• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.23-33
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• 2011

In this study, the data that examined the chloride ion concentration of ground water wells in the west coast of Jeollabukdo applying the GIS spatial estimation method were analyzed. In particular, through the designation of a validation point among ground water wells and then the analysis of error characteristics of the chloride ion concentration by each method of IDW (Inverse Distance Weight), Spline, and Kriging Interpolation method which is proper for estimating salt water intrusion was selected. The main conclusion from this study is as follows. First, as a result of analyzing the error characteristics of various spatial estimation methods by using the data from the chloride ion concentration of 485 ground water wells, the IDW method was found to be the most appropriate for estimating chloride ion concentration by salt water intrusion. Second, analyzing the average chloride ion concentration of the targeted regions has revealed that Gunsan-si with the record of $541mg/{\ell}$ did not meet water quality standards even for industrial use. Both Gimje-si and Gochang-gun satisfied drinking water quality standards and Buan-gun with $272mg/{\ell}$ was slightly below the standards for drinking water. Third, concerning the results of analysis according to administrative districts, as the areas adjacent to the west coast such as Daemyeong-dong, Joong-dong, Jangjae-dong and Guemam-dong in Gunsan-si are found to have very high chloride ion concentration, and both Hoehyeon-myeon and Daeya-myeon bounded by the Mankeong river did not meet water quality standards even for industrial use. From these facts, it is concluded that salt water intrusion has a great effect on Gunsan-si generally.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.1-9
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• 2016

Linear interpolation is a basic sampling method for volume visualization. This method generates good images but sometimes it is inferior to our high expectation because it is encouraged to produce high quality images in the medical applications. In this paper, B spline based tri-cubic interpolation is used for the re-sampling step. The conventional B spline is an approximation method which does not cross control points so that we moved the control points and the curve crosses the original control points. In the rendering step, the empty space leaping is applicable to increase rendering speed. We have to calculate the maximum and minimum values for each block to detect empty space. The convex hull property of B spline enables the values of control points to be used as the maximum and minimum values. As a result, tri-cubic interpolated volume rendering is possible in interactive speed.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.1 s.13
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• pp.29-40
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• 1999

In vector GIS, natural linear entities (called linear entitles) are usually represented by a set of line segments. As an alternative of the line segments, curve segments can be used to represent the linear entities. The curve segments, as one-dimensional spatial objects, we generated by spline interpolation technique such as Bezier technique. In an effort to improve its accuracy in resembling the linear entities, the Bezier technique was modified generating a new technique (called New technique) (Kiyun, 1998). In this paper, validity of the New technique was tested. Test focused on answering two questions: (1) whether or not the curve segments from the New technique replace line segments so as to enhance the accuracy of representations of linear entities, and (2) whether or not the curve segments from the New technique represent the linear entities more accurately than curve segments from the Bezier technique. Answering these two questions entailed two hypothesis tests. For test data, a series of hydrologic lines on 7.5-minute USGS map series were selected. Test were done using t-test method and statistical inferences were made from the results. Test results indicated that curve segments from both the Bezier and New techniques represent the linear entities more accurately than the line segments do. In addition, curve segments from the New technique represent the linear entities more accurately than the line segments from the Bezier technique do at probability level 69% or higher.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.226-226
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• 2017

최근 국지성 집중호우 및 돌발홍수와 같은 급격한 기상변화로 인한 기상재해의 발생빈도가 증가함에 따라 고해상도의 기상레이더 강수자료를 사용한 수공학 분야의 연구가 활발하게 진행되고 있다. 레이더 강수자료를 수문분석에 활용하는 목적은 레이더 강수량이 제공하는 공간분포를 최대한 활용하는데 있다. 기상레이더는 광범위한 영역에 대하여 시공간적으로 연속적인 관측이 가능하므로 지상 강수자료에 비하여 고해상도의 강수자료를 확보하는데 이점이 있다. 본 연구에서는 고해상도의 레이더 강수자료의 공간분포 특성을 유지하면서 지상 강수자료의 양적특성을 유지할 수 있는 조건부 합성기법을 개발하였다. 레이더 강수자료와 지상 강수자료를 조건부 합성하기 위하여 널리 활용되고 있는 Kriging, 역거리 가중법 및 Spline 보간법을 적용하였다. 조건부 합성결과는 지상 강수패턴을 현실성 있게 재현하였다. 추가적으로 미계측 지점으로 간주하여 보간법에 적용되지 않은 강수자료와 조건부 합성기법 결과에 대하여 교차검증을 수행한 결과 조건부 합성기법을 통한 강수정보는 수문분석에 직접적으로 활용될 수 있는 가능성을 확인하였다. 본 연구결과를 향후 초단기 레이더 강수예측기법과 연계하여 수문모형의 입력 자료로 활용한다면 보다 진보된 수문해석이 가능할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.381-381
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• 2018

우리나라에서는 지속적인 자연재해로 각기 다른 필요성과 목적에 따라 다양한 형태의 홍수 침수 관련 지도가 작성되어 왔다. 연구 성과로 작성된 계획 빈도 및 상위 2개 빈도의 호우피해예상도를 실측 강우와 연계하여 재난관리단계별 대응단계에 활용하기 위해 실시간 피해위험구역을 표출하고자 한다. 본 연구는 실시간으로 피해위험구역을 표출하기 위해 실측 강우와 연계된 호우피해예상도에 공간 보간 알고리즘을 적용하고자 한다. 호우피해예상도란 돌발호우나 태풍으로 인하여 홍수가 발생하면 인명 및 재산피해를 최소화하기 위해 홍수지역을 미리 예측 가능하도록 제작된 지도이다. 지형자료(DEM), 하천 중심선(Stream Centerline), 하천 횡단면(Cross-Section Line), 제방고(Bank), 수문기상 자료(Hydrological Data), 조도계수(Roughness) 등을 사용하여 하천법 제 21조와 하천법시행령 제 17조를 근거로 작성된다. 본 연구에서는 호우피해예상도에 IDW(Inverse Distance Weighted, 역거리가중법) 보간, TIN(Triangulated Irregular Network system, 불규칙삼각망) 보간, Kriging 보간 방법 적용 알고리즘을 제시하고자 하였다. 호우피해예상도에 보간 알고리즘을 적용하기 위해 보간 방법에 따른 적용사례를 분석하였으며 그 결과, 보간 알고리즘을 적용한 호우피해예상도 보간을 통하여 계획빈도 및 상위 2개 빈도 이외의 빈도(하위빈도-계획빈도, 계획빈도-상위빈도 구간)에 대한 호우피해예상도의 피해위험구역 구현 방안을 제시하였다. 호우피해예상도에 IDW, TIN, Kriging 보간 알고리즘을 적용하여 계획빈도 및 상위빈도 이외의 빈도에 대한 피해위험구역을 표출 할 수 있다. 표출된 계획빈도 및 상위빈도 이외의 빈도를 지점확률강우량-빈도에 대한 Matching table을 통하여 실측 강우와 연계 가능하다. 본 연구 결과는 추후 풍수해피해예측시스템에 활용하여 재난관리단계별 예방 및 대응 단계에 활용 할 수 있을 것으로 판단된다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.989-996
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• 2010

Statistical regression and/or interpolation models have been used for data analysis and response prediction using the results of the physical experiments and/or computer simulations in structural engineering fields. These models have been employed during the last decade to develop a variety of design methodologies. However, these models only handled responses with respect to space variables such as size and shape of structures and cannot handle time-variant dynamic responses, i.e. response varying with time. In this research, statistical space-time metamodels based on multiple response approach that can handle responses with respect to both space variables and a time variable are proposed. Regression and interpolation models such as the response surface model (RSM) and kriging model were developed for handling time-variant dynamic responses of structural engineering. We evaluate the accuracies of the responses predicted by the two statistical space-time metamodels by comparing them with the responses obtained by the physical experiments and/or computer simulations.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.77-85
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• 1996

Using a series of medical tomograms, we can reconstruct internal organs or other objects of interest and generate 3-D images. It is generally accepted that the axial resolution determined by two sequential image slices is lower than the planar resolution in one image slices. Therefore, various methods of interpolation were developed for an accurate display of reconstructed images. In this paper, a new algorithm for 3-D reconstruction of the medical images such as MRI and X-ray CT is suggested. The algorithm is shape-based and utilizes parts of the gray-level information. We extend the conventional shape-based interpolation of the binary images to the gray-scale images using the shortest distance map. Using this new algorithm, We could reduce the execution time for interpolation while keeping similar high quality of the reconstructed images with reduced execution time and is applicable to the various medical tomograms.

• Journal of the Korean GEO-environmental Society
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• v.22 no.11
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• pp.5-13
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• 2021

The interest of expecting the liquefaction damage is increasing due to the liquefaction in Pohang in 2017. Liquefaction is defined as a phenomenon that the ground can not support the superstructure due to loss of the strength of the ground. As an alternative against this, many studies are being conducted to increase the precision and to compose a liquefaction hazard map for the purpose of identifying the scale of liquefaction damage using the liquefaction potential index (LPI). In this research, in order to analyze the degree of precision with regard to spatial interpolation objects such as LPI value and geotechnical information for LPI determination, liquefaction hazard map were made for the target area. Furthermore, based on the trend of precision, probability value was analyzed using probability maps prepared through qualitative characteristics. Based on the analysis results, the precision of the liquefaction hazard map setting the spatial interpolation object as geotechnical information is higher than that as LPI value. Furthermore, the precision of the liquefaction hazard map does not affect the distribution of the probability value.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.337-345
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• 2022

For data such as rainfall and soil moisture, it is important to obtain the values of all points required as geostatistical data. Spatial interpolation is generally performed in this process, and commercial software such as ArcGIS is often used. However, commercial software has fatal drawbacks due to its high expertise and cost. In this study, R, an open source-based environment with ArcGIS, a commercial software, was used to compare the differences according to the processing environment when performing spatial interpolation. The data for spatial interpolation was weather forecast data calculated through Land-Atmosphere Modeling Package (LAMP)-WRF model, and soil moisture data calculated for each cumulative rainfall scenario. There was no difference in the output value in the two environments, but there was a difference in user interface and calculation time. The results of spatial interpolation work in the test bed showed that the average time required for R was 5 hours and 1 minute, and for ArcGIS, the average time required was 4 hours and 40 minutes, respectively, showing a difference of 7.5%. The results of this study are meaningful in that researchers can derive the same results in a commercial software environment and an open source-based environment, and can choose according to the researcher's environment and level.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.3
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• pp.147-163
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• 2013

The purpose of this study is to compare precipitation distributions in precipitation data sets over South Korea produced by three interpolation methods. The differences of precipitation caused by interpolation methods is an important information when the interpolated precipitation data sets were used in researches such as ecological and hydrological modeling as well as regional climate impact studies. In this study, the precipitation data sets were produced by IDW(Inverse Distance Weighting) and Cokriging in this study and the PRISM(Precipitation-elevation Regressions on Independent Slopes Model) data set obtained from Climate Change Information Center of Korea. The spatial resolution of the precipitation data is 1km. As a result, there was a great precipitation difference caused by interpolation methods in data of mountainous watersheds in general. Especially the difference of monthly precipitation was 10~20% or more in the mountainous watersheds near the Military Demarcation Line dividing North and South Korea, Mt. Sobaik, Mt. Worak, Mt. Deogyu, Mt. Jiri and Taeback Mountain Range. It means that a final result of a research can be affected by adopted interpolation method when an interpolated precipitation data set is used in the research for the these study sites.