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Estimate forest type for a tree list based on location

Source: R/trees_type.R
trees_type.Rd

trees_type() uses the input tree list (e.g. as exported by raster2trees()) with the columns treeID, tree_x, tree_y to attach species information using USDA Forest Inventory and Analysis (FIA) codes. If a spatial data frame of points is the input tree list, then the columns tree_x, tree_y are not required.

FIA Forest Type Group Code is attached to each tree in the tree list based on the spatial overlap with the Forest Type Groups of the Continental United States dataset Wilson 2023.

The simplified process for attaching forest type group to a tree is:

  • Forest type group 30-m raster (Wilson 2023) was aggregated to 90-m to make the data more accessible over the entire continental US

  • Nearest neighbor imputation is used to fill forest type data if a tree falls inside a no-forest cell in the original data

  • The FIA forest type group is applied to a tree based on spatial overlap

Usage

trees_type(
  tree_list,
  crs = NA,
  study_boundary = NA,
  input_foresttype_dir = NULL,
  max_search_dist_m = 1000
)

Arguments

tree_list

data.frame. A data frame with the columns treeID, tree_x, tree_y, and tree_height_m. If an sf class object with POINT geometry (see sf::st_geometry_type()), the program will use the data "as-is" and only require the treeID column.

crs

string. A crs string as returned from sf::st_crs() or the EPSG code of the x,y coordinates. Defaults to the crs of the tree_list data if of class "sf".

study_boundary

sf. The boundary of the study area to define the area of the regional model. If no boundary given, regional model will be built from location of trees in the tree list.

input_foresttype_dir

directory where Forest Type Groups data exists. Use get_foresttype() first.

max_search_dist_m

number. Maximum search distance (m) to obtain forest type group data for trees in tree_list that overlap with non-forest data in the original Wilson (2023) data. Larger search distances will increase processing time and possibly result in memory issues.

Value

Returns a list of objects: tree_list = spatial data frame of individual trees; foresttype_rast = raster of forest types in the area.

References

Examples

 if (FALSE) { # \dontrun{
 library(tidyverse)
 # example tree list
 tl <- dplyr::tibble(
     treeID = c(1:21)
     , tree_x = rnorm(n=21, mean = 458064, sd = 11)
     , tree_y = rnorm(n=21, mean = 4450074, sd = 11)
   )
 # call the function
 tl_type <- trees_type(tree_list = tl, crs = "32613")
 # what?
 tl_type %>% class()
 # a list, but what is in it?
 tl_type %>% names()
 # plot the tree_list spatial points
 tl_type$tree_list %>% ggplot2::ggplot() + ggplot2::geom_sf(ggplot2::aes(color=forest_type_group))
 # plot the foresttype_rast raster
 tl_type$foresttype_rast %>% terra::plot()
 } # }