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extract() obtains the values of a GRaster or GVector associated with the locations of a set of points. The output depends on the input:
Case #1: x is a numeric or integer GRaster and y is a points GVector: Returns values of cells that have points. If xy is TRUE, also returns the coordinates of the points.
Case #2: x is a categorical (factor) GRaster and y is a points GVector: Same as case #1, but if cats is TRUE, returns category labels of cells that have points. If xy is TRUE, also returns the coordinates of the points.
Case #3: x is a categorical GRaster and y is a lines or polygons GVector: Returns a summary (e.g., mean, standard deviation, etc.) of all cells that overlap the line(s) or polygon(s).
Case #4: x is a GVector and y is a points GVector: Returns the data table row associated each point. If xy is TRUE, also returns the coordinates of the points.
Note that whenever a points GVector is allowed for y, a data.frame, data.table, matrix, or numeric values representing points can be used instead.
# S4 method for GRaster,GVector
extract(
x,
y,
fun = "mean",
prob = 0.5,
overlap = TRUE,
xy = FALSE,
cats = TRUE,
verbose = FALSE,
...
)# S4 method for GRaster,data.frame
extract(x, y, xy = FALSE, cats = TRUE)
# S4 method for GRaster,data.table
extract(x, y, xy = FALSE, cats = TRUE)
# S4 method for GRaster,matrix
extract(x, y, xy = FALSE, cats = TRUE)
# S4 method for GRaster,numeric
extract(x, y, xy = FALSE, cats = TRUE)
# S4 method for GVector,GVector
extract(x, y, xy = FALSE, verbose = TRUE)
# S4 method for GVector,data.frame
extract(x, y, xy = FALSE, verbose = TRUE)
# S4 method for GVector,data.table
extract(x, y, xy = FALSE, verbose = TRUE)
# S4 method for GVector,matrix
extract(x, y, xy = FALSE, verbose = TRUE)
# S4 method for GVector,numeric
extract(x, y, xy = FALSE)
A data.frame or data.table.
A GRaster or GVector.
A GVector, or a data.frame or matrix where the first two columns represent longitude and latitude (in that order), or a two-element numeric vector where the first column represents longitude and the second latitude. Values of x will be extracted from the points in y. GVectors can be of types points, lines, or polygons.
Character vector: Name(s) of function(s) to apply to values. This is used when x is a GRaster and y is a lines or polygons GVector. The method(s) specified by fun will be applied to all cell values that overlap with each geometry (i.e., individual cell values will not be returned). Valid functions include:
"countNonNA": Number of overlapping cells.
"countNA": Number of overlapping NA cells.
"mean": Average.
"min": Minimum.
"max": Minimum.
"sum": Sum.
"range": Maximum - minimum.
"sd": Sample standard deviation (same as stats::sd()).
"sdpop": Population standard deviation.
"var": Sample variance (same as stats::var()).
"varpop": Population variance.
"cv": Coefficient of variation.
"cvpop": Population coefficient of variation.
"median": Median.
"quantile": Quantile; you can specify the quantile using the prob argument.
Numeric in the range from 0 to 1: Quantile which to calculate. The value of prob will be rounded to the nearest hundredth.
Logical: If TRUE (default), and y is a lines or polygons GVector, then account for potential overlap of geometries when extracting. This can be slow, so if you are sure geometries do not overlap, you can change this to FALSE. This argument is ignored if y is a points GVector.
Logical: If TRUE and y represents points, also return the coordinates of each point. Default is FALSE.
Logical (extracting from a raster): If TRUE (default) and x is a categorical GRaster, then return the category labels instead of the values.
Logical: If TRUE, display progress (will only function when extracting from points on a GRaster when the number of GRasters is large, or when extracting using a "points" GVector with lots of points).
Arguments to pass to project(). This is used only if extracting from a GRaster at locations specified by a GVector, and they have a different coordinate reference system. In this case, users should specify the wrap argument to project().
terra::extract(), and modules r.what and v.what in GRASS
if (grassStarted()) {
# Setup
library(sf)
library(terra)
# Example data: elevation raster and points vector
madElev <- fastData("madElev") # raster
madCover <- fastData("madCover") # categorical raster
madDypsis <- fastData("madDypsis") # points vector
madRivers <- fastData("madRivers") # lines vector
madCoast4 <- fastData("madCoast4") # polygons vector
# Convert to fasterRaster formats:
elev <- fast(madElev) # raster
cover <- fast(madCover) # categorical raster
dypsis <- fast(madDypsis) # points vector
rivers <- fast(madRivers) # lines vector
coast <- fast(madCoast4) # polygons vector
# Get values of elevation at points where Dypsis species are located:
extract(elev, dypsis, xy = TRUE)
# Extract from categorical raster at points:
categories <- extract(cover, dypsis)
categoryValues <- extract(cover, dypsis, cats = FALSE)
categories
categoryValues
# Extract and summarize values on a raster across polygons:
extract(elev, coast, fun = c("sum", "mean", "countNonNA"), overlap = FALSE)
# Extract and summarize values on a raster across lines:
extract(elev, rivers, fun = c("sum", "mean", "countNonNA"), overlap = FALSE)
# Extract from a polygons vector at a points vector:
polysFromPoints <- extract(coast, dypsis, xy = TRUE)
head(polysFromPoints) # first 3 are outside polygons vector, next 3 are inside
}
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