est_clutter: Estimate future and present basal area, volume, TCA, CMI and...

In forestmangr: Forest Mensuration and Management

Estimate future and present basal area, volume, TCA, CMI and MMI values of the Clutter Growth and Yield Model

Description

This function estimates the present the present value of basal area for each class using either the class mean, or a linear quadratic model, and then uses it's value to calculate the basal area from Clutter's growth and yield model.

Usage

est_clutter(
  df,
  age,
  basal_area,
  site,
  category,
  coeffs,
  method = "average",
  annual_increment = FALSE,
  gray_scale = TRUE,
  output = "table"
)

Arguments

df	A data frame.
age	A numeric vector with the desired age range to be used in the estimation, or a Quoted name for the age variable.
basal_area	Quoted name for the basal area variable.
site	Quoted name for the average site variable.
category	Quoted name for the category variable.
coeffs	Numeric vector or a data frame with the fitted values of Clutter's growth and yield model. It must be a named vector, with b0,b1,b2,b3,a0 and a1 as names. a1 is not obligatory.
method	Method used for estimating the present basal area of each class. It can either be the class' average basal area "average", or an estimated value from a linear quadratic model of site as a function of basal area "model". Default: "average".
annual_increment	If TRUE, changes the labels from Mean Monthly Increment (MMI) and Current Monthly Increment (CMI) to Mean Annual Increment (MAI) and Current Annual Increment (CAI). Default FALSE.
gray_scale	If TRUE, the plot will be rendered in a gray scale. Default: "TRUE".
output	Type of output the function should return. This can either be "plot", for the estimation plots, "table", for a data frame with the estimated values, and "full" for a list with the plot and 2 more data frames. "table".

Value

A data frame, a ggplot object or a list, according to output.

Author(s)

Sollano Rabelo Braga [e-mail]

See Also

other sampling functions: fit_clutter for fitting the clutter growth and Yield model, and classify_site for classifying data according to site.

Examples

library(forestmangr)
data("exfm17")
head(exfm17)

clutter <- fit_clutter(exfm17, "age", "DH", "B", "V", "S", "plot")
clutter

# Classify data into 3 classes:
ex_class <- classify_site(exfm17, "S", 3, "plot")
head(ex_class ,15)

# Estimate basal area using the average basal area as the initial basal area,
# volume,  Mean Monthly Increment (MMI) and Current Monthly Increment (CMI)
# values using Clutter's model:
est_clutter(ex_class,20:125, "B","S","category_",clutter,"average")

# For a more detailed output, including a plot, use output="full":
est_clutter(ex_class,20:125, "B","S","category_",clutter, output="full")

# Estimate basal area using an estimated basal area as the initial basal area:
est_clutter(ex_class,20:125,"B","S","category_",clutter,"model") 

# age can be a variable:
est_clutter(ex_class,"age","B","S","category_", clutter,"model")  
  

forestmangr documentation built on Nov. 24, 2023, 1:07 a.m.