Abstract
Geostatistics, developed originally in the mining industry from the 1950s onwards, is now being applied widely in environmental science for mapping, monitoring and management. It is based on the theory of random spatial processes. There are numerous examples in soil science, meteorology, agronomy, hydrology, ecology and some aspects of marine science. By taking into account and modelling spatial correlation, geostatistics provides unbiased predictions of environmental variables with minimum and known variance in ways that no other method does. The general technique of prediction is known as kriging. It requires a mathematical model to describe the spatial covariance, usually expressed as a variogram, which in its parameterized form has become the central tool of geostatistics. Successful kriging and estimation of the variogram depend on sampling adequately without bias and with suitable spatial configurations and supports. These differ somewhat from design-based estimation with its emphasis on random sampling.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2015 The Author(s)
About this chapter
Cite this chapter
Oliver, M.A., Webster, R. (2015). Introduction. In: Basic Steps in Geostatistics: The Variogram and Kriging. SpringerBriefs in Agriculture. Springer, Cham. https://doi.org/10.1007/978-3-319-15865-5_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-15865-5_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-15864-8
Online ISBN: 978-3-319-15865-5
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)