• DocumentCode
    538890
  • Title

    Development of Adaptive Thiessen Polygon Method for Imperfect Observation Data

  • Author

    Lei, Xiaohui ; Tian, Yu ; Wang, Xu ; Jiang, Yunzhong ; Liao, Weihong

  • Author_Institution
    China Inst. of Water Resource & Hydropower Res., Beijing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    16-17 Dec. 2010
  • Firstpage
    81
  • Lastpage
    86
  • Abstract
    The problem of the low efficiency of the existing spatial interpolation algorithm for hydro meteorological information is discussed and two fast interpolation algorithms based on the conventional Thiessen polygon method was proposed in this paper: improved Thiessen polygon method and self-adaptive Thiessen polygon method. Studies of the Luan River Basin had shown that the self-adaptive Thiessen polygon algorithms are 10-200 times more efficient than the conventional Thiessen polygon method and guarantee calculation accuracy. A comparative analysis of the factors influencing the interpolation algorithm efficiency revealed that the number of grids and stations had the greatest effect on the calculation efficiency, while the number of sub basins was a secondary factor.
  • Keywords
    computational geometry; geophysics; hydrological techniques; interpolation; meteorology; rivers; Luan River Basin; calculation accuracy; calculation efficiency; comparative analysis; conventional Thiessen polygon method; hydro meteorological information; imperfect observation data; interpolation algorithm efficiency; interpolation algorithms; self-adaptive Thiessen polygon algorithms; self-adaptive Thiessen polygon method; spatial interpolation algorithm; Accuracy; Algorithm design and analysis; Arrays; Hydroelectric power generation; Interpolation; Rivers; Water resources; algorithm efficiency; initial matrix; self-adaptive Thiessen polygon method; weight matrix;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems (GCIS), 2010 Second WRI Global Congress on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-9247-3
  • Type

    conf

  • DOI
    10.1109/GCIS.2010.178
  • Filename
    5708792