• Journal of Korean Society for Geospatial Information Science
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• v.1 no.1 s.1
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• pp.171-180
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• 1993

Concern about nonpoint source pollution associated with urban storm water has led to the development of new tools for better water quality planning. This paper presents an application of a geographic information system (GIS) for urban water quality study. The GIS was used to manage land use data for nonpoint source pollution modeling and to aggregate pollutant loadings within various types of geographic units. An empirical water quality model was used to estimate pollutant loadings based primarily on land use. A land use coverage was created by updating an old coverage through interpretation of recent photography. This land use coverage was also used to record all pollutant loadings for each land use polygon. Storm sewer maps were digitized and interpreted to create a coverage of storm sewer basins and sub-basins. By overlaying pollutant loadings with the sewer sub-basin layer, aggregated pollutant loadings for major sewer outfalls were calculated. Based on the loading information, critical areas of excessive pollutant loadings were located and the effectiveness of Best Management Practices (BMPs) to control pollutant loadings were evaluated.

• Journal of Preventive Medicine and Public Health
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• v.54 no.4
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• pp.238-244
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• 2021

Objectives: Previous pandemics have demonstrated that several demographic, geographic, and socioeconomic factors may play a role in increased infection risk. During this current coronavirus disease 2019 (COVID-19) pandemic, our aim was to examine the association of timing of lockdown at the county level and aforementioned risk factors with daily case rate (DCR) in the United States. Methods: A cross-sectional study using publicly available data was performed including Americans with COVID-19 infection as of May 24, 2020. The United States counties with >100 000 population and >50 cases per 100 000 people were included. The independent variable was the days required from the declaration of lockdown to reach the target case rate (50/100 000 cases) while the dependent (outcome) variable was the DCR per 100 000 on the day of statistical calculation (May 24, 2020) after adjusting for multiple confounding socio-demographic, geographic, and health-related factors. Each independent factor was correlated with outcome variables and assessed for collinearity with each other. Subsequently, all factors with significant association to the outcome variable were included in multiple linear regression models using stepwise method. Models with best R² value from the multiple regression were chosen. Results: The timing of mandated lockdown order had the most significant association on the DCR per 100 000 after adjusting for multiple socio-demographic, geographic and health-related factors. Additional factors with significant association with increased DCR include rate of uninsured and unemployment. Conclusions: The timing of lockdown order was significantly associated with the spread of COVID-19 at the county level in the United States.

• Health Policy and Management
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• v.29 no.2
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• pp.130-137
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• 2019

The fee-for-service system is used as the main payment system for health care providers in Korea. It has been argued that it can't reflect differences in the medical practice costs across regions because the fee schedule is calculated based on the average cost. So, some researchers and providers have disputed that there is need for adopting geographic practice cost index (GPCI) used in the United States for the Medicare program for the elderly to the fee-for-service payment system. This study performed to identify whether the difference in the practice costs among regions exists or not and to examine the feasibility of applying GPCI to Korea payment system. For this purpose, we calculated modified-GPCI and examined considerations to introduce GPCI in Korea. First we identified available data to calculate GPCI. Second, we made applicable GPCI equations to Korea payment system and computed it based on four types of regions (metropolitan, urban, suburban, and rural). We also categorize the regions based on the availability of the medical resources and the capability of utilizing them. As a result, we found that there wasn't any significant difference in the GPCI by regional types in general, but the indices of rural areas (0.91-0.98) was relatively low compared to the indices of other regions (0.96-1.07). Considering the need to use GPCI floor, the pros and cons of using GPCI, and the concern of the regional imbalance of resources, the introduction of GPCI needs to be carefully considered.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.44-58
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• 2014

In this study, a standard vector data model was developed for interoperability of river-geospatial information and for verification purpose the applicability of the standard vector model was evaluated using a model to RIMGIS vector data at Changnyeong-Hapcheon & Gangjung-Goryeong irrigation watershed. The standards from ISO and OGC were analyzed and the river geospatial data model standard was established by applying the standards. The ERD was designed based on the analysis information on data characteristics and relationship. The verification of RIMGIS vector data included points, lines and polygon to develope GDM was carried out by comparing with the data by layer. This conducting comparison of basic spatial data and attribute data to each record and spatial information vertex. The error in the process of conversion was 0 %, indicating no problem with model. Our Geospatial Data Model presented in this study provides a new and consistent format for the storage and retrieval of river geospatial data from connected database. It is designed to facilitators integrated analysis of large data sets collected by multiple institutes.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.95-106
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• 2014

In this study, the applicability of a standard vector model was evaluated using RIMGIS vector data and a portal based river-geospatial information web service system was developed using XML and JSON based data linkage between the server and the client. The RIMGIS vector data including points, lines, and polygons were converted to the Geospatial Data Model(GDM) developed in this study and were validated by layers. After the conversion, it was identified that the attribute data of a shape file remained without loss. The GeoServer GDB(GeoDataBase) that manages a DB in the portal was developed as a management module. The XML-based Geography Markup Language(GML) standards of OGC was used for accessing to and managing vector layers and encoding spatial data. The separation of data content and expression in the GML allowed the different expressions of the same data, convenient data revision and update, and enhancing the expandability. In the future, it is necessary to improve the access, exchange, and storage of river-geospatial information through the user's customized services and Internet accessibility.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.3
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• pp.31-44
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• 2000

The purpose of this study is to show how could GIS along with digital maps and census data be used for scientific urban analysis and location analysis for a proposed project. Results are summarized as follows. First. after digital maps being completed, the census tract system being adopted, and major urban data being inputted in the computer file, GIS could be used intensively for various reliable urban analysis. With graphic statistical, and overlay functions of GIS, various physical and socio-economic characteristics of urban areas could be presented for analysis in the form of thematic and datapoint maps on the computer screen. Second, the locational analysis for a proposed project is a major part in the building permit review process, which tends to become disputable and time consuming as society become pluralized. Along with various GIS functions scientific decision-making methods could be developed, and the methods could play an important role for faster and scientific location analysis. As such, GIS would play an important role for faster and reliable urban analysis and location analysis and these functions finally would play important roles to improve public services and administration of local governments.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.119-132
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• 2010

In this study, 2-dimensional inundation analysis for Taehwa watershed in Ulsan metropolitan city was conducted to analyze flow behaviors, inundation depth and inundation stage, considering the building effect. Lidar having the interval of 1 m was employed to generate topographic data with 10m interval, and building data extracted from digital map was combined with the constructed topographic data for 2-dimensional inundation analysis. A few scenarios were constructed for the analysis to provide an effective and accurate inundation analysis method through analyzing the results. The disagreement based on the areas of inundation showed over 10% between the cases with and without consideration of building effect. The maximum inundation depth without considering the effects of buildings was 0.29m higher than that with considering the building effects. On the contrary, the maximum inundation stage with consideration of building effects was 0.49m higher than that without consideration of building effects.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.15-26
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• 1999

A horticultural field database system is constructed for the intelligent farm management using GIS. The database system include both spatial and attribute data of the GIS that can be used as useful information for the farmers every year. The result of the research is summarized as follow; First, the system provides the position, attributes and spatial data of the horticultural farm through AML. Second, the user interface that composed of a basic function menu and application menu is easy to use. Third, the method which applicated overlay and analysis would be need to manage farming data in this horticultural farm and to develop a dynamic decision support system interfaced with GIS.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.