Create a sdm_area object — sdm

This function creates a new sdm_area object.

Usage

sdm_area(x, cell_size = NULL, crs = NULL, variables_selected = NULL,
                gdal = TRUE, crop_by = NULL, lines_as_sdm_area = FALSE)

get_sdm_area(i)

add_sdm_area(sa1, sa2)

Arguments

x: A shape or a raster. Usually a shape from sf class, but rasters from stars, rasterStack or SpatRaster class are also allowed.
cell_size: numeric. The cell size to be used in models.
crs: numeric. Indicates which EPSG should the output grid be in. If NULL, epsg from x is used.
variables_selected: A character vector with variables in x to be used in models. If NULL (standard), all variables in x are used.
gdal: Boolean. Force the use or not of GDAL when available. See details.
crop_by: A shape from sf to crop x.
lines_as_sdm_area: Boolean. If x is a sf with LINESTRING geometry, it can be used to model species distribution in lines and not grid cells.
i: A sdm_area or a input_sdm object.
sa1: A sdm_area object.
sa2: A sdm_area object.

Value

A sdm_area object containing:

grid: sf with POLYGON geometry representing the grid for the study area.
cell_size: numeric information regarding the size of the cell used to rescale variables to the study area, representing also the cell size in the grid.

Details

The function returns a sdm_area object with a grid built upon the x parameter. There are two ways to make the grid and resample the variables in sdm_area: with and without gdal. As standard, if gdal is available in you machine it will be used (gdal = TRUE), otherwise sf/stars will be used. get_sdm_area will return the grid built by sdm_area. add_sdm_area will sum two sdm_area objects. As geoprocessing in caretSDM is performed using sf objects, add_sdm_area simply applies a rbind in the two different areas.

Author

Luíz Fernando Esser (luizesser@gmail.com) and Reginaldo Ré. https://luizfesser.wordpress.com

Examples

# Create sdm_area object:
sa_area <- sdm_area(parana, cell_size = 50000, crs = 6933)
#> ! Making grid over study area is an expensive task. Please, be patient!
#> ℹ Using GDAL to make the grid and resample the variables.

# Create sdm_area using a subset of rivs (lines):
sa_rivers <- sdm_area(rivs[c(1:100),], cell_size = 100000, crs = 6933, lines_as_sdm_area = TRUE)
#> ! Making grid over study area is an expensive task. Please, be patient!
#> ℹ Using GDAL to make the grid and resample the variables.

Create a `sdm_area` object