hist_stack

Provides functions for forest objects detection, structure metrics
computation, model calibration and mapping with airborne laser scanning:
co-registration of field plots (Monnet and Mermin (2014)
<doi:10.3390/f5092307>); tree detection (method 1 in Eysn et al. (2015)
<doi:10.3390/f6051721>) and segmentation; forest parameters estimation with
the area-based approach: model calibration with ground reference, and maps
export (Aussenac et al. (2023) <doi:10.12688/openreseurope.15373.2>);
extraction of both physical (gaps, edges, trees) and statistical
features useful for e.g. habitat suitability modeling (Glad et al. (2020)
<doi:10.1002/rse2.117>) and forest maturity mapping (Fuhr et al. (2022)
<doi:10.1002/rse2.274>).

Jean-Matthieu Monnet

lidaRtRee

Forest Analysis with Airborne Laser Scanning (LiDAR) Data

Pascal Obstétar

hist_stack function

<dl><dt>x</dt>
<dd>list of vectors. values for each category</dd>
<dt>breaks</dt>
<dd>vector. breaks for histogram bins</dd>
<dt>col</dt>
<dd>vector. colors for each category</dd>
<dt>breaksFun</dt>
<dd>function for breaks display</dd>
<dt>...</dt>
<dd>arguments to be passed to methods, as in <code><a href="/link/plot?package=lidaRtRee&version=4.0.8" data-mini-rdoc="lidaRtRee::plot">plot</a></code></dd></dl>

Arguments

Stacked histogram — hist_stack

<dl>

<dt>x</dt>
<dd>list of vectors. values for each category</dd>


<dt>breaks</dt>
<dd>vector. breaks for histogram bins</dd>


<dt>col</dt>
<dd>vector. colors for each category</dd>


<dt>breaksFun</dt>
<dd>function for breaks display</dd>


<dt>...</dt>
<dd>arguments to be passed to methods, as in <code><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></code></dd>

</dl>

hist_stack: Stacked histogram

Description

Usage

Value

Arguments