sp (version 1.4-7)

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


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


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



geometry (locations) of the queries


layer from which the geometries or attributes are queried


logical; see value


(optional) a function; see value


arguments passed on to function fn, except for the special argument minDimension: minimal dimension for an intersection to be counted; -1 takes any intersection, and does not order; 0 takes any intersection but will order according to dimensionality of the intersections (if returnList is TRUE, 1 (2) selects intersections with dimension 1, meaning lines (2, meaning areas); see vignette("over") for details


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 preferred over points on polygon boundaries).


x = "SpatialPoints", y = "SpatialPolygons"

returns a numeric vector of length equal to the number of points; the number is the index (number) of the polygon of y in which a point falls; NA denotes the point does not fall in a polygon; if a point falls in multiple polygons, the last polygon is recorded.

x = "SpatialPointsDataFrame", y = "SpatialPolygons"

equal to the previous method, except that an argument fn=xxx is allowed, e.g. fn = mean which will then report a data.frame with the mean attribute values of the x points falling in each polygon (set) of y

x = "SpatialPoints", y = "SpatialPolygonsDataFrame"

returns a data.frame of the second argument with row entries corresponding to the first argument

x = "SpatialPolygons", y = "SpatialPoints"

returns the polygon index of points in y; if x is a SpatialPolygonsDataFrame, a data.frame with rows from x corresponding to points in y is returned.

x = "SpatialGridDataFrame", y = "SpatialPoints"

returns object of class SpatialPointsDataFrame with grid attribute values x at spatial point locations y; NA for NA grid cells or points outside grid, and NA values on NA grid cells.

x = "SpatialGrid", y = "SpatialPoints"

returns grid values x at spatial point locations y; NA for NA grid cells or points outside the grid

x = "SpatialPixelsDataFrame", y = "SpatialPoints"

returns grid values x at spatial point locations y; NA for NA grid cells or points outside the grid

x = "SpatialPixels", y = "SpatialPoints"

returns grid values x at spatial point locations y; NA for NA grid cells or points outside the grid

x = "SpatialPoints", y = "SpatialGrid"


x = "SpatialPoints", y = "SpatialGridDataFrame"


x = "SpatialPoints", y = "SpatialPixels"


x = "SpatialPoints", y = "SpatialPixelsDataFrame"


x = "SpatialPolygons", y = "SpatialGridDataFrame"


See Also

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


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))

srdf=SpatialPolygonsDataFrame(sr, data.frame(cbind(1:4,5:2), 

coordinates(meuse) = ~x+y

# 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)

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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