secr (version 3.0.1)

addCovariates:

Description

Tools to construct spatial covariates for existing mask or traps objects from a spatial data source. Possible sources include GIS data such as ESRI polygon shapefiles input using maptools.

Usage

addCovariates(object, spatialdata, columns = NULL, strict = FALSE, replace = FALSE)

Arguments

object

mask or traps 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 object that lie outside spatialdata (mask data sources only)

replace

logical; if TRUE then covariates with duplicate names are replaced; otherwise a new column is added

Value

An object of the same class as object with new or augmented covariates attribute. Column names and types are derived from the input.

Warning

Use of a SpatialGridDataFrame for spatialdata is untested.

Details

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 or a SpatialGridDataFrame then it will be used in an overlay operation as described.

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.

See Also

make.mask, read.mask, read.traps

Examples

## 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))