Maximum likelihood variograms for efficient prediction in precision agriculture

R. Kerry; M.A. Oliver

Maximum likelihood variograms for efficient prediction in precision agriculture

In: Precision Agriculture â05

Authors:

R. Kerry

R. Kerry ¹Department of Geography, Brigham Young University, Provo, Utah, USA
ruth_kerry@byu.edu

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M.A. Oliver

M.A. Oliver ²Department of Soil Science, University of Reading, Reading, England

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Type:: Chapter

Pages:: 707â714

DOI:: https://doi.org/10.3920/978-90-8686-549-9_087

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To produce accurate maps of soil properties geostatistically for precise management is costly. The method of moments (MoM) variogram requires about 100 sites, which is more sampling than farmers can generally afford. It has been suggested that the maximum likelihood (ML) variogram might need fewer data, however, it is not clear how the sites should be distributed. Data from different sampling schemes were used to calculate ML and MoM variograms and their model parameters were used for cross-validation. Predictions from ML variograms were generally more accurate than those from the MoM with fewer than 100 sampling sites. Computing ML variograms from 50-60 sites is suggested for kriging.

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Precision Agriculture â05

E-Book ISBN:: 9789086865499

Publisher:: Wageningen Academic

Print Publication Date:: 24 Oct 2005

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Maximum likelihood variograms for efficient prediction in precision agriculture

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Precision Agriculture â05

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Precision Agriculture â05