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Calculates Basal Area in square meters.

Usage

silv_stand_basal_area(diameter, ntrees = NULL, units = "cm")

Arguments

diameter

Numeric vector of diameters or diameter classes

ntrees

Numeric vector with number of trees of the diameter class per hectare. If ntrees = NULL, the function will assume that each diameter corresponds to only one tree

units

The units of the diameter (one of mm, cm, dm, or m)

Value

A numeric vector

Details

The function uses the next formula:

\(G = \frac{\pi}{40000} \cdot D^2 \cdot \text{ntrees}\)

where G is the basal area in \(m^2\), and D is the diameter in cm. If ntrees in the number of trees per hectare, then the result will be \(m^2/ha\). It is recommended to use the squared mean diameter calculated with silv_stand_qmean_diameter().

Note that if ntrees = NULL, the output of the function will be exactly the same as in silv_tree_basal_area().

Examples

## calculate G for inventory data grouped by plot_id and species
library(dplyr)
inventory_samples |>
mutate(dclass = silv_tree_dclass(diameter)) |>
  summarise(
    height = mean(height, na.rm = TRUE),
    ntrees = n(),
    .by    = c(plot_id, species, dclass)
  ) |>
  mutate(
    ntrees_ha = silv_density_ntrees_ha(ntrees, plot_size = 10),
    dg        = silv_stand_qmean_diameter(dclass, ntrees_ha),
    g         = silv_stand_basal_area(dclass, ntrees_ha),
    .by       = c(plot_id, species)
  )
#> # A tibble: 57 × 8
#>    plot_id species dclass height ntrees ntrees_ha    dg       g
#>      <int>   <int>  <dbl>  <dbl>  <int>     <dbl> <dbl>   <dbl>
#>  1       7      27     50  18         3      95.5  57.9 0.196  
#>  2       7      27     55  17.6       5     159.   57.9 0.238  
#>  3       7      27     35  16.5       1      31.8  57.9 0.0962 
#>  4       7      27     45  14.6       2      63.7  57.9 0.159  
#>  5       7      27     60  19.1       3      95.5  57.9 0.283  
#>  6       7      27     25  12.9       1      31.8  57.9 0.0491 
#>  7       7      27    120  20.9       1      31.8  57.9 1.13   
#>  8       8      83     20   5.10      3      95.5  15.1 0.0314 
#>  9       8      83     10   6.10      4     127.   15.1 0.00785
#> 10       8      28     55  15.5       1      31.8  57.6 0.238  
#> # ℹ 47 more rows