# A sample of trees from an angle count sample , where each
# tree represents a basal area of 4 m²/ha
d_cm <- c(12, 13, 25, 27, 28, 26, 26.1, 32, 35, 31, 42)
n_rep_ha <- 4 / ((d_cm / 100)^2 * pi / 4) # representation number of each tree
dq_cm <- d_q(d_cm, n_rep_ha)
h_m <- 0.9 * dq_cm * (d_cm / dq_cm)^0.8 # quick plausible height estim.
h_dom_weise(h_m, d_cm, n_rep_ha)
h_100(h_m, d_cm, n_rep_ha) # dominant height h100 for comparison
h_q(h_m, d_cm) # quadratic mean height for comparison
# if 20% of the trees are 100 stems/ha, Weise's dominant diameter and
# d100 are equal
d_cm <- rnorm(n = 500, mean = 35, sd = 7)
dq_cm <- d_q(d_cm)
h_m <- 0.8 * dq_cm * (d_cm / dq_cm)^0.8 # quick plausible height estim.
h_dom_weise(h_m, d_cm, 1)
h_100(h_m, d_cm, 1)
# Weise's dominant diameter is greater than d100, if 20% of the trees
# represent less than 100 trees/ha
d_cm <- rnorm(n = 200, mean = 35, sd = 7)
dq_cm <- d_q(d_cm)
h_m <- 0.8 * dq_cm * (d_cm / dq_cm)^0.8 # quick plausible height estim.
h_dom_weise(h_m, d_cm, 1)
h_100(h_m, d_cm, 1)
# Weise's dominant diameter is smaller than d100, if 20% of the trees
# represent more than 100 trees/ha
d_cm <- rnorm(n = 800, mean = 35, sd = 7)
dq_cm <- d_q(d_cm)
h_m <- 0.8 * dq_cm * (d_cm / dq_cm)^0.8 # quick plausible height estim.
h_dom_weise(h_m, d_cm, 1)
h_100(h_m, d_cm, 1)
Run the code above in your browser using DataLab