• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.44-54
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• 2005

Most advanced countries in GIS field have established and managed georeferenced socioeconomic data systematically and made a great profit on various social and economic areas. In Korea, however, socioeconomic geographical information is relatively poor compared to systems related to geographical and topographical features. This is mainly due to the characteristics of the process from the construction to the utilization of socioeconomic data. That is, from the stage of data construction, socioeconomic data require solutions for frequent changes compared to data on geographical and topographical features and, because of difficulties in marking the positions of individual entities, information is built up through setting appropriate spatial units of aggregation. In the stage of data utilization, the data often need to be combined with other types of socioeconomic data due to the complexity of socioeconomic phenomena. Thus, the this study examined usability of GIS in socioeconomic fields and the spatial dimension of socioeconomic information through representative cases of GIS in developed countries and, based on the results, derived data requirements for socioeconomic GIS found in the construction and utilization of data and proposed solutions for the requirements.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.325-335
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• 2006

This paper evaluates and maps the quality of life in the Atlanta, Georgia metropolitan area in 2000. Three environmental variables from Landsat TM data, four socioeconomic variables from census data, and a hazard-related variable from toxic release inventory (TRI) database were integrated into a geographic information system (GIS) environment for the quality of life assessment. To solve the incompatibility problem in areal units among different data, the four socioeconomic variables aggregated by zonal units were spatially disaggregated into individual pixels. Principal components analysis (PCA) was employed to integrate and transform environmental, socioeconomic, and hazard-related variables into a resultant quality of life score for each pixel. Results indicate that the highest quality of life score was found around Sandy Springs, Roswell, Alphretta, and the northern parts of Fulton County along Georgia 400 whereas the lowest quality of life score was clustered around Smyma of Cobb County, the inner city of Atlanta, and Hartsfield-Jackson International Airport. The results also reveals that normalized difference vegetation index (NDVI) and relative risk from TRI facilities are two versatile indicators of environmental and socioeconomic quality of an urban area in the United States.

• Journal of Periodontal and Implant Science
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• v.46 no.3
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• pp.207-217
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• 2016

Purpose: The aim of this study is to analyze and visualize the distribution of patients visiting the periodontology department at a dental college hospital, using a geographic information system (GIS) to utilize these data in patient care and treatment planning, which may help to assess the risk and prevent periodontal diseases. Methods: Basic patient information data were obtained from Dankook University Dental Hospital, including the unit number, gender, date of birth, and address, down to the dong (neighborhood) administrative district unit, of 306,656 patients who visited the hospital between 2007 and 2014. The data of only 26,457 patients who visited the periodontology department were included in this analysis. The patient distribution was visualized using GIS. Statistical analyses including multiple regression, logistic regression, and geographically weighted regression were performed using SAS 9.3 and ArcGIS 10.1. Five factors, namely proximity, accessibility, age, gender, and socioeconomic status, were investigated as the explanatory variables of the patient distribution. Results: The visualized patient data showed a nationwide scale of the patient distribution. The mean distance from each patient's regional center to the hospital was $30.94{\pm}29.62km$ and was inversely proportional to the number of patients from the respective regions. The distance from a regional center to the adjacent toll gate had various effects depending on the local distance from the hospital. The average age of the patients was $52.41{\pm}12.97years$. Further, a majority of regions showed a male dominance. Personal income had inconsistent results between analyses. Conclusions: The distribution of patients is significantly affected by the proximity, accessibility, age, gender and socioeconomic status of patients, and the patients visiting the periodontology department travelled farther distances than those visiting the other departments. The underlying reason for this needs to be analyzed further.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.146-155
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• 2006

A handful of previous studies have attempted to integrate socioeconomic data and remotely sensed data for urban quality of life assessment with their spatial dimension in a zonal unit. However, such a zone-based approach not only has the unrealistic assumption that all attributes of a zone are uniformly spatially distributed throughout the zone, but also has resulted in serious methodological difficulties such as the modifiable areal unit problem and the incompatibility problem with environmental data. An alternative to the zone-based approach can be a pixel-based approach which gets its spatial dimension through a pixel. This paper proposes a pixel-based approach to linking remotely sensed data with socioeconomic data in GIS for urban quality of life assessment. The pixel-based approach uses dasymetric mapping and spatial interpolation to spatially disaggregate socioeconomic data and integrates remotely sensed data with spatially disaggregated socioeconomic data for the quality of life assessment. This approach was implemented and compared with a zone-based approach using a case study of Fulton County, Georgia. Results indicate that the pixel-based approach allows for the calculation of a microscale indicator in the urban quality of life assessment and facilitates efficient data integration and visualization in the assessment although it costs an intermediate step with more processing time such as the disaggregation of zonal data. The results also demonstrate that the pixel-based approach opens up the potential for the development of new database and increased analytical capabilities in urban analysis.

• Journal of Climate Change Research
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• v.9 no.3
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• pp.223-234
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• 2018

Estimation of future land cover based on climate change scenarios is an important factor in climate change impact assessment and adaptation policy. This study estimated future land cover considering Shared Socioeconomic Pathways (SSP) using Scenario Generators. Based on the storylines of SSP1-3, future population and estimated urban area were adopted for the transition matrix, which contains land cover change trends of each land cover class. In addition, limits of land cover change and proximity were applied as spatial data. According to the estimated land cover maps from SSP1-3 in 2030, 2050, and 2100, respectively, urban areas near a road were expanded, but agricultural areas and forests were gradually decreased. More drastic urban expansion was seen in SSP3 compared to SSP1 and SSP2. These trends are similar with previous research with regard to storyline, but the spatial results were different. Future land cover can be easily adjusted based on this approach, if econometric forecasts for each land cover class added. However, this requires determination of econometric forecasts for each land cover class.

• Journal of Dental Rehabilitation and Applied Science
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• v.31 no.4
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• pp.283-293
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• 2015

Purpose: The aims of this study are to analyze and to visualize distribution of patients visiting at a dental college hospital, using geographic information system (GIS). The visualized data can be utilized in patient care and treatment planning, ultimately leading to the assessment of risk evaluation and prevention of dental diseases. Materials and Methods: Patient information data was obtained from Dankook University Dental Hospital including the unit number, gender, date of birth, and address from 2007 to 2014. Patient distribution was visualized using GIS. Statistical analyses were performed using SAS 9.3 and ArcGIS 10.1. Five factors including proximity, accessibility, age, gender, and socioeconomic status were investigated as the explanatory variables of the patient distribution. Results: The visualized patient data showed a nationwide scale of the patient distribution. There was a little difference in characteristics for each department. As closer at Dankook University Dental Hospital, visitors increased. And it strongly showed that elderly patients in rural areas tend to visit more. Conclusion: The distribution of patients has been shown to be significantly affected by the proximity, accessibility, age, gender and socioeconomic status. The underlying reason remains to be further studied.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.371-374
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• 2007

For development of landslide risk assessment techniques using GIS(Geographic Information System), this study classifies the category of socioeconomic factors. The landslide quantitative risk assessment performs first prediction of flow trajectory and runout distance of debris flow over natural terrain. Based on those results, it can be analyzed the factors of socioeconomic which are directly related to the magnitude of risk due to landslide hazards. Those risk assessment results can deliver factual damage situation prediction to policy making for the landslide damage mitigation. Therefore, this study is based on feature classification of the digital map ver. 2.0 provided by the National Geographic Information Institute. The category of factors can be used as useful data in preventing landslide.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.280-285
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• 2007

Since the human civilization, people's livelihood is dependent on natural resources primarily on forest. Human dimensions such as population, poverty, agricultural expansion and infrastructure development are some of the underlying factors and their interrelated associations which could play a vital role in deforestation and forest degradation. This process is not only related to the human population but also connected to the various socioeconomic factors. This paper focuses to link the spatio-temporal extent of population, poverty incidence and forest dependency and their severity on Terai forest of Nepal. Secondary data on censuses were used. ArcGIS and descriptive statistics were also used for data analysis. Based on analysis & literature review we concluded that population, poverty and forest dependency have largely expanded over time in Terai and their interrelated associations substantively influence on deforestation. However, the direct relationship of such factors with deforestation and forest degradation found to be incompatible, complex and hard to perceive with fragmented and inconsistency censuses data. So, deforestation and forest degradation issues intertwined with socioeconomic factors need detailed analysis to comprehend where these linkages are still unravel.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.4
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• pp.359-365
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• 2006

Recently generated natural disaster of rainfall is transformed into nationwide generate form from a specific region of generated form that damages are steadily growing. such natural disaster lead to much influence such as socioeconomic, financial, physical and casualties etc, therefore model collection can be a step required establishment of systematically management foundation and offer of systematic solved plan. this study proposed to analyze and arrange pattern of disaster and systems designed plan and establishment further scientific, prompt service of disaster. with GIS technique for decision-making offer the necessary preliminary data. also, each city have orthophoto and digital elevation model that analyze real topography and situation. with establish management system in order to carry out appropriate service of disaster management and establish realistic management system. system had established that OpenGL make three dimensional illustrate scale image data and digital elevation model therefore a module of section analysis developed way to illustrate and to analyze topography and longitudinal section in screen.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.76-86
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• 2012

The purpose of this study is to investigate the environmental equity of the accessibility to public transportation services in the city of Daegu. The 2005 census data as well as bus stop and subway station datasets were integrated for building the GIS database. Public transportation service areas were then identified by a coverage method. Mann Whitney U test was used for statistically comparing the socioeconomic characteristics over different levels of access to the public transportation services. Both Dong-gu, Suseong-gu, Dalseo-gu, and Buk-gu located outside of the city had worse accessibility than others while Jung-gu, Seo-gu, and Nam-gu had better accessibility than others. There appeared no environmental inequity pattern in terms of the percentages of men, women, and teenagers over the city of Daegu whereas there existed some environmental inequity pattern in terms of the percentages of people above the age of 65 and people below poverty line. This environmental inequity pattern would be caused by some factors. Firstly, the lower income class has tended to reside in the declined or blighted areas far away from public transportation facilities since this class can not afford to pay expensive rents and land prices around the main roads with higher accessibility. Many old people belonging to the lower income class also reside in the declined or blighted areas. Secondly, there has been no law to locate bus stops and subway stations considering residents' socioeconomic characteristics and the spatial distribution of public transportation facilities has been not managed systematically by the city government. This research would shed insight on building the public transportation policy to locate bus stops and subway stations and to select the routes of buses and subways considering the spatial distribution of residents' socioeconomic characteristics.