• Journal of Radiation Protection and Research
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• v.30 no.4
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• pp.237-245
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• 2005

The distribution of radionuclides in soil and plants were calculated, assuming an accidental release of radionuclides from Yeonggwang Nuclear Power Plant. The results which show the concentration change with time and regions were displayed by GIS. GIS Included the commercial program, ArcView(ESRI), and a basic digital map of 1:5000 scale for 30km by 30km area around Yeonggwang Nuclear Power Plant. The target material was $^{137}Cs$ in soil around Yeonggwang area. Given denosited $^{137}Cs$ concentrations, ECOREA-II code computed the $^{137}Cs$ concentration of the soil and the plant in the area divided by 16 azimuth, 480 unit cells in total in which the concentrations also varied with time. The results were introduced into the attributed data of previously designed polygon cells in ArcView. In order to display the concentration change with time by monotonic color, the RGB value for ArcView color lamp was controlled. This display is useful for the public to understand the concentration change of radionuclide around Yeonggwang area definitely.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.187-197
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• 2008

This study is to assess the impact of future land use change on hydrology and water quality in Gyungan-cheon watershed ($255.44km^2$) using SWAT (Soil and Water Assessment Tool) model. Using the 5 past Landsat TM (1987, 1991, 1996, 2004) and $ETM^+$ (2001) satellite images, time series of land use map were prepared, and the future land uses (2030, 2060, 2090) were predicted using CA-Markov technique. The 4 years streamflow and water quality data (SS, T-N, T-P) and DEM (Digital Elevation Model), stream network, and soil information (1:25,000) were prepared. The model was calibrated for 2 years (1999 and 2000), and verified for 2 years (2001 and 2002) with averaged Nash and Sutcliffe model efficiency of 0.59 for streamflow and determination coefficient of 0.88, 0.72, 0.68 for Sediment, T-N (Total Nitrogen), T-P (Total Phosphorous) respectively. The 2030, 2060 and 2090 future prediction based on 2004 values showed that the total runoff increased 1.4%, 2.0% and 2.7% for 0.6, 0.8 and 1.1 increase of watershed averaged CN value. For the future Sediment, T-N and T-P based on 2004 values, 51.4%, 5.0% and 11.7% increase in 2030, 70.5%, 8.5% and 16.7% increase in 2060, and 74.9%, 10.9% and 19.9% increase in 2090.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.34-44
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• 2024

Recently, due to abnormal climate caused by climate change, natural disasters such as floods, landslides, and soil outflows are rapidly increasing. In Korea, more than 63% of the land is vulnerable to slope disasters due to the geographical characteristics of mountainous areas, and in particular, Quarry mines soil and rocks, so there is a high risk of landslides not only inside the workplace but also outside.Accordingly, this study built a DEM using UAV and aviation LiDAR for monitoring the quarry, conducted a time series change analysis, and proposed an optimal DEM construction method for monitoring the soil collection site. For DEM construction, UAV and LiDAR-based Point Cloud were built, and the ground was extracted using three algorithms: Aggressive Classification (AC), Conservative Classification (CC), and Standard Classification (SC). UAV and LiDAR-based DEM constructed according to the algorithm evaluated accuracy through comparison with digital map-based DEM.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.91-106
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• 2014

This study tries to cluster the 795 standard watersheds of Korea Water Resources Unit Map using multivariate statistical analysis technique. The 30 factors of watershed characteristics related to topography, stream, meteorology, soil, land cover and hydrology were selected for comprehensive analysis. From the factor analysis, 16 representative factors were selected. The significant factors in order were the pedological feature, scale and geological location and meteorological and hydrological features of the watershed. As a next step, the 73 gauged watersheds were selected for cluster analysis. They are scattered properly to the whole country and the discharge data were within a confidential level. Based on the 73 watersheds, the other ungaged watersheds were clustered by applying the 16 factors and calculating Euclidian distances. The clustering results showed that the similarity between standard watersheds within the same river basin were 87%, 69%, 41%, 52%, and 27% for Han, Nakdong, Geum, Seomjin, and Yeongsan river basins respectively.

• Journal of the Korean Geotechnical Society
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• v.28 no.4
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• pp.23-33
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• 2012

Recently, landslide disasters caused by severe rain storms and typhoons have been frequently reported. Due to the geomorphologic characteristics of Korea, considerable portion of urban area and infrastructures such as road and railway have been constructed near mountains. These infrastructures may encounter the risk of landslide and debris flow. It is important to evaluate the highly risky locations of landslide and to prepare measures for the protection of landslide in the process of construction planning. In this study, a landslide-risk prediction equation is proposed based on the statistical analysis of 423 landslide data set obtained from field surveys, disaster reports on national road, and digital maps of landslide area. Each dataset includes geomorphologic characteristics, soil properties, rainfall information, forest properties and hazard history. The comparison between the result of proposed equation and actual occurrence of landslide shows 92 percent in the accuracy of classification. Since the input for the equation can be provided within short period and low cost, and the results of equation can be easily incorporated with hazard map, the proposed equation can be effectively utilized in the analysis of landslide-risk for large mountainous area.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.667-677
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• 2020

Crop water stress can be detected based on soil moisture content, crop physiological characteristics and remote-sensing technology. The detection of crop water stress is an important issue for the accurate assessment of yield decline. The crop water stress index (CWSI) has been introduced based on the difference between leaf and air temperature. In this paper, drone-based thermal infrared image was used to map of crop water stress in water control plot (WCP) and water deficit plot (WDP) over spring chinese cabbage fields. The spatial distribution map of CWSI was in strong agreement with the abnormal growth response factors (plant height, plant diameter, and measured value by chlorophyll meter). From these results, CWSI can be used as a good method for evaluation of crop abnormal growth monitoring.

• Korean Journal of Environmental Biology
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• v.36 no.1
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• pp.21-32
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• 2018

This study was carried out to define the characteristics of the identified ground-dwelling invertebrate communities at Nari basin and Tonggumi area in Ulleungdo Island, designated as a nationally important agricultural heritage. The habitat types were divided into the following categories: crop land, forest, and ecotone, and the soil-dwelling invertebrates were collected according to habitat type. The ground-dwelling invertebrates were collected using a pitfall trap, and a self-organizing map (SOM) was applied to the invertebrates dataset to define the characteristics in invertebrates distribution. The SOM clearly classified the relevant information into four clusters, and extracted ecological information from the invertebrates dataset. The cluster II was composed of invertebrate communities which are collected in the Tonggumi area. The Tonggumi area is where mountainous areas were developed for agricultural purposes, which has geographical features commonly observed in Ulleungdo Island. It is noted that the cluster II has different characteristics as compared other clusters. The results of this study are expected to be used for the preservation of agricultural environment and maintenance of biodiversity by providing basic data, on the biotope of Ulleungdo Island designated as a nationally important agricultural heritage and information on the characteristics of the applicable ground-dwelling invertebrate communities.

• Proceedings of the KSRS Conference
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• v.2
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• pp.551-554
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• 2006

House management is very important in water resource protection in order to provide sustainable drinking water for about four millions population in northern Taiwan. House management can be a simple job that can be done without any ingredient of remote sensing or geographic information systems. Remote sensing and GIS integration for house management can provide more efficient management prescription when land use enforcement, soil and water conservation, sewage management, garbage collection, and reforestation have to be managed simultaneously. The objective of this paper was to integrate remote sensing and GIS to manage houses in a water resource protection district. More than four thousand houses have been surveyed and created as a house data base. Site map of every single house and very detail information consisting of address, ownership, date of creation, building materials, acreages floor by floor, parcel information, and types of house condition. Some houses have their photos in different directions. One house has its own card consists these information and these attributes were created into a house data base. Site maps of all houses were created with the same coordinates system as parcel maps, topographic maps, sewage maps, and city planning maps. Visual Basic.NET, Visual C#.NET have been implemented to develop computer programs for house information inquiry and maps overlay among house maps and other GIS map layers. Remote sensing techniques have been implemented to generate the background information of a single house in the past 15 years. Digital orthophoto maps at a scale of 1:5000 overlay with house site maps are very useful in determination of a house was there or not for a given year. Satellite images if their resolutions good enough are also very useful in this type of daily government operations. The developed house management systems can work with commercial GIS software such as ArcView and ArcPad. Remote sensing provided image information of a single house whether it was there or not in a given year. GIS provided overlay and inquiry functions to automatically extract attributes of a given house by ownership, address, and so on when certain house management prescriptions have to be made by government agency. File format is the key component that makes remote sensing and GIS integration smoothly. The developed house management systems are user friendly and can be modified to meet needs encountered in a single task of a government technician.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.119-131
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• 2003

Rainfall-runoff process is under the control of hydrologic parameters having temporal and spatial variety. Accordingly, it is difficult to efficiently deal them since many parameters and various information are required to perform hydrologic simulation. So the purposes of this study is to estimate the runoff volume by frequency using GIS techniques and NRCS method. The analysis of frequency rainfall is analyzed using FARD 2002 program and the result of goodness of fit test show that Log-pearson type III is suitable distribute type for the applied area. TOPAZ program used for the analysis of DEM data examining into geological characteristic. NRCS curve numbers estimated using landuse map and soil map for the estimation of effective rain fall in the basin. The storm Type II and Type III were used as the type for the application of NRCS. The result of application show that the runoff volumes above 80 years frequency in return period have similar patterns regardless of Type II and Type III. In addition, the results of comparison with runoff volumes by frequency in the report of river improvement master plan show that it have similar volumes as the relative errors for them of 80, 100 years frequency are each 7.65%, 5.33%.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.75-85
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• 2020

This study examines machine learning cross-validation to utilized create ROI for classification of land cover. The study area located in Sejong and one KOMPSAT-3A image was used in this analysis: procedure on October 28, 2019. We used four bands(Red, Green, Blue, Near infra-red) for learning cross validation process. In this study, we used K-fold method in cross validation and used SVM kernel type with cross validation result. In addition, we used 4 kernels of SVM(Linear, Polynomial, RBF, Sigmoid) for supervised classification land cover map using extracted ROI. During the cross validation process, 1,813 data extracted from 3,500 data, and the most of the building, road and grass class data were removed about 60% during cross validation process. Based on this, the supervised SVM linear technique showed the highest classification accuracy of 91.77% compared to other kernel methods. The grass' producer accuracy showed 79.43% and identified a large mis-classification in forests. Depending on the results of the study, extraction ROI using cross validation may be effective in forest, water and agriculture areas, but it is deemed necessary to improve the distinction of built-up, grass and bare-soil area.