• Journal of Korea Multimedia Society
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• v.18 no.2
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• pp.233-243
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• 2015

A hotspot is a spatial pattern that properties or events of spaces are densely revealed in a particular area. Whereas location information is easily captured with increasing use of mobile devices, so is not our emotion unless asking directly through a survey. Tweet provides a good way of analyzing such spatial sentiment, but relevant research is hard to find. Therefore, we analyzed hotspots of emotion in the twitter using spatial autocorrelation. 10,142 tweets and related GPS data were extracted. Sentiment of tweets was classified into good or bad with a support vector machine algorithm. We used Moran's I and Getis-Ord $G_i^*$ for global and local spatial autocorrelation. Some hotspots were found significant and drawn on Seoul metropolitan area map. These results were found very similar to an earlier conducted official survey of happiness index.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.29-40
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• 2021

Risk factors that threaten public safety such as crime, fire, and traffic accidents have spatial characteristics. Since each region has different dangerous environments, it is necessary to analyze the spatial pattern of risk factors for each sector such as traffic accident, fire, crime, and living safety. The purpose of this study is to analyze the spatial distribution pattern of local safety level index, which act as an index that rates the safety level of each sector (traffic accident, fire, crime, living safety, suicide, and infectious disease) for basic local governments across the nation. The following analysis tools were used to analyze the spatial autocorrelation of local safety level index : Global Moran's I, Local Moran's I, and Getis-Ord's G⁎i. The result of the analysis shows that the distribution of safety level on traffic accidents, fire, and suicide tends to be more clustered spatially compared to the safety level on crime, living safety, and infectious disease. As a result of analyzing significant spatial correlations between different regions, it was found that the Seoul metropolitan areas are relatively safe compared to other cities based on the integrated index of local safety. In addition, hot spot analysis using statistical values from Getis-Ord's G⁎i derived three hot spots(Samchuck, Cheongsong-gun, and Gimje) in which safety-vulnerable areas are clustered and 15 cold spots which are clusters of areas with high safety levels. These research findings can be used as basic data when the government is making policies to improve the safety level by identifying the spatial distribution and the spatial pattern in areas with vulnerable safety levels.

• Journal of Environmental Impact Assessment
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• v.24 no.3
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• pp.233-243
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• 2015

The ecosystem fragmentation due to transportation infrastructure causes road-kill phenomenon. When making policy for reducing road-kill it is important to select target-species in order to enhance its efficiency. However, many corridors installed in Korea have been raised issues about their effectiveness due to lack of considerations such as target-species selection, site selection, and management, etc. In this study, we are to grasp relationship between road-kill area and habitat patches and suggest that spatial location of habitat patches should be considered as one of the important factors when making policy for reducing road-kill. Habitat patches were presumed from overlying suitability index that chosen by literature review and road-kill hotspot was determined by Getis-Ord $G_i^*$ analysis. Afterwards, we performed a correlation analysis between $G_i$ Z-score and the distance from habitat patches to the roads. As a result, there is a negative correlation between two variables, It affects the $G_i^*$ Z-score going up if the habitat patches and the roads become closer.

• Journal of the Korean association of regional geographers
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• v.16 no.5
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• pp.590-609
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• 2010

The purpose of the study is to propose and evaluate Exploratory Spatial Data Analysis(ESDA) methods for examining age-specific population migration characteristics. First, population migration pyramid which is a pyramid-shaped graph designed with in-migration, out-migration, and net migration by age (or age group), was developed as a tool exploring age-specific migration propensities and structures. Second, various spatial statistics techniques based on local indicators of spatial association(LISA) such as Local Moran''s $I_i$, Getis-Ord ${G_i}^*$, and AMOEBA were suggested as ways to detect spatial dusters of age-specific net migration rate. These ESDA techniques were applied to age-specific population migration of Daegu Metropolitan City. Application results demonstrated that suggested ESDA methods can effectively detect new information and patterns such as contribution of age-specific migration propensities to population changes in a given region, relationship among different age groups, hot and cold spot of age-specific net migration rate, and similarity between age-specific spatial clusters.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.42-54
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• 2012

The main purpose of this study is to suggest the spatial statistical approach suitable for the delimitation of Busan CBD. For this purpose, Getis-Ord $G_i^*$ and both of IDW (Inverse Distance Weight) and FDB(Fixed Distance Band) were applied to delimit the CBD boundary. And then, the results of the CBD boundary were compared and verified with the methodologies of the previous studies. The result of IDW accorded with the previous study relating to the delimitation of the boundary of CBD, and the result of FDB was reflecting the characteristics of the mixed-use residential of a transition zone. As a result of the land use quotient, the mixed land use of residential and commercial was highly specialized in the boundary of FDB. These results will be able to support the understanding of urban spatial structure and the effective CBD management.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.336-341
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• 2016

The object of this study was to classify the local types in relation to regional differences using Height-DBH growth of Pinus densiflora in Korea. The regional types were clustered according to Getis-Ord's $G_i$ among Local indicators of spatial association (LISA) by characteristics of spatial distribution which were calculated the residual of sample plots by fitting Height-DBH growth model using Weibull growth equation. Accordingly, Pinus densiflora were classified 3 groups, It indicated that annual precipitation had one of the biggest impacts among the considered site and climate factors. This results can become the standard for regional management of Pinus densiflora forests.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.1-14
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• 2014

In this study, the change characteristics of urban spatial structure in Daegu were analyzed connecting with urban planning for efficient urban management. Urban development process from 1970 to 2010 in Daegu was analyzed utilizing Getis-Ord $G_i^*$ methodology, a spatial statistical method, and it was identified that Daegu was in the stage of disurbanization. However, as Daegu orients multi-nuclei city, it was difficult to explain the stage of urban development after disurbanization in 2000. Accordingly, to analyze detailed changes in spatial structure in multi-centric areas after 2000, population, land price and employment factor changes were analyzed using Bachi Measurement. According to analytical results, multi-centralization process has been continued in Daegu. Urban core area and Chilgok area showed spatial structure change into distribution process, Ansim area into concentration process, and Seongseo and Talseo area into concentration and distribution process. Therefore, urban planning considering the regional characteristics are needed for efficient urban management.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.181-195
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• 2019

This study aims to analyze the spatial context by analyzing the flow characteristics of the walking tour course and visualizing effectively using the floating population data constructed through the communication data. The floating population data refinement algorithm was developed for estimation flow population along the road and the floating population data for each walking tour courses was constructed. In order to adopt the algorithm for forming suitable for the analysis of the walking tour courses, the estimation of floating population considering the area of the road and the estimation of floating population considering the value of floating population around the road were compared. As a result, the estimation of floating population considering ambient the values of flow population was adopted, which is more appropriate to apply analysis method due to the relatively consistent data. Then, a datamining algorithm for walking tour course was constructed according to the characteristics of the floating population data, the absence of missing values. Finally, this study analyzed the flow characteristics and spatial patterns of 18 walking trails in Seoul through the floating population data according to walking tour course. To do this, the kernel density analysis and the Getis-Ord $G^*_i$ statistical hotspot analysis were applied to visualize the main characteristics of each walking tour course.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.40-51
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• 2021

The purpose of this study is to diagnose urban spatial structures using spatial modeling techniques for balanced urban development as part of sustainable urban growth management. Since urban spatial structure is an interaction of various activities, it is necessary to interpret the analysis results in conjunction with the analysis of changes in spatial structural elements. In this study, population and transportation were approached for research purposes. Population data were applied to the Getis-Ord G_i^* method, a spatial statistical technique, to analyze the concentration-decreasing region of the population. Traffic data analyzed the trend of centrality change by applying commuting traffic O-D data to Social Network Analysis techniques. The analysis showed that urban imbalance was growing, and the centrality of transportation was changing. The results of the analysis of spatial structure elements could be interpreted by linking the results of each factor to each neighborhood unit, predicting changes in urban spatial structure and suggesting directions for sustainable urban growth management.These results could also be used as a decision-making tool for various urban growth management policies introduced to cope with rapid urban development and uncontrollable development in many cities around the world.

• 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.