Environmental and Ecological Statistics

, Volume 18, Issue 3, pp 411–426

Ordinary kriging for function-valued spatial data


  • R. Giraldo
    • Universitat Politècnica de Catalunya
    • Universidad Nacional de Colombia
  • P. Delicado
    • Universitat Politècnica de Catalunya
    • Department of MathematicsUniversity Jaume I

DOI: 10.1007/s10651-010-0143-y

Cite this article as:
Giraldo, R., Delicado, P. & Mateu, J. Environ Ecol Stat (2011) 18: 411. doi:10.1007/s10651-010-0143-y


In various scientific fields properties are represented by functions varying over space. In this paper, we present a methodology to make spatial predictions at non-data locations when the data values are functions. In particular, we propose both an estimator of the spatial correlation and a functional kriging predictor. We adapt an optimization criterion used in multivariable spatial prediction in order to estimate the kriging parameters. The curves are pre-processed by a non-parametric fitting, where the smoothing parameters are chosen by cross-validation. The approach is illustrated by analyzing real data based on soil penetration resistances.


Cross-validationFunctional dataNon-parametric curve fittingOrdinary krigingSoil penetration resistanceTrace-variogram
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© Springer Science+Business Media, LLC 2010