• Title/Summary/Keyword: kriging interpolation

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Determination of the Optimal Spatial Interpolation Methods for Estimating Missing Precipitation Data in Not Covered Area by Climate Change Scenario (기후변화시나리오 데이터 누락지역의 강수자료 보완을 위한 최적 공간보간기법 선정)

  • Jang, Dong Woo;Park, Hyo Seon;Choi, Jin Tak
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.14-14
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    • 2015
  • 공간보간기법은 미계측지역의 강수예측을 위해 통상적으로 사용되는 방법 중의 하나이다. 이 연구에서는 기상청에서 제공하고 있는 RCP 8.5 시나리오에 의한 남한상세 강수자료 중 지형이 복잡한 도서지역에서 제공되지 않는 데이터 누락격자에 대하여 최적의 공간보간기법을 선정하여 강수자료를 생성할 수 있도록 하였다. 적합한 보간기법을 선정하기 위해 데이터 누락지역에 대한 분석을 수행하였고, 최신 행정구역도에 맞추어 $1km{\times}1km$ 격자를 한반도 전체지역에 맞추어 생성된 격자를 사용하였다. ESRI사의 ArcGIS 프로그램을 이용하여 공간보간기법을 적용하였다. 사용된 보간법은 역거리가중치법(IDW), 정규크리깅(Ordinary Kriging), 보편크리깅(Universal Kriging), 스플라인(Spline)이며 가장 적합한 공간보간기법을 선정하기 위해 기후변화시나리오에 의한 데이터 중 해안선 주변 특정격자에서의 값을 누락시켜 공간보간기법을 통해 생성된 값과 기후변화 시나리오에 의한 값을 정량적으로 비교하였다. 공간보간기법의 적합도 평가를 위해 MAE(Mean Absolute Error), MSE(Mean Squared Error), PBIAS(Percent of BIAS), G(goodness of prediction) 분석을 수행하였고, 산점도 분석을 통해 실제값과 보간값의 오차율 평가를 병행하여 최적 공간보간기법을 결정하였다. 사용된 강수데이터는 RCP 8.5 시나리오에서 2015~2019년 중 강수가 높게 나타난 8월 자료를 이용하였다. 해안선 지역의 강수량 추정시 역거리 가중치법과 크리깅방법은 일부 지점에서 과다 추정되는 경향이 있고, 스플라인 방법이 전체적인 총 강수량이 기후변화시나리오에 의한 실제값과 유사한 것으로 나타났다. 실제값과 보간값의 교차검증을 수행한 결과 정규크리깅 기법이 가장 높은 정확도를 보였으며, 전체적으로 실제값과 유사한 범위내의 강수량이 생성되는 것으로 나타났다.

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Reconstruction of the Volcanic Lake in Hanon Volcano Using the Spatial Statistical Techniques (공간통계기법을 이용한 하논화산의 화구호 복원)

  • Choi Kwang-Hee;Yoon Kwang-Sung;Kim Jong-Wook
    • Journal of the Korean Geographical Society
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    • v.41 no.4 s.115
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    • pp.391-403
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    • 2006
  • The Hanon volcano located in the southern pan of Cheju Island, Korea has a wetland in its crater being used as a farmland. Previous researchers presumed this wetland was a maar lake in the past. Based on the seismic refraction method, the wetland sediment layer was estimated between 5 to 14 m deep, which is mostly in accordance with previous researches. However, this shows only the depths at some sites, not representing the whole spatial distribution. This study is an attempt to reconstruct the volcanic lake in Hanon crater by applying the spatial statistical techniques based on the depth information from the seismic survey and known data. The procedure of reconstruction is as follows: First, the depth information from the seismic survey and known data were collected and it was interpolated by IDW and Ordinary Kriging method. Next, with the interpolation map and the present DEM the paleo DEM was constructed. Finally, using the paleo lake level on core data, the boundary of volcanic lake was extracted from the paleo DEM. The reconstructed lake resembles a half-moon in the north of the central scoria cone. It is estimated that the lake was 5 m deep on average and 13 m deep at the deepest point. Although there are slight differences according to the interpolation techniques, it is calculated that the area of the lake was between 184,000 and $190000m^2,$ and its volume approximately $869,760m^3$. Because of the continuous deposition processes after the crater formation, the reconstructed volcanic lake would not indicate an actual lake at a specific time. Nevertheless, it offers a significant clue regarding the inner morphology and evolution of the crater.

Optimization of Soil Contamination Distribution Prediction Error using Geostatistical Technique and Interpretation of Contributory Factor Based on Machine Learning Algorithm (지구통계 기법을 이용한 토양오염 분포 예측 오차 최적화 및 머신러닝 알고리즘 기반의 영향인자 해석)

  • Hosang Han;Jangwon Suh;Yosoon Choi
    • Economic and Environmental Geology
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    • v.56 no.3
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    • pp.331-341
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    • 2023
  • When creating a soil contamination map using geostatistical techniques, there are various sources that can affect prediction errors. In this study, a grid-based soil contamination map was created from the sampling data of heavy metal concentrations in soil in abandoned mine areas using Ordinary Kriging. Five factors that were judged to affect the prediction error of the soil contamination map were selected, and the variation of the root mean squared error (RMSE) between the predicted value and the actual value was analyzed based on the Leave-one-out technique. Then, using a machine learning algorithm, derived the top three factors affecting the RMSE. As a result, it was analyzed that Variogram Model, Minimum Neighbors, and Anisotropy factors have the largest impact on RMSE in the Standard interpolation. For the variogram models, the Spherical model showed the lowest RMSE, while the Minimum Neighbors had the lowest value at 3 and then increased as the value increased. In the case of Anisotropy, it was found to be more appropriate not to consider anisotropy. In this study, through the combined use of geostatistics and machine learning, it was possible to create a highly reliable soil contamination map at the local scale, and to identify which factors have a significant impact when interpolating a small amount of soil heavy metal data.

Enhancement of Geomorphology Generation for the Front Land of Levee Using Aerial Photograph (항공영상을 연계한 하천 제외지의 지형분석 개선 기법)

  • Lee, Geun Sang;Lee, Hyun Seok;Hwang, Eui Ho;Koh, Deuk Koo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.3D
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    • pp.407-415
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    • 2008
  • This study presents the methodology to link with aerial photos for advancing the accuracy of topographic survey data that is used to calculate water volume in urban stream. First, GIS spatial interpolation technique as Inverse Distance Weight (IDW) and Kriging was applied to construct the terrain morphology to the sand-bar and grass area using cross-sectional survey data, and also validation point data was used to estimate the accuracy of created topographic data. As the result of comparison, IDW ($d^{-2}_{ij}$, 2nd square number) in Sand-bar area and Kriging Spherical model in grass area showed more efficient results in the construction of topographic data of river boundary. But the differences among interpolation methods are very slight. Image classification method, Minimum Distance Method (MDM) was applied to extract sand-bar and grass area that are located to river boundary efficiently and the elevation value of extracted layers was allocated to the water level point value. Water volume with topographic data from aerial photos shows the advanced accuracy of 13% (in sand-bar) and 12% (in grass) compared to the water volume of original terrain data. Therefore, terrain analysis method in river linking with aerial photos is efficient to the monitoring about sand-bar and grass area that are located in the downstream of Dam in flooding season, and also it can be applied to calculate water volume efficiently.

The Effect of Climate Data Applying Temperature Lapse Rate on Prediction of Potential Forest Distribution (기온감율을 적용한 기후자료가 잠재 산림분포 예측에 미치는 영향)

  • Lee, Sang-Chul;Choi, Sung-Ho;Lee, Woo-Kyun;Yoo, Seong-Jin;Byun, Jae-Gyun
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.2
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    • pp.19-27
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    • 2011
  • The objective of this study was to suggest technical approaches for preparation and down scaling of climate data used for predicting the potential forest distribution. To predict the forest distribution, we employed a Korean-specific forest distribution model, so-called the TAG(Thermal Analogy Group), and defined the PFT(Plant Functional Types) based on the HyTAG(Hydrological and Thermal Analogy Group). The climate data with 20km spatial resolution were interpolated to fit on the input data format with 1km spatial resolution. Two potential forest distribution maps were estimated using climate data constructed by kriging, one of the interpolation and down-scaling approaches, with and without lapse rate considered. Through the verification process by comparing two potential maps with the actual vegetation map, the forest distribution using the lapse rate was proven to be 38% more accurate.

A Study on the Development of a 3D Visualization Program from Geotechnical Information (지반정보로부터 3차원 가시화 프로그램 개발에 관한 연구)

  • Bong-Jun, LEE;Hong, MIN;Hoon-Joon, KOUH
    • Journal of the Korean Association of Geographic Information Studies
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    • v.25 no.4
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    • pp.49-62
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    • 2022
  • Borehole Data is geotechnical information provided so that workers can safely perform construction at the field. It creates 3D data and supports viewing as a 3D image. Currently, all Korean companies that develop programs using 3D visualization use the MVS program developed by C Tech Development Corporation. However, the MVS program is a commercial program, and it is difficult to use MVS in 3D related programs developed by Korean Companies. In this paper, we propose to develop a program that can replace MVS to generate a 3D stratum model from clustered borehole information using Python's Gempy open-source. The 3D stratum model program can creates point data for each stratum and can creates a surface for each stratum through interpolation. Then, the 3D stratum model program is completed by merging the surfaces of each stratum. It was confirmed that there was no difference when a 3D model was created and compared with the MVS program and the proposed program from the borehole data of a Goyang area.

GROUNDWATER RECHARGE ESTIMATION USING ARCGIS-CHLORIDE MASS BALANCE APPROACH

  • Lee Ju Young;Krishinamurshy Ganeshi
    • Water Engineering Research
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    • v.6 no.1
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    • pp.31-38
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    • 2005
  • Groundwater recharge is defined in an addition of water to groundwater reservoir. Recently, many people have been moving to the Edwards aquifer and urban and agricultural industry have been expending. Hydrologists and water planning managers concern about insufficient groundwater amounts and irrigation water price variability. In this paper, I focus on estimates of local recharge volumes and quantify preferential flow through GIS technique. Chloride Mass Balance (CMB) and hydrochemical components have been widely applied to recharge rate and evaluate flow paths. The CMB method is based on relationship between wet-dry chloride deposition data and Rainfall data. These data are manipulated using ArcGIS. Especially, hydrochemical concentration distribution is good index for groundwater residence times or flow paths such as $[Mg^{2+}]/[Ca^{2+}],[Cl]$ and log$([Ca^{2+}]+[Mg^{2+}])/[Na^+]$. Well information such as hydrological-hydrochemical data are imported into ArcGIS and manipulated by interpolation techniques. For each potentiometric surface and water quality, point data are converted to spatial data through each Kriging and Inverse Distance Weighted (IDW) techniques.

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Estimation of Precipitation in Ungaged Watershed using a Conditional Merging Technique Coupled with Different Interpolation Schemes (조건부 합성기법을 활용한 미계측유역의 강수 추정)

  • Kim, Tae-Jeong;Lee, Dong-Ryul;Kwon, Hyun-Han
    • 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.

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Meta-model Effects on Approximate Multi-objective Design Optimization of Vehicle Suspension Components (차량 현가 부품의 근사 다목적 설계 최적화에 대한 메타모델 영향도)

  • Song, Chang Yong;Choi, Ha-Young;Byon, Sung-Kwang
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.18 no.3
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    • pp.74-81
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    • 2019
  • Herein, we performed a comparative study on approximate multi-objective design optimization, to realize a structural design to improve the weight and vibration performances of the knuckle - a car suspension component - considering various load conditions and vibration characteristics. In the approximate multi-objective optimization process, a regression meta-model was generated using the response surfaces method (RSM), while Kriging and back-propagation neural network (BPN) methods were applied for interpolation meta-modeling. The Pareto solutions, multi-objective optimal solutions, were derived using the non-dominated sorting genetic algorithm (NSGA-II). In terms of the knuckle design considered in this study, the characteristics and influence of the meta-model on multi-objective optimization were reviewed through a comparison of the approximate optimization results with the meta-models and the actual optimization.

An Evaluation of River Discharge Estimates in a Junction with Backwater effect using Interpolated Hydraulic Performance Graph (HPG로 산정한 합류부 배수영향 구간의 유량 평가)

  • Kim, Ji-Sung;Kim, Won
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.6
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    • pp.831-838
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    • 2018
  • This paper presents a method to estimate the flow discharge in a backwater affected river junction. First, unsteady HEC-RAS model was simulated and calibrated using 2 recent real flood and then HPG (Hydraulic Performance Graph) was created by plotting the relationship between upstream and downstream stages and discharge in the reach and performing kriging interpolation. During a flood, the discharge through the reach can be estimated based on the stages at its ends and the developed HPG. These discharge data were in good agreement with the automatic discharge measurements such as ADVM. This study could provide an economical and practical method for estimating discharge in a junction with a high hysteresis of stage-discharge relationships.