aba_inference

computes inference from area-based model and predicted values

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

aba_inference function

<dl><dt>aba_model</dt>
<dd>a model returned by <code>aba_build_model</code> or
<code>aba_combine_strata</code></dd>
<dt>r_predictions</dt>
<dd>raster of predicted values</dd>
<dt>type</dt>
<dd>string vector specifying which estimators should be computed
(one or several in "SRS", "ED", "D", "STR", "SYNT")</dd>
<dt>r_mask</dt>
<dd>raster to mask region of interest (NA values), may contain
post-stratification categories (should be integer, positive values)</dd></dl>

Arguments

computes inference from area-based model and predicted values — aba_inference

<dl>

<dt>aba_model</dt>
<dd>a model returned by <code>aba_build_model</code> or
<code>aba_combine_strata</code></dd>


<dt>r_predictions</dt>
<dd>raster of predicted values</dd>


<dt>type</dt>
<dd>string vector specifying which estimators should be computed
(one or several in "SRS", "ED", "D", "STR", "SYNT")</dd>


<dt>r_mask</dt>
<dd>raster to mask region of interest (NA values), may contain
post-stratification categories (should be integer, positive values)</dd>

</dl>

aba_inference: computes inference from area-based model and predicted values

Description

Usage

Value

Arguments