• Title/Summary/Keyword: geostatistics

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Applications of Geostatistics to the Quantitative Analysis of Genetic Instability in Carcinogenesis

  • Kim Hyoung-Moon
    • Communications for Statistical Applications and Methods
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    • v.13 no.1
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    • pp.167-175
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    • 2006
  • It has long been recognized that cancer is a genetic disease. To find this measures of genetic instability, stain cells with chromosome specific probes using chromosome in-situ hybridization technique is adopted. Even though in-situ hybridization technique is powerful, truncation of nuclei often results in under-representation of chromosome copies in slides due to the sectioning of tissue blocks. Because of this problem we suggest three different methods to analyze the cervical cancer data set. We observe that genetic instability is an increasing function of histology and our suggested model is the best in detecting genetic instability of tumorigenesis processes.

Analysis of the Distribution Pattern of Seawater Intrusion in Coastal Area using the Geostatistics and GIS (지구통계기법과 GIS를 이용한 연안지역 해수침투 분포 파악)

  • 최선영;고와라;윤왕중;황세호;강문경
    • Spatial Information Research
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    • v.11 no.3
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    • pp.251-260
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    • 2003
  • Distribution pattern of seawater intrusion was analyzed from the spatial distribution map of chloride using the geostatistics and CIS analyses. The chloride distribution map made by kriging(ordinary kriging and co-kriging) after exploratory spatial data analysis. Kriging provides an advanced methodology which facilitates quantification of spatial features and enables spatial interpolation. TDS, Na$^{+}$, Br$^{[-10]}$ were selected as second parameters of co-kriging which is higher value of correlation coefficients between chloride and others groundwater properties. Chloride concentration is highest in yeminchon and coastal area. And result in co-kriging was accurate than ordinary kriging.

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Characterizing Spatial Variability of a Soft Ground of Songdo by Geostatistics (지구통계학을 이용한 송도연약지반의 공간적 변화특성 분석)

  • Kim, Dong-Hee;Ko, Seong-Kwon;Park, Jong-Ik;Park, Jung-Gyu;Lee, Woo-Jin
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.10a
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    • pp.1296-1305
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    • 2008
  • In this study, the spatial distribution of depth between alluvial soil and weathered soil of Song-do new city is analyzed using geostatistics. From analysis results, the boundary depth of north-east region is deeper than that of south-west region, and average depth of north-east region is 27.14m and average depth of south-west region is 23.25m. The boundary depth is estimated by ordinary kriging and inverse distance method, and estimated results are almost similarity. So, in Song-do new city, these two method can be used to estimate the boundary depth. The ordinary kriging method is a very useful tool because the more exact analysis of spatial continuity and distribution characteristic is possible.

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Design-Parameter Computation of Subsurface Investigation Profile on Probability Method (확률론적 방법에 의한 지반조사 자료의 설계정수 산정)

  • 신은철;김종인;이준철
    • Proceedings of the Korean Geotechical Society Conference
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    • 2003.03a
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    • pp.833-840
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    • 2003
  • The stability of structure, effectiveness of design and construction are very important factors in soil-structure design. The design-parameter is based on the test through laboratory-test and field-test. There are two ways to obtain the design-parameter. One is to through test, and the other is through relative documents and references. Recently, statistics has been used to get reliable data. In this study, Kriging method as Geostatistics and the theory of Bayesian's inference are used and the design-parameters are obtained. As the result of this study to the design-parameter is reliable and information about soil condition and soil properties in design and construction is easily found.

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Geostatistical analyses and spatial distribution patterns of tundra vegetation in Council, Alaska

  • Park, Jeong Soo;Lee, Eun Ju
    • Journal of Ecology and Environment
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    • v.37 no.2
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    • pp.53-60
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    • 2014
  • The arctic tundra is an important ecosystem in terms of the organic carbon cycle and climate change, and therefore, detailed analysis of vegetation distribution patterns is required to determine their association. We used grid-sampling method and applied geostatistics to analyze spatial variability and patterns of vegetation within a two-dimensional space, and calculated the Moran's I statistics and semivariance to assess the spatial autocorrelation of vegetation. Spatially autocorrelated vegetation consisted of moss, Eriophorum vaginatum, Betula nana, and Rubus chamaemorus. Interpolation maps and cross-correlograms revealed spatial specificity of Carex aquatilis and a strong negative spatial correlation between E. vaginatum and C. aquatilis. These results suggest differences between the species in water requirements for survival in the arctic tundra. Geostatistical methods could offer valuable information for identifying the vegetation spatial distribution.

Geostatistics for Bayesian interpretation of geophysical data

  • Oh Seokhoon;Lee Duk Kee;Yang Junmo;Youn Yong-Hoon
    • 한국지구물리탐사학회:학술대회논문집
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    • 2003.11a
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    • pp.340-343
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    • 2003
  • This study presents a practical procedure for the Bayesian inversion of geophysical data by Markov chain Monte Carlo (MCMC) sampling and geostatistics. We have applied geostatistical techniques for the acquisition of prior model information, and then the MCMC method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter. This approach provides an effective way to treat Bayesian inversion of geophysical data and reduce the non-uniqueness by incorporating various prior information.

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Estimation of Distribution of the Weak Soil Layer for Using Geostatistics (지구통계학적 기법을 이용한 연약 지반 분포 추정)

  • Jeong, Jin;Jang, Won-Il
    • Journal of Advanced Marine Engineering and Technology
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    • v.35 no.8
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    • pp.1132-1140
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    • 2011
  • When the offshore wind power plant is planned to construct, it is important for the wind farm site to figure out the distribution of the weak soil layers that might cause subsidence by the impact of the external moment from the wind plant's load and an oscillating wind load. Coring test is the optimistic method to figure out weak soil layers, but this method have some problem such as condition of the in-situ or economical limitation. In order to make up for the weak points in coring test, the researches using the geostatistics methods is actually done. In this study, setting a fixed coastal area that offshore wind plants construct firstly and Estimation of distribution on the thickness of the weak soil layer through the geostatistic method is conducted. The weak soil layer is sorted by result of the Standard penetration test, geostatistic method is used to ordinary kring and sequential gaussian simulation and compared to both method's result. As a results of study, we found that both methods show similar estimations of deep weak soil layer and we could evaluate quantitatively the uncertainty of the result.

Downscaling of Thematic Maps Based on Remote Sensing Data using Multi-scale Geostatistics (다중 스케일 지구통계학을 이용한 원격탐사 자료 기반 주제도의 다운스케일링)

  • Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.26 no.1
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    • pp.29-38
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    • 2010
  • It is necessary to develop an integration model which can account for various data acquired at different measurement scales in environmental thematic mapping with high-resolution ground survey data and relatively low-resolution remote sensing data. This paper presents and applies a multi-scale geostatistical methodology for downscaling of thematic maps generated from lowresolution remote sensing data. This methodology extends a traditional ordinary kriging system to a block kriging system which can account for both ground data and remote sensing data which can be regarded as point and block data, respectively. In addition, stochastic simulation based on block kriging is also applied to describe spatial uncertainty attached to the downscaling. Two downscaling experiments including SRTM DEM and MODIS Leaf Area Index (LAI) products were carried out to illustrate the applicability of the geostatistical methodology. Through the experiments, multi-scale geostatistics based on block kriging successfully generated relatively high-resolution thematic maps with reliable accuracy. Especially, it is expected that multiple realizations generated from simulation would be effectively used as input data for investigating the effects of uncertain input data on GIS model outputs.

AN ESTIMATION METHOD FOR GROUNDWATER ELEVATION

  • Cho, Choon-Kyung;Kang, Sung-Won
    • Communications of Mathematical Education
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    • v.5
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    • pp.493-502
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    • 1997
  • An estimation method for groundwater level elevations is introduced. Using geostatistical techniques and anisotropies, experimental variograms show significant improved correlations compared with those from conventional techniques.

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