sum_k_tree: Summarizing of tree-level data for k-tree sampling

In AWF-GAUG/fisim: Forest Inventory Simulator (fisim) is a package for simulating response and samplign designs common in forest inventories.

Description

Helper function to summarize tree-level sample data to the plot-level, where k-tree sampling (k_tree) was used for selecting trees at sample locations.

Usage

sum_k_tree(tree_sample, target_vars)

Arguments

tree_sample	A tree_sample object as coming from the extract_data function.
target_var	A character vector of variable names which should be summarized at the plot level

Details

For k-tree sampling, individual tree inlcusion probabilities can only be derived if the tree stem positions of a substantially larger number of trees are available than are actually selected at the single sample locations (see Kleinn & Vilcko 2006a). In practical timber surveys or forest inventories, such extensive numbers of tree positions around the actual sample of trees are typically not available. Instead approximations for expanding the locally observed forest stand characteristics are applied. This functions provides a set of four approximations that are presented in Kleinn & Vilcko (2006b).

Value

A data.table object with stand characteristics at the plot level. Currently, basal area per hectare and the number of trees per hectare are included. The four different approximations are provided under the following columns:

• Prodan - The approach of Prodan, where only half of the k-th tree is considered (Prodan, 1968).

• Eberhardt - Expansion is based on the distance to the k-th tree and corrected with factor (k-1)/k (Eberhardt 1967)

• d_mean - A circle, where the radius is the average between the distances to tree k and tree k+1

• a_mean - The radius of the average area of the circles that are built from the distances to tree k and tree k+1

References

• Kleinn, C., Vil<c4><8d>ko, F., 2006a. Design-unbiased estimation for point-to-tree distance sampling. Canadian Journal of Forest Research 36, 1407<e2><80><93>1414. https://doi.org/10.1139/x06-038

• Kleinn, C., Vil<c4><8d>ko, F., 2006b. A new empirical approach for estimation in k-tree sampling. Forest Ecology and Management 237, 522<e2><80><93>533. https://doi.org/10.1016/j.foreco.2006.09.072

• Prodan, M., 1968. Punktstichprobe f<c3><bc>r die Forsteinrichtung (A point sample for forest management planning). Forst Holzwirt 23 (11), 225<e2><80><93>226.

• Eberhardt, L.L., 1967. Some developments in distance sampling. Biometrics 23, 207<e2><80><93>216.

AWF-GAUG/fisim documentation built on May 28, 2019, 11:02 a.m.