masking

mask_access

mask_existing

Mask covariates and existing samples by access

internal

Structurally guided sampling (SGS) approaches for airborne laser scanning (ALS; LIDAR). Primary functions provide means
to generate data-driven stratifications & methods for allocating samples. Intermediate functions for calculating and extracting important information
about input covariates and samples are also included. Processing outcomes are intended to help forest and environmental management
practitioners better optimize field sample placement as well as assess and augment existing sample networks in the context of data
distributions and conditions. ALS data is the primary intended use case, however any rasterized remote sensing data can be used,
enabling data-driven stratifications and sampling approaches.

Tristan RH Goodbody

sgsR

Structurally Guided Sampling

Nicholas C Coops

Martin Queinnec

masking function

<dl><dt>raster</dt>
<dd>SpatRaster. Raster to be masked.</dd>
<dt>access</dt>
<dd>sf 'LINESTRING' or 'MULTILINESTRING'. Access network.</dd>
<dt>buff_inner</dt>
<dd>Numeric. Inner buffer boundary specifying distance
from access where plots cannot be sampled.</dd>
<dt>buff_outer</dt>
<dd>Numeric. Outer buffer boundary specifying distance
from access where plots can be sampled.</dd>
<dt>existing</dt>
<dd>sf 'POINT'. Existing plot network.</dd></dl>

Arguments

Masking — masking

<dl>

<dt>raster</dt>
<dd>SpatRaster. Raster to be masked.</dd>


<dt>access</dt>
<dd>sf 'LINESTRING' or 'MULTILINESTRING'. Access network.</dd>


<dt>buff_inner</dt>
<dd>Numeric. Inner buffer boundary specifying distance
from access where plots cannot be sampled.</dd>


<dt>buff_outer</dt>
<dd>Numeric. Outer buffer boundary specifying distance
from access where plots can be sampled.</dd>


<dt>existing</dt>
<dd>sf 'POINT'. Existing plot network.</dd>

</dl>

masking: Masking

Description

Usage

Value

Arguments