The continuous population approach to forest inventories and use of information in the design. Grafström, A., Schnell, S., Saarela, S., Hubbell, S. P., & Condit, R. Environmetrics, 2017.
The continuous population approach to forest inventories and use of information in the design [link]Paper  doi  abstract   bibtex   
An extended theoretical framework for the continuous population approach to forest inventories is derived. Here, we treat a simultaneous selection of sample points with any prescribed sampling intensity over a continuous population. Different ways to use available auxiliary information, for example, from remote sensing, by selection of approximately balanced or spatially balanced samples are considered. A large data set of spatially continuous individual tree-level data is used to demonstrate the potential of these theoretical approaches. This study shows new ways to integrate remote sensing information in designs for forest inventory applications, which can significantly reduce the variance of the Horvitz–Thompson estimator for target variables related to the auxiliary information.
@article{RN471,
   author = {Grafström, A. and Schnell, S. and Saarela, S. and Hubbell, S. P. and Condit, R.},
   title = {The continuous population approach to forest inventories and use of information in the design},
   journal = {Environmetrics},
   volume = {28},
   number = {8},
   abstract = {An extended theoretical framework for the continuous population approach to forest inventories is derived. Here, we treat a simultaneous selection of sample points with any prescribed sampling intensity over a continuous population. Different ways to use available auxiliary information, for example, from remote sensing, by selection of approximately balanced or spatially balanced samples are considered. A large data set of spatially continuous individual tree-level data is used to demonstrate the potential of these theoretical approaches. This study shows new ways to integrate remote sensing information in designs for forest inventory applications, which can significantly reduce the variance of the Horvitz–Thompson estimator for target variables related to the auxiliary information.},
   keywords = {balanced sampling
cube method
Horvitz–Thompson estimator
local pivotal method
Monte Carlo
representative samples},
   ISSN = {1099-095X},
   DOI = {10.1002/env.2480},
   url = {https://doi.org/10.1002/env.2480},
   year = {2017},
   type = {Journal Article}
}

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