Add Covariates to Mask or Traps
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 rgdal.
addCovariates(object, spatialdata, columns = NULL, strict = FALSE, replace = FALSE)
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 |
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 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.
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.
The package rgdal is needed to read a shapefile, and the package sp is needed for spatial overlay.
## 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))
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.