Uncertainty assessment of spatial soil information

Gerard B.M. Heuvelink, Richard Webster

Research output: Chapter in Book/Report/Conference proceedingEntry for encyclopedia/dictionaryAcademic

3 Citations (Scopus)

Abstract

Information on the soil of any region is never free of error because it is derived from imperfect measurements, imperfect models and imperfect mapping algorithms. Scientists and technologists who produce the information and those who use it cannot be certain about the true values of the soil properties and soil classes in a region, and they must acknowledge the fact. That uncertainty can best be characterized by probability distributions. Geostatistics, based on such distributions, has become fashionable in the last 30years or so for quantifying uncertainty in spatial information, and rightly so as it quantifies the uncertainty in its predictions. Uncertainty in soil information also propagates through agronomic and environmental models. It must be communicated to end users because the validity of their decisions depends on it.

Original languageEnglish
Title of host publicationEncyclopedia of Soils in the Environment, Second Edition
Subtitle of host publicationVolume 1-5
EditorsM.J. Goss, M. Oliver
PublisherElsevier
PagesV4-671-V4-683
Volume4
Edition2
ISBN (Electronic)9780128229743
ISBN (Print)9780323951333
DOIs
Publication statusPublished - 14 Aug 2023

Keywords

  • Change of support
  • Classification error
  • Decision making
  • Geostatistics
  • Interpolation error
  • Model error
  • Monte Carlo
  • Probability distribution
  • Random variable
  • Risk analysis
  • Uncertainty
  • Uncertainty propagation
  • Variance

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