XU Wuping, QIU Feng, XU Aiping. Automatic Method of Kriging Interpolation of Spatial Data[J]. Geomatics and Information Science of Wuhan University, 2016, 41(4): 498-502. DOI: 10.13203/j.whugis20140131
Citation: XU Wuping, QIU Feng, XU Aiping. Automatic Method of Kriging Interpolation of Spatial Data[J]. Geomatics and Information Science of Wuhan University, 2016, 41(4): 498-502. DOI: 10.13203/j.whugis20140131

Automatic Method of Kriging Interpolation of Spatial Data

Funds: The National Science and Technology Major Projects of Water Pollution Control and Governance; No.2013ZX07503-001-06; the Major Scientific and Technological Innovation Project of HuBei Province, No.2013AAA020.
More Information
  • Received Date: October 12, 2014
  • Published Date: April 04, 2016
  • Kriging interpolation is a common method applied to spatial data. Correct fitting of the variogram mode is the key to kriging interpolation. At present, experience is the guide when fitting variograms in analysis tools and development kits. An intuitional method is used to determine the parameters of a variogram and the parameters are adjusted reiteratively. These artificial operational steps obstruct the automation of kriging interpolation but also are not based on scientific theories relevant to setting parameters and option modes As a result, the predictive results are not exact. Aiming to address this problem and with the goal of automating the process, in this paper we calculate the sampling variogram and an automatic fitting algorithm for variograms is studied. Automatic kriging interpolation is realized and automatic cross validation is conducted based on the automatic fitting function in R language. The results of experiments show that a automatic method for kriging interpolation to spatial data is feasible.
  • [1]
    Zhang Renduo.The Theory and Application of Space Variogram[M]. Beijing:Science Press,2005(张仁铎.空间变异理论及应用[M].北京:科学出版社,2005)
    [2]
    Li Sha, Shu Hong, Xu Zhengquan. Interpolation of Temperature Based on Spatial-temporal Kriging[J]. Geomatics and Information Science of Wuhan University, 2012, 37(2):237-241(李莎,舒红,徐正全.利用时空Kriging进行气温插值研究[J].武汉大学学报·信息科学版, 2012, 37(2):237-241)
    [3]
    Xu Aiping, Sheng Wenshun, Shu Hong. Interpolation and Validation Based on Spatiotemporal Product-sum Model[J]. Geomatics and Information Science of Wuhan University, 2012, 37(7):766-769(徐爱萍,圣文顺,舒红.时空积和模型的数据插值与交叉验证[J].武汉大学学报·信息科学版,2012, 37(7):766-769)
    [4]
    R-Prgect.org. CRAN-Package Automap[OL]. http://cran.r-project.org/web/packages/automap/index.html
    [5]
    Li Shaohua, Lu Wentao. Automatic Fit of the Variogram[C]. Third International Conference on Information and Computing, Wuxi, China, 2010
    [6]
    Pesquer L, Cortés A, Pons X. Parallel Ordinary Kriging Interpolation Incorporating Automatic Variogram Fitting[J]. Computers & Geosciences, 2011,37(1):464-473
    [7]
    Xu Aiping, Shu Hong. Applied Spatial Data Analysis with R[M]. Beijing:Tsinghua University Press,2013(徐爱萍,舒红,译.空间数据分析与R语言实践[M].北京:清华大学出版社,2013)
    [8]
    Zheng Xingwen, Hu Hongda, Xu Jiaqi, et al. The Mixed Programming Component of Ordinary Kriging[J]. Urban Geotechnical Investigation & Surveying, 2013,6:139-142(郑兴文,胡泓达,许家琦,等. Kriging插值组件的混合编程实现[J]. 城市勘测, 2013,6:139-142)
  • Cited by

    Periodical cited type(3)

    1. 朱广彬,常晓涛,瞿庆亮,周苗. 利用卫星引力梯度确定地球重力场的张量不变方法研究. 武汉大学学报(信息科学版). 2022(03): 334-340 .
    2. 刘焕玲,文汉江,徐新禹,赵永奇,蔡剑青. GOCE实测数据反演高阶重力场模型的Torus方法. 测绘学报. 2020(08): 965-973 .
    3. 景小阳,裴婧,许航,解文博. 使用Savitzky—Golay滤波器改进的位场ISVD算法. 工程地球物理学报. 2019(04): 486-493 .

    Other cited types(3)

Catalog

    Article views (1499) PDF downloads (759) Cited by(6)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return