• Journal of Soil and Groundwater Environment
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• v.18 no.5
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• pp.26-38
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• 2013

In this study, priority for groundwater contamination management was assessed based on regional vulnerability in Goyang-si area, Gyonggi-do, Korea using analytic hierarchy process (AHP) and geographic information system (GIS). We proposed a concept for regional vulnerability to groundwater contamination with using socio-environmental vulnerability factors, which can be classified into three properties including regional hydrogeological property, contamination property, and groundwater use property. This concept is applied to Goyang-si area. For AHP analysis, an expertise-targeted survey was conducted. Based on the survey, a total of 10 factors (criteria) and corresponding weights for regional vulnerability assessment were determined. The result shows that regional contamination property is the most weighted factor among the three property groups (hydrogeological property: contamination property: groundwater use property = 0.3: 0.4: 0.3). Then, database layers for those factors were constructed, and regional vulnerability to groundwater contamination was assessed by weighted superposition using GIS. Results show that estimated regional vulnerability score is ranged from 22.7 to 94.5. Central and western areas of Goyang-si which have groundwater tables at shallow depths and are mainly occupied by industrial and residential areas are estimated to be relatively highly vulnerable to groundwater contamination. Based on assessed regional vulnerability, we classified areas into 4 categories. Category 1 areas, which are ranked at the top 25% of vulnerability score, take about 2.8% area in Goyang-si and give a high priority for groundwater contamination management. The results can provide useful information when the groundwater management authority decide which areas should be inspected with a high priority for efficient contamination management.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.30-46
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• 2013

Using ArcGIS Model Builder, with emphasis on the importance of ecology and user friendliness, a model for site selecting tool is developed. This tool is developed by establishing standardized method for data selection and analysis with evaluation criteria using GIS. For this task, our first action was to objectively define and establish 18 elements to evaluate the potentiality of the site based on extensive literature reviews. These 18 elements reflect environmental, social/cultural and legal aspects that may influence the decision process to select the desired site. Secondly, using ArcGIS Model Builder, 18 analytical elements were made into thematic mapping which represent systematically organized graphic input to the model with automatic double check system and overlay analysis capability. Thirdly, to validate the effectiveness of the developed model, site location analysis was performed using the actual site, Buk-ku, Pohang.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.56-65
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• 2009

This study was carried out to embody monitoring system of growing environments of fruit tree with Ubiquitous Sensor Network and to analyze various fruit qualities by the tree's vigor in the apple orchard located in Poonggi-eup, Yeongju-shi, Gyeongsangbukdo, Korea. The tree's vigor of apple trees was influenced to insolation, temperature, and humidity and it had influence on the weights, sugar contents and the quality(especially in mineral contents) of apples. The use of Ubiquitous Sensor Network will not only contribute to improve the quality of fruit by the offer of scientific fruit-cultivation method, but also to expand its application more and more.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.1
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• pp.1-19
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• 2002

Estimation and indication for spatial distribution of living quality and poor condition associated with land and house's access as a basic human need has been imperative questions and predicaments while it is required to boost digital economic development and consolidate social maturity. Although modern IT and sophisticated GIS/LIS technologies are used to examine spatial analysis of population location-patterns, land uses and development, and environmental degradation, etc, it still might remain immature step to figure out the causations and results of poverty in space and time. In this research, a new approach to poverty management is explicated by using 6 parameters as a major tool for assisting poverty monitoring concerning the poor who are very unpredictable in space and could be regarded as renegades in the Internet age. In addition, it expounds a new approach and conceptual idea for poverty management to notify spatial location of the digital divide when poverty reduction is closely concerned with sustainable goal of land information.

• Journal of Environmental Science International
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• v.19 no.1
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• pp.27-37
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• 2010

A system coupled the prognostic WRF mesoscale model and CALMET diagnostic model has been employed for predicting high-resolution wind field over complex coastal area. WRF has three nested grids down to from during two days from 24 August 2007 to 26 August 2007. CALMET simulation is performed using both initial meteorological field from WRF coarsest results and surface boundary condition that is Shuttle Radar Topography Mission (SRTM) 90m topography and Environmental Geographic Information System (EGIS) 30m landuse during same periods above. Four Automatic Weather System (AWS) and a Sonic Detection And Ranging (SODAR) are used to verify modeled wind fields. Horizontal wind fields in CM_100m is not only more complex but better simulated than WRF_1km results at Backwoon and Geumho in which there are shown stagnation, blocking effects and orographically driven winds. Being increased in horizontal grid spacing, CM_100m is well matched with vertically wind profile compared SODAR. This also mentions the importance of high-resolution surface boundary conditions when horizontal grid spacing is increased to produce detailed wind fields over complex terrain features.

• Journal of Environmental Health Sciences
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• v.40 no.5
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• pp.355-366
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• 2014

Objectives: This study seeks to evaluate the vulnerability assessment of the human health sector for $PM_{10}$, which is reflected in the regional characteristics and related disease mortality rates for $PM_{10}$ in Busan over the period of 2006-2010. Methods: According to the vulnerability concept suggested by the Intergovernmental Panel on Climate Change (IPCC), vulnerability to $PM_{10}$ is comprised of the categories of exposure, sensitivity, and adaptive capacity. The indexes of the exposure and sensitivity categories indicate positive effects, while the adaptive capacity index indicates a negative effect on vulnerability to $PM_{10}$. Variables of each category were standardized by the rescaling method, and each regional relative vulnerability was computed through the vulnerability index calculation formula. Results: The regions with a high exposure index are Jung-Gu (transportation region) and Saha-Gu (industrial region). Major factors determining the exposure index are the $PM_{10}$ concentration, days of $PM_{10}{\geq}50$, ${\mu}g/m^3$, and $PM_{10}$ emissions. The regions that show a high sensitivity index are urban and rural regions; these commonly have a high mortality rate for related disease and vulnerable populations. The regions that have a high adaptive capacity index are Jung-Gu, Gangseo-Gu, and Busanjin-Gu, all of which have a high level of economic/welfare/health care factors. The high-vulnerability synthesis of the exposure, sensitivity, and adaptive capacity indexes show that Dong-Gu and Seo-Gu have a risk for $PM_{10}$ potential effects and a low adaptive capacity. Conclusions: This study presents the vulnerability index to $PM_{10}$ through a relative comparison using quantitative evaluation to draw regional priorities. Therefore, it provides basic data to reflect environmental health influences in favor of an adaptive policy limiting damage to human health caused by vulnerability to $PM_{10}$.

• Economic and Environmental Geology
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• v.40 no.3 s.184
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• pp.295-306
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• 2007

In this study, we predicted areas vulnerable to ground subsidence near abandoned underground coal mine at Sam-cheok City in Korea using a probability (frequency ratio) model with Geographic Information System (GIS). To extract the factors related to ground subsidence, a spatial database was constructed from a topographical map, geo-logical map, mining tunnel map, land characteristic map, and borehole data on the study area including subsidence sites surveyed in 2000. Eight major factors were extracted from the spatial analysis and the probability analysis of the surveyed ground subsidence sites. We have calculated the decision coefficient ($R^2$) to find out the relationship between eight factors and the occurrence of ground subsidence. The frequency ratio model was applied to deter-mine each factor's relative rating, then the ratings were overlaid for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with the surveyed ground subsidence sites. The results of verification showed high accuracy of 96.05% between the predicted hazard map and the actual ground subsidence sites. Therefore, the quantitative analysis of ground subsidence near abandoned underground coal mine would be possible with a frequency ratio model and a GIS.

• Journal of Environmental Health Sciences
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• v.38 no.5
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• pp.369-379
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• 2012

Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of experience of authors were conducted to know academic background of spatial analysis, appling methods on epidemiology and asbestos exposure. Results: Spatial analysis based on spatial autocorrelation provides a variety of methods through which to conduct mapping, cluster analysis, diffusion, interpolation, and identification. Cause of disease occurrence can be investigated through spatial analysis. Appropriate methods can be applied according to contagiousness and continuity. Spatial analysis for asbestos exposure source is needed to study asbestos related diseases. Although a great amount of research has used spatial analysis to study exposure assessment and distribution of disease occurrence, these studies tend to focus on the construction of a thematic map without different forms of analysis. Recently, spatial analysis has been advanced by merging with web tools, mobile computing, statistical packages, social network analysis, and big data. Conclusions: Because the trend in spatial analysis has evolved from simple marking into a variety of forms of analyses, environmental researchers including asbestos exposure study are required to be aware of recent trends.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2003.11a
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• pp.549-555
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• 2003

For the safe management of radwaste repository, data of the site and environment have to be collected and managed systematically. Particularly, for the radwaste repository, which has to be institutionally controlled for a long period after closure, data will be collected and maintained through the monitoring programme. To meet this requirement, a new programme called "Site Information and Total Environmental data management System (SITES)" is being developed. In this study, as the first stage of GIS(Geographic Information System) development that will be embedded in SITES, the scope and function of GIS are issued. Methodology for the Selection and management of thematic maps is studied as well.d as well.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.91-102
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• 2007

To anticipate and respond to harmful algae produced in a big artificial lake like Daecheong reservoir, development of a regional analysis computer system using GIS or RS technique is needed in addition to biological and chemical research. The purpose of this study is to develop a cyanobacterial blooming prediction model to prevent harmful algae produced in Daecheong reservoir and construct an early forecasting system based on GIS. For this purpose this paper examines previous studies related to the relationship between cyanobacteria and environmental factors in Daecheong reservoir and selects precipitation and air temperature as two important environmental factors for the development of cyanobacterial blooming prediction model. Data used in this study are water quality and weather data for three water regions in Daecheong reservoir between 2000 and 2004. Based on qualitative correlation analysis between cyanobacteria and environmental factors, this paper presents a Rump model which enables us to predict cyanobacteria in water regions of Daecheong reservoir. Under this model the prediction of initial occurrence time and growth period of cyanobacteria are possible. The model is also applied to the GIS-based early forecasting system for cyanobacteria, and finally a GIS which can predict cyanobacteria produced in Daecheong reservoir and can manage the related data is developed.