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Spatially balanced sampling designs for environmental surveys

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Abstract

Some environmental studies use non-probabilistic sampling designs to draw samples from spatially distributed populations. Unfortunately, these samples can be difficult to analyse statistically and can give biased estimates of population characteristics. Spatially balanced sampling designs are probabilistic designs that spread the sampling effort evenly over the resource. These designs are particularly useful for environmental sampling because they produce good-sample coverage over the resource, they have precise design-based estimators and they can potentially reduce the sampling cost. The most popular spatially balanced design is Generalized Random Tessellation Stratified (GRTS), which has many desirable features including a spatially balanced sample, design-based estimators and the ability to select spatially balanced oversamples. This article considers the popularity of spatially balanced sampling, reviews several spatially balanced sampling designs and shows how these designs can be implemented in the statistical programming language R. We hope to increase the visibility of spatially balanced sampling and encourage environmental scientists to use these designs.

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Acknowledgements

We thank Jennifer Brown, Trent McDonald, Anton Grafström and Roberto Benedetti and anonymous referees for valuable comments that improved this paper.

Funding

This work was supported by “Communauté d’Agglomération Pays Basque – Euskal Hirigune Elkargoa” through a thesis grant.

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Authors and Affiliations

  1. Laboratoire de Mathématiques et de leurs Applications de Pau – MIRA, CNRS/Univ Pau & Pays Adour/E2S UPPA, UMR 5142, 64600, Anglet, France

    Claire Kermorvant, Frank D’Amico & Noëlle Bru

  2. Ifremer - Laboratoire Environnement Ressources d’Arcachon, 1 Allée du Parc Montaury, 64600, Anglet, France

    Nathalie Caill-Milly

  3. School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand

    Blair Robertson

Authors
  1. Claire Kermorvant
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  2. Frank D’Amico
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  3. Noëlle Bru
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  4. Nathalie Caill-Milly
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  5. Blair Robertson
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Correspondence to Claire Kermorvant.

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Kermorvant, C., D’Amico, F., Bru, N. et al. Spatially balanced sampling designs for environmental surveys. Environ Monit Assess 191, 524 (2019). https://doi.org/10.1007/s10661-019-7666-y

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