Modeling Forest Tree Data Using Sequential Spatial Point Processes
Yazigi, A., Penttinen, A., Ylitalo, A.-K., Maltamo, M., Packalen, P., & Mehtätalo, L. (2022). Modeling Forest Tree Data Using Sequential Spatial Point Processes. Journal of Agricultural, Biological, and Environmental Statistics, 27(1), 88-108. https://doi.org/10.1007/s13253-021-00470-2
© 2021 The Author(s)
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. ...
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Additional information about fundingThis research was financially supported by the Academy of Finland research Project 310073 and the flagship program (UNITE, Decision Number 337655). Open access funding provided by University of Eastern Finland (UEF) including Kuopio University Hospital.
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