data_site

This is simulated data describing site descriptors

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_site function

A data frame with 371 rows and 5 variables:<dl>
 <dt>plotID</dt>
<dd>a unique identifier for plot</dd> <dt>slope</dt>
<dd>slope on a plot</dd> <dt>elevation</dt>
<dd>plot elevation</dd> <dt>northness</dt>
<dd>plot northness, 1 is north, 0 is south</dd> <dt>siteIndex</dt>
<dd>a proxy for site index, higher value represents more productive sites</dd>
</dl>

Format

An example of site descriptors — data_site

A data frame with 371 rows and 5 variables:<dl>
 <dt>plotID</dt>
<dd>a unique identifier for plot</dd>

 <dt>slope</dt>
<dd>slope on a plot</dd>

 <dt>elevation</dt>
<dd>plot elevation</dd>

 <dt>northness</dt>
<dd>plot northness, 1 is north, 0 is south</dd>

 <dt>siteIndex</dt>
<dd>a proxy for site index, higher value represents more productive sites</dd>


</dl>

data_site: An example of site descriptors

Description

Usage

Arguments

Format