data_tariffs

The adapted uniform French tariffs are typically used in Slovenia to determine tree volume based on tree DBH

datasets

Climate-sensitive forest simulator based on the principles of
machine learning. It stimulates all key processes in the forest: radial growth,
height growth, mortality, crown recession, regeneration and harvesting. The
method for predicting tree heights was described by Skudnik and Jevšenak
(2022) <doi:10.1016/j.foreco.2022.120017>, while the method for predicting
basal area increments (BAI) was described by Jevšenak and Skudnik (2021)
<doi:10.1016/j.foreco.2020.118601>.

Jernej Jevsenak

MLFS

Machine Learning Forest Simulator

data_tariffs function

A data frame with 1196 rows and 4 variables:<dl>
 <dt>tarifa_class</dt>
<dd>tariff class for a particular species on this plot</dd> <dt>plotID</dt>
<dd>plot identifier</dd> <dt>species</dt>
<dd>species name as used in data_NFI</dd> <dt>v45</dt>
<dd>volume of tree with DBH 45 cm</dd>
</dl>

Format

An example of table with one-parametric volume functions (adapted uniform French tariffs) — data_tariffs

A data frame with 1196 rows and 4 variables:<dl>
 <dt>tarifa_class</dt>
<dd>tariff class for a particular species on this plot</dd>

 <dt>plotID</dt>
<dd>plot identifier</dd>

 <dt>species</dt>
<dd>species name as used in data_NFI</dd>

 <dt>v45</dt>
<dd>volume of tree with DBH 45 cm</dd>


</dl>

data_tariffs: An example of table with one-parametric volume functions (adapted uniform French tariffs)

Description

Usage

Arguments

Format