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A sample coordination method to monitor totals of environmental variables

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  • Xin Zhao
  • Anton Grafström

Abstract

A new sampling strategy for design‐based environmental monitoring is proposed. It has the potential to produce superior estimators for totals of environmental variables and their changes over time. In the strategy, we combine two concepts known as spatially balanced sampling and coordination of samples. Spatially balanced sampling can provide superior estimators of totals, while coordination of samples over time is often used to improve estimators of change. Compared with reference strategies, we show that the new strategy can improve the precision of the estimators of totals and their change simultaneously. A forest inventory application is used to illustrate the new strategy and the results can be summarized as (i) using auxiliary information to spread the sample can improve the estimators of totals; (ii) a positive coordination of the samples reduced the variance of the estimator of change by more than 37% compared with independent samples; and (iii) a high overlap between successive samples does not guarantee a good estimator of change. The presented strategy can be used to develop more efficient environmental monitoring programs.

Suggested Citation

  • Xin Zhao & Anton Grafström, 2020. "A sample coordination method to monitor totals of environmental variables," Environmetrics, John Wiley & Sons, Ltd., vol. 31(6), September.
    • Handle: RePEc:wly:envmet:v:31:y:2020:i:6:n:e2625
    DOI: 10.1002/env.2625
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    1. Roberto Benedetti & Federica Piersimoni & Paolo Postiglione, 2015. "Sampling Spatial Units for Agricultural Surveys," Advances in Spatial Science, Springer, edition 127, number 978-3-662-46008-5.
    2. Anton Grafström & Lina Schelin, 2014. "How to Select Representative Samples," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 277-290, June.
    3. A. Grafström & S. Schnell & S. Saarela & S. P. Hubbell & R. Condit, 2017. "The continuous population approach to forest inventories and use of information in the design," Environmetrics, John Wiley & Sons, Ltd., vol. 28(8), December.
    4. Lennart Bondesson & Daniel Thorburn, 2008. "A List Sequential Sampling Method Suitable for Real‐Time Sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(3), pages 466-483, September.
    5. Anton Grafström & Alina Matei, 2018. "Spatially Balanced Sampling of Continuous Populations," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 45(3), pages 792-805, September.
    6. B. L. Robertson & J. A. Brown & T. McDonald & P. Jaksons, 2013. "BAS: Balanced Acceptance Sampling of Natural Resources," Biometrics, The International Biometric Society, vol. 69(3), pages 776-784, September.
    7. Mach, Lenka & Reiss, Philip T. & Schiopu-Kratina, Ioana, 2006. "Optimizing the Expected Overlap of Survey Samples via the Northwest Corner Rule," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1671-1679, December.
    8. Stevens, Don L. & Olsen, Anthony R., 2004. "Spatially Balanced Sampling of Natural Resources," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 262-278, January.
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    1. Xin Zhao & Anton Grafström, 2024. "Estimation of change with partially overlapping and spatially balanced samples," Environmetrics, John Wiley & Sons, Ltd., vol. 35(1), February.
    2. Wilmer Prentius, 2024. "Locally correlated Poisson sampling," Environmetrics, John Wiley & Sons, Ltd., vol. 35(2), March.

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