• Title/Summary/Keyword: Data Kriging

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Spatial Distribution of the Physicochemical Characteristics of Spring Waters in Mt. Geumjung (금정산 용천수의 물리화학적 성질의 공간적 분포 특성)

  • 김문수;함세영;김광성;김성이;성익환;이병대
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 2000.11a
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    • pp.262-265
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    • 2000
  • In order to estimate spatial physicochemical properties of the spring waters in the study area, spring waters at 57 sites were investigated for measuring ten items (temperature, pH, Eh, EC, TDS, DO, salinity, alkalinity, discharge rate, and surface elevation), To compare each component with one another, regression analysis was carried out. Kriging was used to estimate the spatial characteristics and continuity of data in the study area. To solve kriging equation, the semivariogram was calculated using geostatistical software GS$^{+}$(version 3.1). As a result of semivariogram analysis, the data of nine components but surface elevation could be assumed as stationary random function, and ordinary kriging method was used for making contour maps.s.

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Comparative Research of Kriging Method Using Raingauges Data and Radar Data (지상강우자료와 레이더자료를 이용한 크리깅 기법의 비교연구)

  • Jang, Hong Suk;Kang, Narae;Noh, Huiseong;Kim, Gwangseob;Kim, Hung Soo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.188-188
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    • 2015
  • 최근 기후변화와 지구온난화로 인한 돌발성 집중호우 및 홍수, 태풍의 빈도 증가는 사회 경제적으로 막대한 피해를 입히고 있다. 수자원 분야에서는 이러한 피해를 예방하고 빠른 대처를 위해 강우의 정밀한 관측뿐만 아니라 강우의 정확한 공간 분포 파악이 요구되고 있다. 그러나 일반적으로 강우의 측정 시 사용되는 지상우량계의 경우 공간적인 밀도가 낮고, 불규칙적으로 위치하고 있어 강우의 시 공간적 변화를 반영하기 어려운 한계가 있다. 이러한 문제를 보완하고자 지상강우자료와 레이더자료를 결합하여 사용하고 있다. 본 연구는 지상강우자료의 양적인 특성을 고려함과 동시에 레이더자료의 공간분포특성을 반영하는 강우장을 추정하고자 하였다. 따라서 지구통계학적 공간보간기법인 크리깅 기법을 적용하였으며, OK(Ordinary Kriging), KED(Kriging with External Drift), ColCOK(Collocated Cokriging) 기법에 의해 생성된 강우장을 비교하였다. 지상강우와의 양적인 측면을 비교하기 위해 관측소 위치에서의 실제 강우값과 추정된 강우값의 상관관계를 비교하였으며, 레이더자료의 공간분포특성과의 유사성을 확인하기 위해 각 기법에서의 베리오그램을 비교하였다.

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A Geostatistical Approach for Improved Prediction of Traffic Volume in Urban Area (공간통계기법을 이용한 도시 교통량 예측의 정확성 향상)

  • Kim, Ho-Yong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.4
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    • pp.138-147
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    • 2010
  • As inaccurate traffic volume prediction may result in inadequate transportation planning and design, traffic volume prediction based on traffic volume data is very important in spatial decision making processes such as transportation planning and operation. In order to improve the accuracy of traffic volume prediction, recent studies are using the geostatistical approach called kriging and according to their reports, the method shows high predictability compared to conventional methods. Thus, this study estimated traffic volume data for St. Louis in the State of Missouri, USA using the kriging method, and tested its accuracy by comparing the estimates with actual measurements. In addition, we suggested a new method for enhancing the accuracy of prediction by the kriging method. In the new method, we estimated traffic volume data: first, by applying anisotropy, which is a characteristic of traffic volume data appearing in determining variogram factors; and second, by performing co-kriging analysis using interstate highway, which is in a high spatial correlation with traffic volume data, as a secondary variable. According to the results of the analysis, the analysis applying anisotropy showed higher accuracy than the kriging method, and co-kriging performed on the application of anisotropy produced the most accurate estimates.

PREDICTION OF UNMEASURED PET DATA USING SPATIAL INTERPOLATION METHODS IN AGRICULTURAL REGION

  • Ju-Young;Krishinamurshy Ganeshi
    • Water Engineering Research
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    • v.5 no.3
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    • pp.123-131
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    • 2004
  • This paper describes the use of spatial interpolation for estimating seasonal crop potential evapotranspiration (PET) and irrigation water requirement in unmeasured evaporation gage stations within Edwards Aquifer, Texas using GIS. The Edwards Aquifer area has insufficient data with short observed records and rare gage stations, then, the investigation of data for determining of irrigation water requirement is difficult. This research shows that spatial interpolation techniques can be used for creating more accurate PET data in unmeasured region, because PET data are important parameter to estimate irrigation water requirement. Recently, many researchers are investigating intensively these techniques based upon mathematical and statistical theories. Especially, three techniques have well been used: Inverse Distance Weighting (IDW), spline, and kriging (simple, ordinary and universal). In conclusion, the result of this study (Table 1) shows the kriging interpolation technique is found to be the best method for prediction of unmeasured PET in Edwards aquifer, Texas.

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The Distribution Analysis of PM10 in Seoul Using Spatial Interpolation Methods (공간보간기법에 의한 서울시 미세먼지(PM10)의 분포 분석)

  • Cho, Hong-Lae;Jeong, Jong-Chul
    • Journal of Environmental Impact Assessment
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    • v.18 no.1
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    • pp.31-39
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    • 2009
  • A lot of data which are used in environment analysis of air pollution have characteristics that are distributed continuously in space. In this point, the collected data value such as precipitation, temperature, altitude, pollution density, PM10 have spatial aspect. When geostatistical data analysis are needed, acquisition of the value in every point is the best way, however, it is impossible because of the costs and time. Therefore, it is necessary to estimate the unknown values at unsampled locations based on observations. In this study, spatial interpolation method such as local trend surface model, IDW(inverse distance weighted), RBF(radial basis function), Kriging were applied to PM10 annual average concentration of Seoul in 2005 and the accuracy was evaluated. For evaluation of interpolation accuracy, range of estimated value, RMSE, average error were analyzed with observation data. The Kriging and RBF methods had the higher accuracy than others.

Development of Prediction Model for Renewable Energy Environmental Variables Based on Kriging Techniques (크리깅 기법 기반 재생에너지 환경변수 예측 모형 개발)

  • Choy, Youngdo;Baek, Jahyun;Jeon, Dong-Hoon;Park, Sang-Ho;Choi, Soonho;Kim, Yeojin;Hur, Jin
    • KEPCO Journal on Electric Power and Energy
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    • v.5 no.3
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    • pp.223-228
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    • 2019
  • In order to integrate large amounts of variable generation resources such as wind and solar reliably into power grids, accurate renewable energy forecasting is necessary. Since renewable energy generation output is heavily influenced by environmental variables, accurate forecasting of power generation requires meteorological data at the point where the plant is located. Therefore, a spatial approach is required to predict the meteorological variables at the interesting points. In this paper, we propose the meteorological variable prediction model for enhancing renewable generation output forecasting model. The proposed model is implemented by three geostatistical techniques: Ordinary kriging, Universal kriging and Co-kriging.

A Study on Performance Evaluation of Various Kriging Models for Estimating AADT (연평균 일교통량 산정을 위한 다양한 크리깅 방법의 성능 평가에 대한 연구)

  • Ha, Jung Ah;Oh, Sei-Chang;Heo, Tae-Young
    • Journal of Korean Society of Transportation
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    • v.32 no.4
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    • pp.380-388
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    • 2014
  • Annual average daily traffic(AADT) serves as important basic data in the transportation sector. AADT is used as design traffic which is the basic traffic volume in transportation planning. Despite of its importance, at most locations, AADT is estimated using short term traffic counts. An accurate AADT is calculated through permanent traffic counts at limited locations. This study dealt with estimating AADT using various models considering both the spatial correlation and time series data. Kriging models which are commonly used spatial statistics methods were applied and compared with each model. Additionally the External Universal kriging model, which includes explanatory variables, was used to assure accuracy of AADT estimation. For evaluation of various kriging methods, AADT estimation error, proposed using national highway permanent traffic count data, was analyzed and their performances were compared. The result shows the accuracy enhancement of the AADT estimation.

A Geostatistical Study for the Selection of Prospective Areas of Polymetallic Nodule Deposits (망간단괴광상의 유망광구선정을 위한 지구통계학적 연구)

  • Park, Chan Young;Chon, Hyo Taek;Kang, Jung Keuk
    • Economic and Environmental Geology
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    • v.29 no.5
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    • pp.575-587
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    • 1996
  • The purpose of this study is to develop geostatistical methods for selection of prospective areas of polymetallic nodule deposits in KODOS (Korea Deep Ocean Study) area of the North-East Pacific Ocean. In this study $110{\times}165$ grid system was used, and each node represents the center of an estimated block of $1km{\times}1km$. The ordinary kriging was applied to SeaBeam2000 data in order to evaluate the bathymetry. A structural analysis (variogram) of the bathymetry data was carried out for constructing digital terrain model (DTM) and the maximum slopes of the bathymetry were calculated by DTM data. The above method can be used to solve the problem that is resulted from the lack of theory of a change of support model for the maximum slope of the bathymetry. The ordinary kriging and the indicator kriging were used to evaluate the nodule abundance, and the different two kriging methods were compared to evaluate the accuracy for the estimation of the nodule abundance. It has been shown that indicator kriging was better estimation tool than the ordinary kriging. The overlay map is presented for the selection of potentially minable sites by combining the two indicator maps of the nodule abundance and the maximum slope of bathymetry. This overlay map could be utilized to establish follow-up survey and to investigate the potentially minable sites in the KODOS area.

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Application of Spatial Interpolation to Rainfall Data (강우자료에 대한 공간보간 기법의 적용)

  • Cho Hong-Lae;Jeong Jong-Chul
    • Spatial Information Research
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    • v.14 no.1 s.36
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    • pp.29-41
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    • 2006
  • Geostatistical data are obtained only at selected sites even though they are potentially available at any location In a continuous surface. Therefore it is necessary to estimate the unknown values at unsampled locations based on observations. In this study we compared the accuracy of 5 spatial interpolation methods: local trend surface, IDW, RBF, ordinary kriging, universal kriging. These interpolation methods were applied to annual rainfall data. As the results of validation tests, universal kriging with gaussian variogram model showed the best accuracy in comparison with other interpolation methods. In the case of kriging, the predicted values were more accurate and within a more narrow range than other methods. In contrast with kriging, local trend surface analysis, IDW and RBF showed the wide range of predicted values and abrupt changes between neighbors.

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Thermal Analysis of Heater for Anti-Icing System (방빙 시스템의 히터에 대한 열해석)

  • Kim, Minsoo;Jang, Yunseok;Lee, Seungsoo;Kang, Daeil;Jeong, Yunsoo;Kim, Sungsu;Han, Donggeon
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.47 no.8
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    • pp.541-548
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    • 2019
  • In this paper, the required amount of heat for an anti-icing system of a Flush Air Data Sensing(FADS) system is predicted. For an efficient prediction during the early stage of a design process, a handbook method is used. A program of which inputs are flight conditions is developed to predict the required amount of heat. A CFD analysis is conducted to compute the water catch efficiency which is one of the core parameters used in the handbook method. Kriging method, one of well-known regression mothods, is utilized to construct a surface contour database to evaluate impingements of droplets. To predict the trajectories of droplets, the database of a flow field around the surface is built using Kriging method as well.