• Journal of Wetlands Research
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• v.20 no.1
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• pp.20-26
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• 2018

The purpose of this study is to construct a GIS / DB by grasping a small but ecologically valuable village wetland distribution, and to propose conservation management and wise use plan. The study area is Seocheon-gun, a typical farming village. Firstly, based on the digital topographical map (1:5,000), the Arc-GIS tool was used to identify the provisional(draft) village wetlands. In addition, for the management of village wetlands, wetlands with an area of more or less than $625m^2$ each were derived and according to ecological regions study area was classified into urban areas, inland areas and coastal areas. And finally, according to the wetland identifying indicators, the village wetlands were identified as the final village wetlands through indoor and field trips. The results of the study show that there are 570 village wetlands in Seocheon - gun province, which are 74 in urban areas, 220 in inland areas, and 276 in coastal areas. The case study for village wetland identification was conducted in one out of two urban areas (Seocheon - eup), two of four coastal areas (Biin - myeon and Seo - myeon), and three of seven inland areas (Masan - myeon, Hansan - myeon, and Sicho - myeon). The distribution of village wetlands was found mainly to be a village wetland with an area of less than $625m^2$. In addition, compared with inland areas, the discrimination rate of village wetlands in coastal areas and urban areas was relatively low, indicating that inland areas were still less disturbed, and land use in urban areas and coastal areas is changing rapidly. Especially, land with less awareness such as village wetlands is relatively easily damaged, and management strategy is urgent.

• Journal of Environmental Impact Assessment
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• v.4 no.1
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• pp.59-64
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• 1995

Environmental Impact Assesment(EIA) is composed of various procedures, such as screening, scoping, inventory survey, prediction, assessment, mitigation measure, alternative assessment, and post management. Remote sensing introduced lately begins to be applied ecosystem and land use in inventory survey and assessment of EIA. This study explains on land use classification, buffering analysis of residential area, and overlaying analysis of odor predictive data with residential area for application to EIA with remote sensing data. Residential area extracted from land use classification of remote sensing provides effectively buffering analysis of residential area in selection of landfill site with GIS. It could assess also residential effect to an offensive odor by overlaying analysis. Application methods in EIA should be enlarged to assess effectively.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.6
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• pp.39-50
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• 2014

This study was conducted to establish inventory and propose conservation strategy of 'village wetlands' in Cheonan. As results, the village wetlands are defined as such places as palustrine wetland, village embankment, agricultural reservoir or small reservoirs located in or near the village and related to everyday life or farming. Firstly 791 provisional village wetlands were identified in Cheonan by using Arc-GIS 10.1, then 104 wetlands were defined as village wetlands and listed the inventory of Cheonan Village Wetlands after being validated through their area (greater than $1,000m^2$), satellite images, Korea Land Information System, land use map, land coverage map and field survey. Finally the 49 wetlands were selected for detailed surveying, and function assessment. As the result of the wetland function assessments, 11 wetlands were found to have 'high' wetland function (conservation) 30 wetlands were 'average' (enhancement) and 8 wetlands were 'low' (restoration or enhancement). Enhancing biodiversity and ecosystem services through ecological management of wetlands in Cheonan and connecting with an ecological network were proposed.

• Asian Journal of Atmospheric Environment
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• v.2 no.1
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• pp.34-46
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• 2008

Emissions inputs for use in air quality modeling of Korea were generated with the emissions inventory data from the National Institute of Environmental Research (NIER), maintained under the Clean Air Policy Support System (CAPSS) database. Source Classification Codes (SCC) in the Korea emissions inventory were adapted to use with the U.S. EPA's Sparse Matrix Operator Kernel Emissions (SMOKE) by finding the best-matching SMOKE default SCCs for the chemical speciation and temporal allocation. A set of 19 surrogate spatial allocation factors for South Korea were developed utilizing the Multi-scale Integrated Modeling System (MIMS) Spatial Allocator and Korean GIS databases. The mobile and area source emissions data, after temporal allocation, show typical sinusoidal diurnal variations with high peaks during daytime, while point source emissions show weak diurnal variations. The model-ready emissions are speciated for the carbon bond version 4 (CB-4) chemical mechanism. Volatile organic carbon (VOC) emissions from painting related industries in area source category significantly contribute to TOL (Toluene) and XYL (Xylene) emissions. ETH (Ethylene) emissions are largely contributed from point industrial incineration facilities and various mobile sources. On the other hand, a large portion of OLE (Olefin) emissions are speciated from mobile sources in addition to those contributed by the polypropylene industry in point source. It was found that FORM (Formaldehyde) is mostly emitted from petroleum industry and heavy duty diesel vehicles. Chemical speciation of PM2.5 emissions shows that PEC (primary fine elemental carbon) and POA (primary fine organic aerosol) are the most abundant species from diesel and gasoline vehicles. To reduce uncertainties in processing the Korea emission inventory due to the mapping of Korean SCCs to those of U.S., it would be practical to develop and use domestic source profiles for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources when VOC emissions from the sources are more than 90% of the total.

• 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 The Geomorphological Association of Korea
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• v.24 no.4
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• pp.75-89
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• 2017

Sinkholes are key karst landforms that primarily evolve through the dissolution of limestone, and it posing a significant threat to roads, buildings, and other man-made structures. This study aims to analyze the area susceptible to sinkhole development using GIS and to identify potential danger area from sinkholes. Eight sinkhole related factors (slope angle, distance to caves, distance to faults, bedrock lithology, soil depth, drainage class, distance to mines, and distance to traffic routes) were constructed as spatial databases with sinkhole inventory. Based on the spatial database, sinkhole susceptibility maps were produced using nearest neighbor distance and frequency ratio models. The maps were verified with prediction rate curve and area under curve. The result indicates that the nearest neighbor distance and frequency ratio models predicted 95.3% and 94.4% of possible sinkhole locations respectively. Furthermore, to identify potential sinkhole danger area, the susceptibility map was compared with population distribution and land use map. It has been found that very highly susceptible areas are along Osipcheon and southeast southwest part of Hajang-myeon and south part of Gagok-myeon of Samcheok-si. Among those areas, it has been identified that potential sinkhole danger areas are Gyo-dong, Seongnae-dong, Jeongna-dong, Namyang-dong and Dogye-eup. These results can be useful in the aspects of land use planning and hazard prevention and management.

• Geomechanics and Engineering
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• v.37 no.2
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• pp.135-147
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• 2024

A GIS-based landslide susceptibility mapping (LSM) was carried out using frequency ratio (FR), modified frequency ratio (M-FR), analytic hierarchy process (AHP), and modified analytic hierarchy process (M-AHP) methods to identify and delineate the potential failure zones along the Halong - Vandon expressway. The thematic layers of various landslide causative factors were generated for modeling in GIS, including geology, rainfall, distance to fault, distance to road, slope, aspect, landuse, density of landslide, vertical relief, and horizontal relief. In addition, a landslide inventory along the road network was prepared using data provided by the management department during the course of construction and operation from 2017 to 2019, when many landslides were documented. The validation results showed that the M-FR method had the highest AUC value (AUC = 0.971), which was followed by the FR method with AUC = 0.961. The AUC values were 0.939 and 0.892 for the M-AHP and AHP methods, respectively. The generated LSM obtained from M-FR method classified the study area into five susceptibility classes: very low (0), low (0-1), moderate (1-2), high (2-3), and very high (3-4) classes, which could be useful for various stakeholders like planners, engineers, designers, and local public for future construction and maintenance in the study area.

• Journal of Korea Water Resources Association
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• v.39 no.1 s.162
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• pp.23-33
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• 2006

In this study, application potential of SINMAP, a GIS-based landslide hazard mapping tool, is evaluated through a case study. Through the application to the severe landslide events occurred during a heavy storm in 1991 on the Mt. Dalbong area about 78 kilometers south from Seoul, SINMAP successfully spotted most landslide sites. The effects and proper ranges of three calibration parameters of SINMAP, i.e. the soil internal friction angle, the combined cohesion of tree roots and soil, and T/R, were examined through comparison of predicted landslides with the landslide inventory data. From the findings of this study, it seems that SINMAP could be used as an effective screening tool for landslide hazard mapping especially for mountain areas with fairly steep slopes and relatively thin soil layers.

• Journal of Korean Society of Forest Science
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• v.87 no.2
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• pp.300-307
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• 1998

It is not an easy task for forest managers to make sound decisions on forest management and operations planning because of huge sets of spatial and temporal data and complex decision-making processes involved. However, as an efficient tool, GIS techniques enable them to enhance broad understandings on forest inventory and management conditions. In this study, we developed a GIS model for field use in forest management. In building the model, we have chosen MapInfo version 4.0 as the basic engine of the model. The model also includes an interface module to help forest managers use MapInfo functions easily. It handles MapInfo functions required to manage inventory data and analyze spatial distributions of forest stands. For testing field applicability of the model, we have build field data sets for a district of Chunchun National Forest. Then, we tested functions through quarrying stand attributes and constructing thematic maps. In this paper, the structures and functions of the model as well as the results of field applications are discussed.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.71-77
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• 2010

Cut Slope Management System(CSMS) is a systematic maintenance and management system designed to prevent the collapse of cut slopes located along national roads. In order to implement safe road operation system, KICT has started the inventory of cut slopes and developed a cut slope database since 2006. Cut slope database management system using GIS technology and navigation system was developed as a Information Technology application. Through the Cut Slope Navigation System(SLOPE-Navi.), the previously developed database was checked and verified. The converted cut slope inventory data and field investigation data of 28,707 cut slopes were loaded on the navigation map. We consider that the Cut Slope Navigation Management System can be useful as in-situ system, which can be systematic and effective DB management and operation to prevent cut slope collapses and establish a remedial countermeasure as mitigation concerning disasters.