input_sdm: 'input_sdm'

In caretSDM: Build Species Distribution Modeling using 'caret'

input_sdm

Description

This function creates a new input_sdm object.

Usage

input_sdm(...)

add_input_sdm(i1, i2)

Arguments

...	Data to be used in SDMs. Can be a occurrences and/or a sdm_area object.
i1	A input_sdm object.
i2	A input_sdm object.

Details

If sdm_area is used, it can include predictors and scenarios. In this case, input_sdm will detect and include as scenarios and predictors in the input_sdm output. Objects can be included in any order, since the function will work by detecting their classes. The returned object is used throughout the whole workflow to apply functions.

Value

A input_sdm object containing:

grid	sf with POLYGON geometry representing the grid for the study area or LINESTRING if sdm_area was built with a LINESTRING sf.
bbox	Four corners for the bounding box (class bbox): minimum value of X, minimum value of Y, maximum value of X, maximum value of Y
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.
epsg	character information about the EPSG used in all slots from sdm_area.
predictors	character vector with predictors names included in sdm_area.

Author(s)

Luiz Fernando Esser ([e-mail]) https://luizfesser.wordpress.com

See Also

occurrences_sdm sdm_area

Examples

# Create sdm_area object:
sa <- sdm_area(parana, cell_size = 50000, crs = 6933)

# Include predictors:
sa <- add_predictors(sa, bioc) |> select_predictors(c("bio1", "bio4", "bio12"))

# Include scenarios:
sa <- add_scenarios(sa, scen)

# Create occurrences:
oc <- occurrences_sdm(occ, crs = 6933) |> join_area(sa)

# Create input_sdm:
i <- input_sdm(oc, sa)

caretSDM documentation built on Aug. 29, 2025, 5:17 p.m.