| addCovariates {secr} | R Documentation |
Tools to construct spatial covariates for existing mask or traps objects from a spatial data source.
addCovariates(object, spatialdata, columns = NULL, strict = FALSE, replace = FALSE)
object |
mask, traps or popn object |
spatialdata |
spatial data source (see Details) |
columns |
character vector naming columns to include (all by default) |
strict |
logical; if TRUE a check is performed for points in |
replace |
logical; if TRUE then covariates with duplicate names are replaced; otherwise a new column is added |
The goal is to obtain the value(s) of one or more spatial covariates
for each point (i.e. row) in object. The procedure depends on
the data source spatialdata, which may be either a spatial
coverage (raster or polygon) or an object with covariate values at
points (another mask or traps object). In the first case, an
overlay operation is performed to find the pixel or
polygon matching each point. In the second case, a search is conducted
for the closest point in spatialdata.
If spatialdata is a character value then it is interpreted as
the name of a polygon shape file (excluding ‘.shp’).
If spatialdata is a SpatialPolygonsDataFrame,
SpatialGridDataFrame or 'sf' object from sf then it will be used
in an overlay operation as described.
If package terra has been installed then spatialdata may also be a RasterLayer from package raster or SpatRaster from terra. If provided counts should be a single name that will be used for the values (otherwise 'raster' will be used).
If spatialdata is a mask or traps object then it
is searched for the closest point to each point in object, and
covariates are drawn from the corresponding rows in
covariates(spatialdata). By default (strict = FALSE),
values are returned even when the points lie outside any cell of the mask.
An object of the same class as object with new or augmented
covariates attribute. Column names and types are derived from the input.
Use of a SpatialGridDataFrame for spatialdata is untested.
make.mask, read.mask, read.traps
## In the Lake Station skink study (see ?skink), habitat covariates were
## measured only at trap sites. Here we extrapolate to a mask, taking
## values for each mask point from the nearest trap.
LSmask <- make.mask(LStraps, buffer = 30, type = "trapbuffer")
tempmask <- addCovariates(LSmask, LStraps)
## show first few lines
head(covariates(tempmask))