title: Lessening the adverse effect of the semivariogram model selection on an interpolative survey using kriging technique.
abstract: OBJECTIVE
  Many parameters in environmental, scientific and human sciences investigations need to be interpolated. Geostatistics, with its structural analysis step, is widely used for this purpose. This precious step that evaluates data correlation and dependency is performed thanks to semivariogram. However, an incorrect choice of a semivariogram model can skew all the prediction results. The main objectives of this paper are (1) to simply illustrate the influence of the choice of an inappropriate semivariogram model and (2) to show how a best-fitted model can be selected. This may lessen the adverse effect of the semivariogram model selection on an interpolation survey using kriging technique.
  
  
  METHODS
  The influence of the semivariogram model selection is highlighted and illustrated by thematic maps drawn using four different models (Gaussian, magnetic, spherical and exponential). Then, a guideline to select the most suitable model, using mean error (ME), mean square error (MSE), root mean square error (RMSE), average standard error (ASE), and root mean square standardized error (RMSSE), is proposed.
  
  
  RESULTS
  The choice of a semivariogram model seriously influences the results of a kriging survey at both endpoints and amplitude of the range of the estimated values. However, the direction of variation of the interpolated values is independent of the semivariogram model: different semivariogram models (with the same characteristics) produce different thematic maps but, the areas of minimum and maximum values remain unchanged. Yet, the suitable model can be selected by means of ME, MSE, RMSE, ASE and RMSSE.
  
  
  CONCLUSIONS
  The present article illustrates how the use of an inappropriate semivariogram model can seriously distort the results of an evaluation, assessment or prediction survey. To avoid such an inconveniency, a methodical approach based on the computation and analysis of ME, RMSE, ASE, RMSSE and MSE is proposed.
authors.affiliation: Postgraduate School of Science, Technology and Geosciences, University of Yaounde I, P.O. Box 812, Yaounde, Cameroon.
authors.forename: Zakari
authors.initials: Z
authors.lastname: Arétouyap
authors.affiliation: Postgraduate School of Science, Technology and Geosciences, University of Yaounde I, P.O. Box 812, Yaounde, Cameroon.
authors.forename: Philippe
authors.initials: P
authors.lastname: Njandjock Nouck
authors.affiliation: Postgraduate School of Science, Technology and Geosciences, University of Yaounde I, P.O. Box 812, Yaounde, Cameroon.
authors.forename: Robert
authors.initials: R
authors.lastname: Nouayou
authors.affiliation: Postgraduate School of Science, Technology and Geosciences, University of Yaounde I, P.O. Box 812, Yaounde, Cameroon.
authors.forename: Franck Eithel
authors.initials: FE
authors.lastname: Ghomsi Kemgang
authors.affiliation: Postgraduate School of Science, Technology and Geosciences, University of Yaounde I, P.O. Box 812, Yaounde, Cameroon.
authors.forename: Axel Dorian
authors.initials: AD
authors.lastname: Piépi Toko
authors.affiliation: Applied Geophysics Division, Head Atomic Energy Commission, P.O. Box 6091, Damascus, Syria.
authors.forename: Jamal
authors.initials: J
authors.lastname: Asfahani
keywords: Interpolation; Kriging; Predictive analysis; Semivariogram; Spatial analysis; Structural analysis