layer_mask

This function crops and extends raster layers to a study area extent (bbox) defined by longitude
and latitude then applies a mask based on a provided spatial polygon to remove areas outside the polygon.

A user-friendly 'shiny' application for Bayesian machine
learning analysis of marine species distributions. GLOSSA (Global
Species Spatiotemporal Analysis) uses Bayesian Additive Regression
Trees (BART; Chipman, George, and McCulloch (2010)
<doi:10.1214/09-AOAS285>) to model species distributions with
intuitive workflows for data upload, processing, model fitting, and
result visualization. It supports presence-absence and presence-only
data (with pseudo-absence generation), spatial thinning,
cross-validation, and scenario-based projections. GLOSSA is designed
to facilitate ecological research by providing easy-to-use tools for
analyzing and visualizing marine species distributions across
different spatial and temporal scales.

Jorge Mestre-Tomás

glossa

User-Friendly 'shiny' App for Bayesian Species Distribution
Models

Alba Fuster-Alonso

layer_mask function

<dl><dt>layers</dt>
<dd>A stack of raster layers (`SpatRaster` object) to be processed.</dd>
<dt>study_area</dt>
<dd>A spatial polygon (`sf` object) used to mask the raster layers.</dd></dl>

Arguments

Apply Polygon Mask to Raster Layers — layer_mask

<dl>

<dt>layers</dt>
<dd>A stack of raster layers (`SpatRaster` object) to be processed.</dd>


<dt>study_area</dt>
<dd>A spatial polygon (`sf` object) used to mask the raster layers.</dd>

</dl>

layer_mask: Apply Polygon Mask to Raster Layers

Description

Usage

Value

Arguments