distribution pattern of land cover according to categories, we analyzed hot spots and quantified them. Optimal weight for an object-based classification has been selected as the Scale 52, Shape 0.4, Color 0.6, Compactness 0.5, Smoothness 0.5. In case of using the combination of spectral information and texture information, the land cover classification map showed the best overall classification accuracy. Particularly in case of dry fields, protected cultivation, and bare lands, the accuracy has increased about 12 percent more than when we used only spectral information. Forest, paddy fields, transportation facilities, grasslands, dry fields, bare lands, buildings, water and protected cultivation in order of the higher area ratio of DMZ according to categories. Particularly, dry field sand transportation facilities in Yanggu occurred mainly in north areas of the civilian control line. dry fields in Cheorwon, forest and transportation facilities in Inje fulfilled actively in south areas of the civilian control line. In case of distributional patterns according to categories, hot spot of paddy fields, dry fields and protected cultivation, which is related to agriculture, was distributed intensively in plains of Yanggu and in basin areas of Cheorwon. Hot spot areas of bare lands, waters, buildings and roads have similar distribution patterns with hot spot areas related to agriculture, while hot spot areas of bare lands, water, buildings and roads have different distributional patterns with hot spot areas of forest and grasslands.

• Spatial Information Research
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• v.20 no.1
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• pp.81-90
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• 2012

When analyzing geographical phenomena, two properties need to be considered. One is the spatial dependence structure and the other is a variation or an uncertainty inhibited in a geographic space. Two problems are encountered due to the properties. Firstly, spatial dependence structure, which is conceptualized as spatial autocorrelation, generates heterogeneous geographic landscape in a spatial process. Secondly, generic statistics, although suitable for dealing with stochastic uncertainty, tacitly ignores location information im plicit in spatial data. GIS is a versatile tool for manipulating locational information, while spatial statistics are suitable for investigating spatial uncertainty. Therefore, integrating spatial statistics to GIS is considered as a plausible strategy for appropriately understanding geographic phenomena of interest. Geographic hot-spot analysis is a key tool for identifying abnormal locations in many domains (e.g., criminology, epidemiology, etc.) and is one of the most prominent applications by utilizing the integration strategy. The article aims at reviewing spatial statistical perspective for analyzing spatial processes in the framework of GIS by carrying out empirical analysis. Illustrated is the analysis procedure of using spatial scan statistic for detecting clusters in the framework of GIS. The empirical analysis targets for identifying spatial clusters of breast cancer incidents in Erie and Niagara counties, New York.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.161-171
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• 2018

This study set out to identify crime vulnerable areas with the GIS spatial analysis technique for the prediction of crimes. Crime vulnerable areas were extracted from the statistics of crimes with the GIS hotspot analysis technique and the inverse distance weighted(IDW) method applied to different crimes according to places and use districts. The scope of surveillance and weight were calculated for each of CPTED surveillance elements including CCTV, streetlamp, patrol division, and police substation. Maps of crime vulnerable areas were overlapped one after another to make a CPTED-based one expressed in four grades(safety, attention, warning, and risk).

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.93-103
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• 2018

The purpose of this study is to analyze the spatial cluster characteristics of fire using long-term fire data. For this, fire data which were broke out in the last 40 years were converted into GIS data and spatial analysis was performed at Gangwon-do province's minimum administrative district level. In order to grasp the spatial distribution of the fire, Moran's I, Geary's Ci and Getis-Ord's Gi*, which are methods that analyze the local indicators of spatial association(LISA), were used. By integrating the characteristics of the spatial distribution of fire by integrating the results obtained from each analysis, the advantages of the individual analysis methods were reflected in the study results. As a result of the study, hotspot areas of fire in Gangwon-do was derived out. Among the hot spot areas, some areas, where the fire frequency is higher than the adjacent areas, have been identified. The results of this study can be used as information for predicting the fire hazard area and relocating of fire-fighting facilities in the study area.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.161-173
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• 2020

This study analyzed local imbalances in the supply and demand of emergency medical services in Busan using the 119 emergency activity reports of the Busan Fire & Disaster Headquarters. The data for EMS activity reports in 2017 was converted into Jimgyegu units. The spatial distribution of the indicators representing the local imbalance of emergency demand and supply (number of reports, number of reports relative to the population, average coefficient of variation and outlier of on-site arrival time, and number of dispatches outside the jurisdiction) was analyzed using Hotspot analysis of GIS spatial statistics analysis. As a result of the analysis, the hot spot area and the cold spot area where both supply and demand of emergency services are concentrated were clearly distinguished. This means that the supply and demand of emergency services in Busan are locally unbalanced. In particular, there was a difference in the demand and supply of emergency services in the original downtown and its surrounding areas, and in the outskirts of Busan.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.358-362
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• 2011

The National Emergency Management Agency of South Korea has established a Disaster Victims Psychology Support Center. The Disaster Victims Psychology Support Center can enable victims who got psychological damage from disasters to return to their daily lives through healing activity, field visits and advice of experts. The previous Psychology Support Center System managed the information of disaster victims through an independent database. However, this paper proposes a system that is developed to identify medical institutions and mental health centers within a distance of radius, based on the potential Hot-Spot areas of disaster victims using the GIS Systems. The proposed system can efficiently support selection of appropriate institutions for disaster victims using their location and age, classification of damage, and damaged parts of the body. Also, this spatial analysis can assist to decide on a policy based on the location of disaster victims and the extent of damage. Therefore, this paper can provide the required information to support decision making based on the concentrated areas for disaster victims.