fuzzySim (version 3.0)

gridRecords: Grid point occurrence records onto a raster

Description

This function takes a raster stack and a set of spatial coordinates of a species' presence (and optionally absence) records, and returns a data frame with the presences and absences, as well as the corresponding values of the rasters in the grid of pixels (cells). If absence coordinates are not supplied, all pixels without any presence point will be returned as absences.

Usage

gridRecords(rst, pres.coords, abs.coords = NULL, na.rm = TRUE)

Arguments

rst

a Raster* object with the desired spatial resolution and extent for the species presence-absence data, and the layer(s) whose values to extract for those data. The raster should be masked so that pixels have values only in relevant and reasonably surveyed areas.

pres.coords

a matrix or data frame with two columns containing, respectively, the x and y, or longitude and latitude coordinates (in this order, and in the same coordinate reference system as 'rst') of the points where species presence was detected.

abs.coords

same as 'pres.coords' but for points where the species was not detected. If NULL (the default), all pixels that are not intersected by 'pres.coords' will be output as absence cells.

na.rm

Logical value indicating whether pixels without values in any of the 'rst' layers should be removed from the resulting data frame. The default is TRUE.

Value

This function returns a data frame with the following columns:

'presence'

integer, 1 for the cells with at least one presence point, and 0 for the cells with absence points (if provided) AND with no presence points

'x', 'y'

centroid coordinates of each pixel (cell)

'cellnumber'

the pixel identifier in 'rst'

one column for each layer in 'rst'

with the value of each pixel for that layer.

Details

This function was used e.g. in Baez et al. (2020) to get unique presences and absences from point occurrence data at the spatial resolution of marine raster variables.

References

Baez J.C., Barbosa A.M., Pascual P., Ramos M.L. & Abascal F. (2020) Ensemble modelling of the potential distribution of the whale shark in the Atlantic Ocean. Ecology and Evolution, 10: 175-184

See Also

'extract' in package raster

Examples

# NOT RUN {
# you can run the following code if you have the 'raster' and 'sp' packages installed

# import a system raster with 3 layers and crop it to a smaller extent:
require(raster)
rst <- stack(system.file("external/rlogo.grd", package = "raster"))
ext <- extent(c(0, 15, 25, 40))
rst <- crop(rst, ext)
plot(rst)
plot(rst[[1]])

# generate some random presence and absence points:
set.seed(123)
presences <- sp::spsample(as(ext, "SpatialPolygons"), 50, type = "random")
absences <- sp::spsample(as(ext, "SpatialPolygons"), 50, type = "random")
points(presences, pch = 20, cex = 0.2, col = "black")
points(absences, pch = 20, cex = 0.2, col = "white")

# use 'gridRecords' on these random points:
gridded_pts <- gridRecords(rst, coordinates(presences), coordinates(absences))
head(gridded_pts)  # 'red', 'green' and 'blue' are the names of the layers in 'rst'

# plot them to check the result:
pres_coords <- gridded_pts[gridded_pts$presence == 1, c("x", "y")]
abs_coords <- gridded_pts[gridded_pts$presence == 0, c("x", "y")]
points(gridded_pts[ , c("x", "y")], pch = 4, cex = 0.6, col = gridded_pts$presence)

# you can also do it with only presence (no absence) records:
gridded_pres <- gridRecords(rst, coordinates(presences))
head(gridded_pres)
plot(rst[[1]])
points(presences, pch = 20, cex = 0.2, col = "black")
pres_coords <- gridded_pres[gridded_pres$presence == 1, c("x", "y")]
abs_coords <- gridded_pres[gridded_pres$presence == 0, c("x", "y")]
points(gridded_pres[ , c("x", "y")], pch = 4, cex = 0.6, col = gridded_pres$presence)
# }