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Towards a real-time multi-phase sampling strategy optimization

  • D. D’Or

Keywords

Variogram Model Sequential Gaussian Simulation Soft Data Kriging Variance Bayesian Maximum Entropy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Christakos G (2000) Modern spatiotemporal geostatistics. Oxford University Press, New YorkGoogle Scholar
  2. Christakos G, Bogaert P, Serre ML (2002) Temporal GIS. Advanced Functions for Field-Based Applications. Springer-Verlag, New York NYGoogle Scholar
  3. Demougeot-Renard H (2002) De la reconnaissance à la réhabilitation des sols industriels pollués: Estimations géostatistiques pour une optimisation multicritère. Thèse ETHZ n°14615Google Scholar
  4. Demougeot-Renard H, de Fouquet C, Renard Ph (2004) Forecasting the number of soil samples required to reduce remediation cost uncertainty. Journal of Environmental Quality 33:1694–1702CrossRefGoogle Scholar
  5. D’Or D (2003) Spatial prediction of soil properties: the Bayesian Maximum Entropy approach. Ph.D. thesis dissertation. Université catholique de Louvain. http://edoc.bib.ucl.ac.be:81/ETD-db/collection/available/BelnUcetd-05012003-113316/Google Scholar
  6. Englund JE, Heravi N (1994) Phased sampling for soil remediation. Environmental and Ecological Statistics 1:247–263Google Scholar
  7. Van Groenigen JW, Siderius W, Stein A (1999) Constrained optimisation of soil sampling for minimisation of the kriging variance. Geoderma 87(3-4): 239–259Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • D. D’Or
    • 1
    • 2
  1. 1.FSS International R&DSombreffeBelgique
  2. 2.Département des Sciences du Milieu et de l’Aménagement du TerritoireEnvironnemétrieLouvain-la-NeuveBelgium

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