Table of Contents Author Guidelines Submit a Manuscript
Journal of Engineering
Volume 2013 (2013), Article ID 960105, 10 pages
Research Article

The Importance of the Model Choice for Experimental Semivariogram Modeling and Its Consequence in Evaluation Process

1Department of Social Science, University of Cagliari, 09123 Sardinia, Italy
2Department of Civil and Environmental Engineering and Architecture, University of Cagliari, 09123 Sardinia, Italy

Received 8 January 2013; Revised 14 June 2013; Accepted 24 July 2013

Academic Editor: Sergio Nardini

Copyright © 2013 Alessandro Mazzella and Antonio Mazzella. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. G. Matheron, “Principles of geostatistics,” Economic Geology, vol. 58, pp. 1246–1266, 1963. View at Google Scholar
  2. G. Matheron, Traité de Géostatistique Appliquée, Editions Technip, Paris, France, 1963.
  3. D. G. Krige, “A statistical approach to some basic mine valuation problems on the Witwatersrand,” Journal of the Chemical, Metallurgical and Mining Society of South Africa, vol. 52, no. 6, pp. 119–139, 1951. View at Google Scholar
  4. D. G. Krige, “Geostatistics and the definition of uncertainty,” Transactions of the Institution of Mining & Metallurgy A, vol. 93, pp. A41–A47, 1984. View at Google Scholar · View at Scopus
  5. H. S. Sichel, “The estimation of means and associated confidence limits for small samples from lognormal populations,” in Proceedings of the Symposium on Mathematical Statistics Computer Applications in Ore Valuation, pp. 106–123, South African Institute of Mining and Metallurgy, 1966.
  6. M. Bertil, “Spatial Variation: stochastic models and their application to some problems in forest surveys and other sampling investigations,” 1960, Stockholm, Sweden, (OCoLC) 610607424, 1960.
  7. L. S. Gandin, “Complex quality control of meteorological observations,” Monthly Weather Review, vol. 116, no. 5, pp. 1137–1156, 1988. View at Google Scholar · View at Scopus
  8. G. Matheron, Les Variables Régionalisées et Leur Estimation: Une Application de la Théorie des Fonctions Aléatoires aux Sciences de la Nature, Masson, Paris, France, 1965.
  9. J. R. Carr and K. Mela, “Visual basic programs for one, two or three-dimensional geostatistical analysis,” Computers and Geosciences, vol. 24, no. 6, pp. 531–536, 1998. View at Publisher · View at Google Scholar · View at Scopus
  10. A. Mazzella, S. Pretti, and R. Valera, “Valutazione dei giacimenti e geostatistica. Risultati e prospettive,” Industria Mineraria, no. 6, pp. 23–27, 1984. View at Google Scholar
  11. A. Mazzella, A. Mazzella, and P. Valera, “Kriging Assistant: an innovative andautomatic procedure for geostatistical analysis of environmental data,” in Proceedings of the European Congress on Regional Geoscientific Cartography and Information Systems, vol. 1, pp. 85–88, 2009.
  12. A. Mazzella and A. Mazzella, “Kriging Assistant: a geostatistical analysis and evaluation tool,” in Proceedings of GeoEnvironmental Engineering and Geotechnics, GeoShangai 2010 International Conference, pp. 188–193, American Society of Civils Engineers, Shanghai, China, 2010. View at Publisher · View at Google Scholar
  13. C. Deutsch and A. Journel, Geostatistical Software Library and USer's Guide, Oxford University Press, 1992.
  14. E. J. Englund and A. R. Sparks, Geo-EAS (Geostatistical Environmental Assessment Software) USer's Guide, U.S. Environmental Protection Agency, Environmental Monitoring Systems Laboratory, 1989.