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Modeling Forest Tree Data Using Sequential Spatial Point Processes

Author

Listed:
  • Adil Yazigi

    (University of Eastern Finland)

  • Antti Penttinen

    (University of Jyväskylä)

  • Anna-Kaisa Ylitalo

    (Natural Resources Institute Finland (Luke))

  • Matti Maltamo

    (University of Eastern Finland)

  • Petteri Packalen

    (University of Eastern Finland)

  • Lauri Mehtätalo

    (Bioeconomy and Environment Unit, Natural Resources Institute Finland (Luke))

Abstract

The spatial structure of a forest stand is typically modeled by spatial point process models. Motivated by aerial forest inventories and forest dynamics in general, we propose a sequential spatial approach for modeling forest data. Such an approach is better justified than a static point process model in describing the long-term dependence among the spatial location of trees in a forest and the locations of detected trees in aerial forest inventories. Tree size can be used as a surrogate for the unknown tree age when determining the order in which trees have emerged or are observed on an aerial image. Sequential spatial point processes differ from spatial point processes in that the realizations are ordered sequences of spatial locations, thus allowing us to approximate the spatial dynamics of the phenomena under study. This feature is useful in interpreting the long-term dependence and spatial history of the locations of trees. For the application, we use a forest data set collected from the Kiihtelysvaara forest region in Eastern Finland.

Suggested Citation

  • Adil Yazigi & Antti Penttinen & Anna-Kaisa Ylitalo & Matti Maltamo & Petteri Packalen & Lauri Mehtätalo, 2022. "Modeling Forest Tree Data Using Sequential Spatial Point Processes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(1), pages 88-108, March.
    • Handle: RePEc:spr:jagbes:v:27:y:2022:i:1:d:10.1007_s13253-021-00470-2
    DOI: 10.1007/s13253-021-00470-2
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    References listed on IDEAS

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    1. Mari Myllymäki & Tomáš Mrkvička & Pavel Grabarnik & Henri Seijo & Ute Hahn, 2017. "Global envelope tests for spatial processes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 381-404, March.
    2. Jesper Møller & Mohammad Ghorbani & Ege Rubak, 2016. "Mechanistic spatio-temporal point process models for marked point processes, with a view to forest stand data," Biometrics, The International Biometric Society, vol. 72(3), pages 687-696, September.
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