sp (version 1.2-0)

over-methods: consistent spatial overlay for points, grids and polygons

Description

consistent spatial overlay for points, grids and polygons: at the spatial locations of object x retrieves the indexes or attributes from spatial object y

Usage

over(x, y, returnList = FALSE, fn = NULL, ...)
x %over% y

Arguments

x
geometry (locations) of the queries
y
layer from which the geometries or attributes are queried
returnList
logical; see value
fn
(optional) a function; see value
...
arguments passed on to function fn

Value

  • If y is only geometry an object of length length(x). If returnList is FALSE, a vector with the (first) index of y for each geometry (point, grid cell centre, polygon or lines) matching x. if returnList is TRUE, a list of length length(x), with list element i the vector of all indices of the geometries in y that correspond to the $i$-th geometry in x.

    If y has attribute data, attribute data are returned. returnList is FALSE, a data.frame with number of rows equal to length(x) is returned, if it is TRUE a list with length(x) elements is returned, with a list element the data.frame elements of all geometries in y that correspond to that element of x.

    In case the rgeos over methods are used, matching is done by gRelate, which uses DE-9IM (https://en.wikipedia.org/wiki/DE-9IM). From the string returned, characters 1, 2, 4 and 5 are used, indicating the dimension of the overlap of the inner and boundary of each x geometry with the inner and boundary of each y geometry. The order in which matched y geometries are returned is determined by the dimension of the overlap (2: area overlap, 1: line in common, 0: point in common), and then by the position in the string (1, 2, 4, 5, meaning points in polygons are prefered over points on polygon boundaries).

See Also

vignette("over") for examples and figures; point.in.polygon, package gIntersects

Examples

Run this code
r1 = cbind(c(180114, 180553, 181127, 181477, 181294, 181007, 180409, 
180162, 180114), c(332349, 332057, 332342, 333250, 333558, 333676, 
332618, 332413, 332349))
r2 = cbind(c(180042, 180545, 180553, 180314, 179955, 179142, 179437, 
179524, 179979, 180042), c(332373, 332026, 331426, 330889, 330683, 
331133, 331623, 332152, 332357, 332373))
r3 = cbind(c(179110, 179907, 180433, 180712, 180752, 180329, 179875, 
179668, 179572, 179269, 178879, 178600, 178544, 179046, 179110),
c(331086, 330620, 330494, 330265, 330075, 330233, 330336, 330004, 
329783, 329665, 329720, 329933, 330478, 331062, 331086))
r4 = cbind(c(180304, 180403,179632,179420,180304),
c(332791, 333204, 333635, 333058, 332791))

sr1=Polygons(list(Polygon(r1)),"r1")
sr2=Polygons(list(Polygon(r2)),"r2")
sr3=Polygons(list(Polygon(r3)),"r3")
sr4=Polygons(list(Polygon(r4)),"r4")
sr=SpatialPolygons(list(sr1,sr2,sr3,sr4))
srdf=SpatialPolygonsDataFrame(sr, data.frame(cbind(1:4,5:2), 
	row.names=c("r1","r2","r3","r4")))

data(meuse)
coordinates(meuse) = ~x+y

# plot(meuse)
polygon(r1)
polygon(r2)
polygon(r3)
polygon(r4)
# retrieve mean heavy metal concentrations per polygon:
over(sr, meuse[,1:4], fn = mean)

# return the number of points in each polygon:
sapply(over(sr, geometry(meuse), returnList = TRUE), length)

data(meuse.grid)
coordinates(meuse.grid) = ~x+y
gridded(meuse.grid) = TRUE

over(sr, geometry(meuse))
over(sr, meuse)
over(sr, geometry(meuse), returnList = TRUE)
over(sr, meuse, returnList = TRUE)

over(meuse, sr)
over(meuse, srdf)

# same thing, with grid:
over(sr, meuse.grid)
over(sr, meuse.grid, fn = mean)
over(sr, meuse.grid, returnList = TRUE)

over(meuse.grid, sr)
over(meuse.grid, srdf, fn = mean)
over(as(meuse.grid, "SpatialPoints"), sr)
over(as(meuse.grid, "SpatialPoints"), srdf)

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