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Version:	1.0-23
Title:	Simple Features for R
Description:	Support for simple feature access, a standardized way to encode and analyze spatial vector data. Binds to 'GDAL' <doi:10.5281/zenodo.5884351> for reading and writing data, to 'GEOS' <doi:10.5281/zenodo.11396894> for geometrical operations, and to 'PROJ' <doi:10.5281/zenodo.5884394> for projection conversions and datum transformations. Uses by default the 's2' package for geometry operations on geodetic (long/lat degree)coordinates.
License:	GPL-2 |MIT + file LICENSE
URL:	https://r-spatial.github.io/sf/,https://github.com/r-spatial/sf
BugReports:	https://github.com/r-spatial/sf/issues
Depends:	methods, R (≥ 3.3.0)
Imports:	classInt (≥ 0.4-1), DBI (≥ 0.8), graphics, grDevices, grid,magrittr, s2 (≥ 1.1.0), stats, tools, units (≥ 0.7-0), utils
Suggests:	blob, nanoarrow, covr, dplyr (≥ 1.0.0), ggplot2, knitr,lwgeom (≥ 0.2-14), maps, mapview, Matrix, microbenchmark,odbc, pbapply, pillar, pool, raster, rlang, rmarkdown,RPostgres (≥ 1.1.0), RPostgreSQL, RSQLite, sp (≥ 1.2-4),spatstat (≥ 2.0-1), spatstat.geom, spatstat.random,spatstat.linnet, spatstat.utils, stars (≥ 0.6-0), terra,testthat (≥ 3.0.0), tibble (≥ 1.4.1), tidyr (≥ 1.2.0),tidyselect (≥ 1.0.0), tmap (≥ 2.0), vctrs, wk (≥ 0.9.0)
LinkingTo:	Rcpp
VignetteBuilder:	knitr
Encoding:	UTF-8
RoxygenNote:	7.3.3
Config/testthat/edition:	2
Config/needs/coverage:	XML
SystemRequirements:	GDAL (>= 2.0.1), GEOS (>= 3.4.0), PROJ (>= 4.8.0),sqlite3
Collate:	'RcppExports.R' 'init.R' 'import-standalone-s3-register.R''crs.R' 'bbox.R' 'read.R' 'db.R' 'sfc.R' 'sfg.R' 'sf.R''bind.R' 'wkb.R' 'wkt.R' 'plot.R' 'geom-measures.R''geom-predicates.R' 'geom-transformers.R' 'transform.R''proj.R' 'sp.R' 'grid.R' 'arith.R' 'tidyverse.R''tidyverse-vctrs.R' 'cast_sfg.R' 'cast_sfc.R' 'graticule.R''datasets.R' 'aggregate.R' 'agr.R' 'maps.R' 'join.R' 'sample.R''valid.R' 'collection_extract.R' 'jitter.R' 'sgbp.R''spatstat.R' 'stars.R' 'crop.R' 'gdal_utils.R' 'nearest.R''normalize.R' 'sf-package.R' 'defunct.R' 'z_range.R''m_range.R' 'shift_longitude.R' 'make_grid.R' 's2.R' 'terra.R''geos-overlayng.R' 'break_antimeridian.R'
NeedsCompilation:	yes
Packaged:	2025-11-24 20:56:30 UTC; edzer
Author:	Edzer Pebesma [aut, cre], Roger Bivand [ctb], Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb], Kirill Müller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [ctb], Dewey Dunnington [ctb]
Maintainer:	Edzer Pebesma <edzer.pebesma@uni-muenster.de>
Repository:	CRAN
Date/Publication:	2025-11-28 10:50:02 UTC

sf: Simple Features for R

Description

Support for simple feature access, a standardized way to encode and analyze spatial vector data. Binds to 'GDAL'doi:10.5281/zenodo.5884351 for reading and writing data, to 'GEOS'doi:10.5281/zenodo.11396894 for geometrical operations, and to 'PROJ'doi:10.5281/zenodo.5884394 for projection conversions and datum transformations. Uses by default the 's2' package for geometry operations on geodetic (long/lat degree) coordinates.

Author(s)

Maintainer: Edzer Pebesmaedzer.pebesma@uni-muenster.de (ORCID)

Other contributors:

• Roger Bivand (ORCID) [contributor]

• Etienne Racine [contributor]

• Michael Sumner [contributor]

• Ian Cook [contributor]

• Tim Keitt [contributor]

• Robin Lovelace [contributor]

• Hadley Wickham [contributor]

• Jeroen Ooms (ORCID) [contributor]

• Kirill Müller [contributor]

• Thomas Lin Pedersen [contributor]

• Dan Baston [contributor]

• Dewey Dunnington (ORCID) [contributor]

References

Pebesma, E. and Bivand, R. (2023). Spatial DataScience: With Applications in R. Chapman and Hall/CRC.doi:10.1201/9780429459016 which is also found freelyonline athttps://r-spatial.org/book/

Pebesma, E., 2018. Simple Features for R: Standardized Supportfor Spatial Vector Data. The R Journal 10 (1), 439-446,doi:10.32614/RJ-2018-009 (open access)

See Also

Useful links:

• https://r-spatial.github.io/sf/

• https://github.com/r-spatial/sf

• Report bugs athttps://github.com/r-spatial/sf/issues

Internal functions

Description

Internal functions

Usage

.stop_geos(msg)

Arguments

Arithmetic operators for simple feature geometries

Description

Arithmetic operators for simple feature geometries

Usage

## S3 method for class 'sfg'Ops(e1, e2)## S3 method for class 'sfc'Ops(e1, e2)

Arguments

Details

in casee2 is numeric, +, -, *, /, %% and %/% add, subtract, multiply, divide, modulo, or integer-divide bye2. In casee2 is an n x n matrix, * matrix-multiplies and / multiplies by its inverse. Ife2 is ansfg object, |, /, & and %/% result in the geometric union, difference, intersection and symmetric difference respectively, and== and!= return geometric (in)equality, usingst_equals. Ife2 is ansfg orsfc object, for operations+ and- it has to havePOINT geometries.

Ife1 is of classsfc, ande2 is a length 2 numeric, then it is considered a two-dimensional point (and if needed repeated as such) only for operations+ and-, in other cases the individual numbers are repeated; see commented examples.

It has been reported (https://github.com/r-spatial/sf/issues/2067) thatcertain ATLAS versions result in invalid polygons, where the final pointin a ring is no longer equal to the first point. In that case, settingthe precisions withst_set_precision may help.

Value

object of classsfg

Examples

st_point(c(1,2,3)) + 4st_point(c(1,2,3)) * 3 + 4m = matrix(0, 2, 2)diag(m) = c(1, 3)# affine:st_point(c(1,2)) * m + c(2,5)# world in 0-360 range:if (require(maps, quietly = TRUE)) { w = st_as_sf(map('world', plot = FALSE, fill = TRUE)) w2 = (st_geometry(w) + c(360,90)) %% c(360) - c(0,90) w3 = st_wrap_dateline(st_set_crs(w2 - c(180,0), 4326)) + c(180,0) plot(st_set_crs(w3, 4326), axes = TRUE)}(mp <- st_point(c(1,2)) + st_point(c(3,4))) # MULTIPOINT (1 2, 3 4)mp - st_point(c(3,4)) # POINT (1 2)opar = par(mfrow = c(2,2), mar = c(0, 0, 1, 0))a = st_buffer(st_point(c(0,0)), 2)b = a + c(2, 0)p = function(m) { plot(c(a,b)); plot(eval(parse(text=m)), col=grey(.9), add = TRUE); title(m) }o = lapply(c('a | b', 'a / b', 'a & b', 'a %/% b'), p)par(opar)sfc = st_sfc(st_point(0:1), st_point(2:3))sfc + c(2,3) # added to EACH geometrysfc * c(2,3) # first geometry multiplied by 2, second by 3nc = st_transform(st_read(system.file("gpkg/nc.gpkg", package="sf")), 32119) # nc state plane, mb = st_buffer(st_centroid(st_union(nc)), units::set_units(50, km)) # shoot a hole in nc:plot(st_geometry(nc) / b, col = grey(.9))

aggregate ansf object

Description

aggregate ansf object, possibly union-ing geometries

Usage

## S3 method for class 'sf'aggregate(  x,  by,  FUN,  ...,  do_union = TRUE,  simplify = TRUE,  join = st_intersects)

Arguments

Details

In casedo_union isFALSE,aggregate will simply combine geometries usingc.sfg. When polygons sharing a boundary are combined, this leads to geometries that are invalid; seehttps://github.com/r-spatial/sf/issues/681.

Value

ansf object with aggregated attributes and geometries; additional grouping variables having the names ofnames(ids) or are namedGroup.i forids[[i]]; seeaggregate.

Note

Does not work using the formula notation involving~ defined inaggregate.

Examples

m1 = cbind(c(0, 0, 1, 0), c(0, 1, 1, 0))m2 = cbind(c(0, 1, 1, 0), c(0, 0, 1, 0))pol = st_sfc(st_polygon(list(m1)), st_polygon(list(m2)))set.seed(1985)d = data.frame(matrix(runif(15), ncol = 3))p = st_as_sf(x = d, coords = 1:2)plot(pol)plot(p, add = TRUE)(p_ag1 = aggregate(p, pol, mean))plot(p_ag1) # geometry same as pol# works when x overlaps multiple objects in 'by':p_buff = st_buffer(p, 0.2)plot(p_buff, add = TRUE)(p_ag2 = aggregate(p_buff, pol, mean)) # increased mean of second# with non-matching featuresm3 = cbind(c(0, 0, -0.1, 0), c(0, 0.1, 0.1, 0))pol = st_sfc(st_polygon(list(m3)), st_polygon(list(m1)), st_polygon(list(m2)))(p_ag3 = aggregate(p, pol, mean))plot(p_ag3)# In case we need to pass an argument to the join function:(p_ag4 = aggregate(p, pol, mean,      join = function(x, y) st_is_within_distance(x, y, dist = 0.3)))

Methods to coerce simple features to⁠Spatial*⁠ andSpatial*DataFrame objects

Description

as_Spatial() allows to convertsf andsfc toSpatial*DataFrame and⁠Spatial*⁠ forsp compatibility. You can also useas(x, "Spatial") To transformsp objects tosf andsfc withas(x, "sf").

Usage

as_Spatial(from, cast = TRUE, IDs = paste0("ID", seq_along(from)))

Arguments

Details

Packagesp supports three dimensions forPOINT andMULTIPOINT (⁠SpatialPoint*⁠).Other geometries must be two-dimensional (XY). Dimensions can be dropped usingst_zm() withwhat = "M" orwhat = "ZM".

For converting simple features (i.e.,sf objects) to theirSpatial counterpart, useas(obj, "Spatial")

Value

geometry-only object deriving fromSpatial, of the appropriate class

Examples

nc <- st_read(system.file("shape/nc.shp", package="sf"))if (require(sp, quietly = TRUE)) {# convert to SpatialPolygonsDataFramespdf <- as_Spatial(nc)# identical tospdf <- as(nc, "Spatial")# convert to SpatialPolygonsas(st_geometry(nc), "Spatial")# back to sfas(spdf, "sf")}

Bind rows (features) of sf objects

Description

Bind rows (features) of sf objects

Bind columns (variables) of sf objects

Usage

## S3 method for class 'sf'rbind(..., deparse.level = 1)## S3 method for class 'sf'cbind(..., deparse.level = 1, sf_column_name = NULL)st_bind_cols(...)

Arguments

Details

bothrbind andcbind have non-standard method dispatch (seecbind): therbind orcbind method forsf objects is only called when all arguments to be binded are of classsf.

If you need tocbind e.g. adata.frame to ansf, usedata.frame directly and usest_sf on its result, or usebind_cols; see examples.

st_bind_cols is deprecated; usecbind instead.

Value

cbind called with multiplesf objects warns about multiple geometry columns present when the geometry column to use is not specified by using argumentsf_column_name; see alsost_sf.

Examples

crs = st_crs(3857)a = st_sf(a=1, geom = st_sfc(st_point(0:1)), crs = crs)b = st_sf(a=1, geom = st_sfc(st_linestring(matrix(1:4,2))), crs = crs)c = st_sf(a=4, geom = st_sfc(st_multilinestring(list(matrix(1:4,2)))), crs = crs)rbind(a,b,c)rbind(a,b)rbind(a,b)rbind(b,c)cbind(a,b,c) # warnsif (require(dplyr, quietly = TRUE))  dplyr::bind_cols(a,b)c = st_sf(a=4, geomc = st_sfc(st_multilinestring(list(matrix(1:4,2)))), crs = crs)cbind(a,b,c, sf_column_name = "geomc")df = data.frame(x=3)st_sf(data.frame(c, df))if (require(dplyr, quietly = TRUE))  dplyr::bind_cols(c, df)

Determine database type for R vector

Description

Determine database type for R vector

Determine database type for R vector

Usage

## S4 method for signature 'PostgreSQLConnection,sf'dbDataType(dbObj, obj)## S4 method for signature 'DBIObject,sf'dbDataType(dbObj, obj)

Arguments

Writesf object to Database

Description

Writesf object to Database

Writesf object to Database

Usage

## S4 method for signature 'PostgreSQLConnection,character,sf'dbWriteTable(  conn,  name,  value,  ...,  row.names = FALSE,  overwrite = FALSE,  append = FALSE,  field.types = NULL,  binary = TRUE)## S4 method for signature 'DBIObject,character,sf'dbWriteTable(  conn,  name,  value,  ...,  row.names = FALSE,  overwrite = FALSE,  append = FALSE,  field.types = NULL,  binary = TRUE)

Arguments

Drivers for which update should beTRUE by default

Description

Drivers for which update should beTRUE by default

Usage

db_drivers

Format

An object of classcharacter of length 12.

Map extension to driver

Description

Map extension to driver

Usage

extension_map

Format

An object of classlist of length 26.

functions to interact with gdal not meant to be called directly by users (but e.g. by stars::read_stars)

Description

functions to interact with gdal not meant to be called directly by users (but e.g. by stars::read_stars)

Usage

gdal_read(  x,  ...,  options = character(0),  driver = character(0),  read_data = TRUE,  NA_value = NA_real_,  RasterIO_parameters = list())gdal_write(  x,  ...,  file,  driver = "GTiff",  options = character(0),  type = "Float32",  NA_value = NA_real_,  geotransform,  update = FALSE,  scale_offset = c(1, 0))gdal_inv_geotransform(gt)gdal_crs(file, options = character(0))gdal_metadata(  file,  domain_item = character(0),  options = character(0),  parse = TRUE)gdal_subdatasets(file, options = character(0), name = TRUE)gdal_polygonize(  x,  mask = NULL,  file = tempfile(),  driver = "GTiff",  use_integer = TRUE,  geotransform,  breaks = classInt::classIntervals(na.omit(as.vector(x[[1]])))$brks,  use_contours = FALSE,  contour_lines = FALSE,  connect8 = FALSE,  ...)gdal_rasterize(sf, x, gt, file, driver = "GTiff", options = character())gdal_extract(  f,  pts,  resampling = c("nearest", "bilinear", "cubic", "cubicspline"))gdal_read_mdim(  file,  array_name = character(0),  options = character(0),  offset = integer(0),  count = integer(0),  step = integer(0),  proxy = FALSE,  debug = FALSE)gdal_write_mdim(  file,  driver,  dimx,  cdl,  wkt,  xy,  ...,  root_group_options = character(0),  options = character(0),  as_float = TRUE)gdal_create(f, nxy, values, crs, xlim, ylim)

Arguments

Details

These functions are exported for the single purpose of being used by package stars, they are not meant to be used directly and may change or disappear without prior notice or deprecation warnings.

gdal_inv_geotransform returns the inverse geotransform

gdal_crs reads coordinate reference system from GDAL data set

get_metadata gets metadata of a raster layer

gdal_subdatasets returns the subdatasets of a gdal dataset

Value

object of classcrs, seest_crs.

named list with metadata items

gdal_subdatasets returns a zero-length list iffile does not have subdatasets, and else a named list with subdatasets.

Examples

## Not run:   f = system.file("tif/L7_ETMs.tif", package="stars")  f = system.file("nc/avhrr-only-v2.19810901.nc", package = "stars")  gdal_metadata(f)  gdal_metadata(f, NA_character_)  try(gdal_metadata(f, "wrongDomain"))  gdal_metadata(f, c("", "AREA_OR_POINT"))## End(Not run)

Add or remove overviews to/from a raster image

Description

add or remove overviews to/from a raster image

Usage

gdal_addo(  file,  overviews = c(2, 4, 8, 16),  method = "NEAREST",  layers = integer(0),  options = character(0),  config_options = character(0),  clean = FALSE,  read_only = FALSE)

Arguments

Value

TRUE, invisibly, on success

See Also

gdal_utils for access to other gdal utilities that have a C API

Native interface to gdal utils

Description

Native interface to gdal utils

Usage

gdal_utils(  util = "info",  source,  destination,  options = character(0),  quiet = !(util %in% c("info", "gdalinfo", "ogrinfo", "vectorinfo", "mdiminfo")) ||    ("-multi" %in% options),  processing = character(0),  colorfilename = character(0),  config_options = character(0),  read_only = FALSE)

Arguments

Value

info returns a character vector with the raster metadata; all other utils return (invisibly) a logical indicating success (i.e.,TRUE); in case of failure, an error is raised.

See Also

gdal_addo for adding overlays to a raster file;st_layers to query geometry type(s) and crs from layers in a (vector) data source

Examples

if (compareVersion(sf_extSoftVersion()["GDAL"], "2.1.0") == 1) {# info utils can be used to list information about a raster# dataset. More info: https://gdal.org/programs/gdalinfo.htmlin_file <- system.file("tif/geomatrix.tif", package = "sf")gdal_utils("info", in_file, options = c("-mm", "-proj4"))# vectortranslate utils can be used to convert simple features data between# file formats. More info: https://gdal.org/programs/ogr2ogr.htmlin_file <- system.file("shape/storms_xyz.shp", package="sf")out_file <- paste0(tempfile(), ".gpkg")gdal_utils(  util = "vectortranslate",  source = in_file,  destination = out_file, # output format must be specified for GDAL < 2.3  options = c("-f", "GPKG"))# The parameters can be specified as c("name") or c("name", "value"). The# vectortranslate utils can perform also various operations during the# conversion process. For example, we can reproject the features during the# translation.gdal_utils(  util = "vectortranslate",  source = in_file,  destination = out_file,  options = c(  "-f", "GPKG", # output file format for GDAL < 2.3  "-s_srs", "EPSG:4326", # input file SRS  "-t_srs", "EPSG:2264", # output file SRS  "-overwrite"  ))st_read(out_file)# The parameter s_srs had to be specified because, in this case, the in_file# has no associated SRS.st_read(in_file)}

Geometric operations on pairs of simple feature geometry sets

Description

Perform geometric set operations with simple feature geometry collections

Usage

st_intersection(x, y, ...)## S3 method for class 'sfc'st_intersection(x, y, ...)## S3 method for class 'sf'st_intersection(x, y, ...)st_difference(x, y, ...)## S3 method for class 'sfc'st_difference(x, y, ...)st_sym_difference(x, y, ...)st_snap(x, y, tolerance)

Arguments

Details

When using GEOS and not using s2, a spatial index is built on argumentx; seehttps://r-spatial.org/r/2017/06/22/spatial-index.html. The reference for the STR tree algorithm is: Leutenegger, Scott T., Mario A. Lopez, and Jeffrey Edgington. "STR: A simple and efficient algorithm for R-tree packing." Data Engineering, 1997. Proceedings. 13th international conference on. IEEE, 1997. For the pdf, search Google Scholar.

When called with missingy, thesfc method forst_intersection returns all non-empty intersections of the geometries ofx; an attributeidx contains a list-column with the indexes of contributing geometries.

when called with a missingy, thesf method forst_intersection returns ansf object with attributes taken from the contributing feature with lowest index; two fields are added:n.overlaps with the number of overlapping features inx, and a list-columnorigins with indexes of all overlapping features.

Whenst_difference is called with a single argument,overlapping areas are erased from geometries that are indexed at greaternumbers in the argument tox; geometries that are emptyor contained fully inside geometries with higher priority are removed entirely.Thest_difference.sfc method with a single argument returns an object withan"idx" attribute with the original index for returned geometries.

st_snap snaps the vertices and segments of a geometry to another geometry's vertices. Ify contains more than one geometry, its geometries are merged into a collection before snapping to that collection.

(from the GEOS docs:) "A snap distance tolerance is used to control where snapping is performed. Snapping one geometry to another can improve robustness for overlay operations by eliminating nearly-coincident edges (which cause problems during noding and intersection calculation). Too much snapping can result in invalid topology being created, so the number and location of snapped vertices is decided using heuristics to determine when it is safe to snap. This can result in some potential snaps being omitted, however."

Value

The intersection, difference or symmetric difference between two sets of geometries.The returned object has the same class as that of the first argument (x) with the non-empty geometries resulting from applying the operation to all geometry pairs inx andy. In casex is of classsf, the matching attributes of the original object(s) are added. Thesfc geometry list-column returned carries an attributeidx, which is ann-by-2 matrix with every row the index of the corresponding entries ofx andy, respectively.

Note

To find whether pairs of simple feature geometries intersect, usethe functionst_intersects instead ofst_intersection.

When using GEOS and not using s2 polygons contain their boundary. When using s2 this is determined by themodel defaults ofs2_options, which can be overridden via the ... argument, e.g.model = "closed" to force DE-9IM compliant behaviour of polygons (and reproduce GEOS results).

See Also

st_union for the union of simple features collections;intersect andsetdiff for the base R set operations.

Examples

set.seed(131)library(sf)m = rbind(c(0,0), c(1,0), c(1,1), c(0,1), c(0,0))p = st_polygon(list(m))n = 100l = vector("list", n)for (i in 1:n)  l[[i]] = p + 10 * runif(2)s = st_sfc(l)plot(s, col = sf.colors(categorical = TRUE, alpha = .5))title("overlapping squares")d = st_difference(s) # sequential differences: s1, s2-s1, s3-s2-s1, ...plot(d, col = sf.colors(categorical = TRUE, alpha = .5))title("non-overlapping differences")i = st_intersection(s) # all intersectionsplot(i, col = sf.colors(categorical = TRUE, alpha = .5))title("non-overlapping intersections")summary(lengths(st_overlaps(s, s))) # includes self-counts!summary(lengths(st_overlaps(d, d)))summary(lengths(st_overlaps(i, i)))sf = st_sf(s)i = st_intersection(sf) # all intersectionsplot(i["n.overlaps"])summary(i$n.overlaps - lengths(i$origins))# A helper function that erases all of y from x:st_erase = function(x, y) st_difference(x, st_union(st_combine(y)))poly = st_polygon(list(cbind(c(0, 0, 1, 1, 0), c(0, 1, 1, 0, 0))))lines = st_multilinestring(list( cbind(c(0, 1), c(1, 1.05)), cbind(c(0, 1), c(0, -.05)), cbind(c(1, .95, 1), c(1.05, .5, -.05))))snapped = st_snap(poly, lines, tolerance=.1)plot(snapped, col='red')plot(poly, border='green', add=TRUE)plot(lines, lwd=2, col='blue', add=TRUE)

Geometric binary predicates on pairs of simple feature geometry sets

Description

Geometric binary predicates on pairs of simple feature geometry sets

Usage

st_intersects(x, y, sparse = TRUE, ...)st_disjoint(x, y = x, sparse = TRUE, prepared = TRUE, ...)st_touches(x, y, sparse = TRUE, prepared = TRUE, ...)st_crosses(x, y, sparse = TRUE, prepared = TRUE, ...)st_within(x, y, sparse = TRUE, prepared = TRUE, ...)st_contains(x, y, sparse = TRUE, prepared = TRUE, ..., model = "open")st_contains_properly(x, y, sparse = TRUE, prepared = TRUE, ...)st_overlaps(x, y, sparse = TRUE, prepared = TRUE, ...)st_equals(  x,  y,  sparse = TRUE,  prepared = FALSE,  ...,  retain_unique = FALSE,  remove_self = FALSE)st_covers(x, y, sparse = TRUE, prepared = TRUE, ..., model = "closed")st_covered_by(x, y = x, sparse = TRUE, prepared = TRUE, ..., model = "closed")st_equals_exact(x, y, par, sparse = TRUE, prepared = FALSE, ...)st_is_within_distance(x, y = x, dist, sparse = TRUE, ..., remove_self = FALSE)

Arguments

Details

Ifprepared isTRUE, andx contains POINT geometries andy contains polygons, then the polygon geometries are prepared, rather than the points.

For most predicates, a spatial index is built on argumentx; seehttps://r-spatial.org/r/2017/06/22/spatial-index.html.Specifically,st_intersects,st_disjoint,st_touchesst_crosses,st_within,st_contains,st_contains_properly,st_overlaps,st_equals,st_covers andst_covered_by all build spatial indexes for more efficient geometry calculations.st_relate,st_equals_exact, and do not;st_is_within_distance uses a spatial index for geographic coordinates whensf_use_s2() is true.

Ify is missing,st_predicate(x, x) is effectively called, and a square matrix is returned with diagonal elementsst_predicate(x[i], x[i]).

Sparse geometry binary predicate (sgbp) lists have the following attributes:region.id with therow.names ofx (if any, else1:n),ncol with the number of features iny, andpredicate with the name of the predicate used.

formodel, see https://github.com/r-spatial/s2/issues/32

st_contains_properly(A,B) is true if A intersects B's interior, but not its edges or exterior; A contains A, but A does not properly contain A.

See alsost_relate andhttps://en.wikipedia.org/wiki/DE-9IM for a more detailed description of the underlying algorithms.

st_equals_exact returns true for two geometries of the same type and their vertices corresponding by index are equal up to a specified tolerance.

Value

Ifsparse=FALSE,st_predicate (withpredicate e.g. "intersects") returns a dense logical matrix with elementi,j equal toTRUE whenpredicate(x[i], y[j]) (e.g., when geometry of feature i and j intersect); ifsparse=TRUE, an object of classsgbp is returned, which is a sparse list representation of the same matrix, with list elementi an integer vector with all indicesj for whichpredicate(x[i],y[j]) isTRUE (and hence a zero-length integer vector if none of them isTRUE). From the dense matrix, one can find out if one or more elements intersect byapply(mat, 1, any), and from the sparse list bylengths(lst) > 0, see examples below.

Note

For intersection on pairs of simple feature geometries, usethe functionst_intersection instead ofst_intersects.

Examples

pts = st_sfc(st_point(c(.5,.5)), st_point(c(1.5, 1.5)), st_point(c(2.5, 2.5)))pol = st_polygon(list(rbind(c(0,0), c(2,0), c(2,2), c(0,2), c(0,0))))(lst = st_intersects(pts, pol))(mat = st_intersects(pts, pol, sparse = FALSE))# which points fall inside a polygon?apply(mat, 1, any)lengths(lst) > 0# which points fall inside the first polygon?st_intersects(pol, pts)[[1]]# remove duplicate geometries:p1 = st_point(0:1)p2 = st_point(2:1)p = st_sf(a = letters[1:8], geom = st_sfc(p1, p1, p2, p1, p1, p2, p2, p1))st_equals(p)st_equals(p, remove_self = TRUE)(u = st_equals(p, retain_unique = TRUE))# retain the records with unique geometries:p[-unlist(u),]

Combine or union feature geometries

Description

Combine several feature geometries into one, without unioning or resolving internal boundaries

Usage

st_combine(x)st_union(x, y, ..., by_feature = FALSE, is_coverage = FALSE)

Arguments

Details

st_combine combines geometries without resolving borders, usingc.sfg (analogous toc for ordinary vectors).

Ifst_union is called with a single argument,x, (withy missing) andby_feature isFALSE all geometries are unioned together and ansfg or single-geometrysfc object is returned.Ifby_feature isTRUE each feature geometry is unioned individually.This can for instance be used to resolve internal boundaries after polygons were combined usingst_combine.Ify is provided, all elements ofx andy are unioned, pairwise ifby_feature is TRUE, or else as the Cartesian product of both sets.

Unioning a set of overlapping polygons has the effect of merging the areas (i.e. the same effect as iteratively unioning all individual polygons together).Unioning a set of LineStrings has the effect of fully noding and dissolving the input linework. In this context "fully noded" means that there will be a node or endpoint in the output for every endpoint or line segment crossing in the input."Dissolved" means that any duplicate (e.g. coincident) line segments or portions of line segments will be reduced to a single line segment in the output.Unioning a set of Points has the effect of merging all identical points (producing a set with no duplicates).

Value

st_combine returns a single, combined geometry, with no resolved boundaries; returned geometries may well be invalid.

Ify is missing,st_union(x) returns a single geometry with resolved boundaries, else the geometries for all unioned pairs ofx[i] andy[j].

See Also

st_intersection,st_difference,st_sym_difference

Examples

nc = st_read(system.file("shape/nc.shp", package="sf"))st_combine(nc)plot(st_union(nc))

Compute geometric measurements

Description

Compute Euclidean or great circle distance between pairs of geometries; compute, the area or the length of a set of geometries.

Usage

st_area(x, ...)## S3 method for class 'sfc'st_area(x, ...)st_length(x, ...)st_perimeter(x, ...)st_distance(  x,  y,  ...,  dist_fun,  by_element = FALSE,  which = ifelse(isTRUE(st_is_longlat(x)), "Great Circle", "Euclidean"),  par = 0,  tolerance = 0)

Arguments

Details

great circle distance calculations use by default spherical distances (s2_distance ors2_distance_matrix); ifsf_use_s2() isFALSE, ellipsoidal distances are computed usingst_geod_distance which uses functiongeod_inverse from GeographicLib (part of PROJ); see Karney, Charles FF, 2013, Algorithms for geodesics, Journal of Geodesy 87(1), 43–55

Value

If the coordinate reference system ofx was set, these functions return values with unit of measurement; seeset_units.

st_area returns the area of each feature geometry, computed in the coordinate reference system used. In casex has geodetic coordinates (unprojected), then ifsf_use_s2() isFALSEst_geod_area is used for area calculation, if it isTRUE thens2_area is used: the former assumes an ellipsoidal shape, the latter a spherical shape of the Earth. In case of projected data, areas are computed in flat space. The argument... can be used to specifyradius tos2_area, to modify the Earth radius.

st_length returns the length of aLINESTRING orMULTILINESTRING geometry, using the coordinate reference system.POINT,MULTIPOINT,POLYGON orMULTIPOLYGON geometries return zero.

Ifby_element isFALSEst_distance returns a dense numeric matrix of dimension length(x) by length(y); otherwise it returns a numeric vector the same length asx andy with an error raised if the lengths ofx andy are unequal. Distances involving empty geometries areNA.

See Also

st_dimension,st_cast to convert geometry types

Examples

b0 = st_polygon(list(rbind(c(-1,-1), c(1,-1), c(1,1), c(-1,1), c(-1,-1))))b1 = b0 + 2b2 = b0 + c(-0.2, 2)x = st_sfc(b0, b1, b2)st_area(x)line = st_sfc(st_linestring(rbind(c(30,30), c(40,40))), crs = 4326)st_length(line)outer = matrix(c(0,0,10,0,10,10,0,10,0,0),ncol=2, byrow=TRUE)hole1 = matrix(c(1,1,1,2,2,2,2,1,1,1),ncol=2, byrow=TRUE)hole2 = matrix(c(5,5,5,6,6,6,6,5,5,5),ncol=2, byrow=TRUE)poly = st_polygon(list(outer, hole1, hole2))mpoly = st_multipolygon(list(list(outer, hole1, hole2),list(outer + 12, hole1 + 12)))st_length(st_sfc(poly, mpoly))st_perimeter(poly)st_perimeter(mpoly)p = st_sfc(st_point(c(0,0)), st_point(c(0,1)), st_point(c(0,2)))st_distance(p, p)st_distance(p, p, by_element = TRUE)

Dimension, simplicity, validity or is_empty queries on simple feature geometries

Description

Dimension, simplicity, validity or is_empty queries on simple feature geometries

Usage

st_dimension(x, NA_if_empty = TRUE)st_is_simple(x)st_is_empty(x)

Arguments

Value

st_dimension returns a numeric vector with 0 for points, 1 for lines, 2 for surfaces, and, ifNA_if_empty isTRUE,NA for empty geometries.

st_is_simple returns a logical vector, indicating for each geometry whether it is simple (e.g., not self-intersecting)

st_is_empty returns for each geometry whether it is empty

Examples

x = st_sfc(st_point(0:1),st_linestring(rbind(c(0,0),c(1,1))),st_polygon(list(rbind(c(0,0),c(1,0),c(0,1),c(0,0)))),st_multipoint(),st_linestring(),st_geometrycollection())st_dimension(x)st_dimension(x, FALSE)ls = st_linestring(rbind(c(0,0), c(1,1), c(1,0), c(0,1)))st_is_simple(st_sfc(ls, st_point(c(0,0))))ls = st_linestring(rbind(c(0,0), c(1,1), c(1,0), c(0,1)))st_is_empty(st_sfc(ls, st_point(), st_linestring()))

Geometric unary operations on simple feature geometry sets

Description

Geometric unary operations on simple feature geometries. These are all generics, with methods forsfg,sfc andsf objects, returning an object of the same class. All operations work on a per-feature basis, ignoring all other features.

Usage

st_buffer(  x,  dist,  nQuadSegs = 30,  endCapStyle = "ROUND",  joinStyle = "ROUND",  mitreLimit = 1,  singleSide = FALSE,  ...)st_boundary(x)st_convex_hull(x)st_concave_hull(x, ratio, ..., allow_holes)st_simplify(x, preserveTopology, dTolerance = 0)st_triangulate(x, dTolerance = 0, bOnlyEdges = FALSE)st_triangulate_constrained(x)st_inscribed_circle(x, dTolerance, ...)st_minimum_rotated_rectangle(x, ...)st_minimum_bounding_circle(x, ...)st_voronoi(  x,  envelope,  dTolerance = 0,  bOnlyEdges = FALSE,  point_order = FALSE)st_polygonize(x)st_line_merge(x, ..., directed = FALSE)st_centroid(x, ..., of_largest_polygon = FALSE)st_point_on_surface(x)st_reverse(x)st_node(x)st_segmentize(x, dfMaxLength, ...)st_exterior_ring(x, ...)

Arguments

Details

st_buffer computes a buffer around this geometry/each geometry. Depending on the spatialcoordinate system, a different engine (GEOS or S2) can be used, which have different functionarguments. ThenQuadSegs,endCapsStyle,joinStyle,mitreLimit andsingleSide parameters only work if the GEOS engine is used (i.e. projected coordinates orwhensf_use_s2() is set toFALSE). Seepostgis.net/docs/ST_Buffer.htmlfor details. Themax_cells andmin_level parameters (s2::s2_buffer_cells()) work with the S2engine (i.e. geographic coordinates) and can be used to change the buffer shape (e.g. smoothing).The S2 engine returns a polygonaround a number of S2 cells thatcontain the buffer, and hence will always have an area larger than thetrue buffer, depending onmax_cells, and will be non-smooth when sufficiently zoomed in.The GEOS engine will return line segments between pointson the circle, and so will always besmaller than the truebuffer, and be smooth, depending on the number of segmentsnQuadSegs.A negativedist value for geodetic coordinates using S2 does not give a proper (geodetic) buffer.

st_boundary returns the boundary of a geometry

st_convex_hull creates the convex hull of a set of points

st_concave_hull creates the concave hull of a geometry

st_simplify simplifies lines by removing vertices.

st_triangulate triangulates set of points (not constrained).st_triangulate requires GEOS version 3.4 or above

st_triangulate_constrained returns the constrained delaunay triangulation of polygons; requires GEOS version 3.10 or above

st_inscribed_circle returns the maximum inscribed circle for polygon geometries.Forst_inscribed_circle, ifnQuadSegs is 0 a 2-point LINESTRING is returned with thecenter point and a boundary point of every circle, otherwise a circle (buffer) is returned wherenQuadSegs controls the number of points per quadrant to approximate the circle.st_inscribed_circle requires GEOS version 3.9 or above

st_minimum_rotated_rectangle returns the minimumrotated rectangular POLYGON which encloses the input geometry. Therectangle has width equal to the minimum diameter, and a longerlength. If the convex hill of the input is degenerate (a line orpoint) a linestring or point is returned.

st_minimum_bounding_circlereturns a geometry which represents the "minimum bounding circle",the smallest circle that contains the input.

st_voronoi creates voronoi tessellation.st_voronoi requires GEOS version 3.5 or above

st_polygonize creates a polygon from lines that form a closed ring. In case ofst_polygonize,x must be an object of classLINESTRING orMULTILINESTRING, or ansfc geometry list-column object containing these

st_line_merge merges lines. In case ofst_line_merge,x must be an object of classMULTILINESTRING, or ansfc geometry list-column object containing these

st_centroid gives the centroid of a geometry

st_point_on_surface returns a point guaranteed to be on the (multi)surface.

st_reverse reverses the nodes in a line

st_node adds nodes to linear geometries at intersections without a node, and only works on individual linear geometries

st_segmentize adds points to straight lines

st_exterior_ring returns the exterior rings of polygons, removing all holes.

Value

an object of the same class ofx, with manipulated geometry.

See Also

chull for a more efficient algorithm for calculating the convex hull

Examples

## st_buffer, style options (taken from rgeos gBuffer)l1 = st_as_sfc("LINESTRING(0 0,1 5,4 5,5 2,8 2,9 4,4 6.5)")op = par(mfrow=c(2,3))plot(st_buffer(l1, dist = 1, endCapStyle="ROUND"), reset = FALSE, main = "endCapStyle: ROUND")plot(l1,col='blue',add=TRUE)plot(st_buffer(l1, dist = 1, endCapStyle="FLAT"), reset = FALSE, main = "endCapStyle: FLAT")plot(l1,col='blue',add=TRUE)plot(st_buffer(l1, dist = 1, endCapStyle="SQUARE"), reset = FALSE, main = "endCapStyle: SQUARE")plot(l1,col='blue',add=TRUE)plot(st_buffer(l1, dist = 1, nQuadSegs=1), reset = FALSE, main = "nQuadSegs: 1")plot(l1,col='blue',add=TRUE)plot(st_buffer(l1, dist = 1, nQuadSegs=2), reset = FALSE, main = "nQuadSegs: 2")plot(l1,col='blue',add=TRUE)plot(st_buffer(l1, dist = 1, nQuadSegs= 5), reset = FALSE, main = "nQuadSegs: 5")plot(l1,col='blue',add=TRUE)par(op)l2 = st_as_sfc("LINESTRING(0 0,1 5,3 2)")op = par(mfrow = c(2, 3))plot(st_buffer(l2, dist = 1, joinStyle="ROUND"), reset = FALSE, main = "joinStyle: ROUND")plot(l2, col = 'blue', add = TRUE)plot(st_buffer(l2, dist = 1, joinStyle="MITRE"), reset = FALSE, main = "joinStyle: MITRE")plot(l2, col= 'blue', add = TRUE)plot(st_buffer(l2, dist = 1, joinStyle="BEVEL"), reset = FALSE, main = "joinStyle: BEVEL")plot(l2, col= 'blue', add=TRUE)plot(st_buffer(l2, dist = 1, joinStyle="MITRE" , mitreLimit=0.5), reset = FALSE,   main = "mitreLimit: 0.5")plot(l2, col = 'blue', add = TRUE)plot(st_buffer(l2, dist = 1, joinStyle="MITRE",mitreLimit=1), reset = FALSE,   main = "mitreLimit: 1")plot(l2, col = 'blue', add = TRUE)plot(st_buffer(l2, dist = 1, joinStyle="MITRE",mitreLimit=3), reset = FALSE,   main = "mitreLimit: 3")plot(l2, col = 'blue', add = TRUE)par(op)# compare approximation errors depending on S2 or GEOS backend:# geographic coordinates, uses S2:x = st_buffer(st_as_sf(data.frame(lon=0,lat=0), coords=c("lon","lat"),crs='OGC:CRS84'),       units::as_units(1,"km"))y = units::set_units(st_area(x), "km^2")# error: postive, default maxcells = 1000(units::drop_units(y)-pi)/pix = st_buffer(st_as_sf(data.frame(lon=0,lat=0), coords=c("lon","lat"),crs='OGC:CRS84'),       units::as_units(1,"km"), max_cells=1e5)y = units::set_units(st_area(x), "km^2")# error: positive but smaller:(units::drop_units(y)-pi)/pi# no CRS set: assumes Cartesian (projected) coordinatesx = st_buffer(st_as_sf(data.frame(lon=0,lat=0), coords=c("lon","lat")), 1)y = st_area(x)# error: negative, nQuadSegs default at 30((y)-pi)/pix = st_buffer(st_as_sf(data.frame(lon=0,lat=0), coords=c("lon","lat")), 1, nQuadSegs = 100)y = st_area(x)# error: negative but smaller:((y)-pi)/pinc = st_read(system.file("shape/nc.shp", package="sf"))nc_g = st_geometry(nc)plot(st_convex_hull(nc_g))plot(nc_g, border = grey(.5), add = TRUE)pt = st_combine(st_sfc(st_point(c(0,80)), st_point(c(120,80)), st_point(c(240,80))))st_convex_hull(pt) # R2st_convex_hull(st_set_crs(pt, 'OGC:CRS84')) # S2set.seed(131)if (compareVersion(sf_extSoftVersion()[["GEOS"]], "3.11.0") > -1) { pts = cbind(runif(100), runif(100)) m = st_multipoint(pts) co = sf:::st_concave_hull(m, 0.3) coh = sf:::st_concave_hull(m, 0.3, allow_holes = TRUE) plot(co, col = 'grey') plot(coh, add = TRUE, border = 'red') plot(m, add = TRUE)}# st_simplify examples:op = par(mfrow = c(2, 3), mar = rep(0, 4))plot(nc_g[1])plot(st_simplify(nc_g[1], dTolerance = 1e3)) # 1000mplot(st_simplify(nc_g[1], dTolerance = 5e3)) # 5000mnc_g_planar = st_transform(nc_g, 2264) # planar coordinates, US footplot(nc_g_planar[1])plot(st_simplify(nc_g_planar[1], dTolerance = 1e3)) # 1000 footplot(st_simplify(nc_g_planar[1], dTolerance = 5e3)) # 5000 footpar(op)if (compareVersion(sf_extSoftVersion()[["GEOS"]], "3.10.0") > -1) { pts = rbind(c(0,0), c(1,0), c(1,1), c(.5,.5), c(0,1), c(0,0)) po = st_polygon(list(pts)) co = st_triangulate_constrained(po) tr = st_triangulate(po) plot(po, col = NA, border = 'grey', lwd = 15) plot(tr, border = 'green', col = NA, lwd = 5, add = TRUE) plot(co, border = 'red', col = 'NA', add = TRUE)}if (compareVersion(sf_extSoftVersion()[["GEOS"]], "3.9.0") > -1) {  nc_t = st_transform(nc, 'EPSG:2264')  x = st_inscribed_circle(st_geometry(nc_t))  plot(st_geometry(nc_t), asp = 1, col = grey(.9))  plot(x, add = TRUE, col = '#ff9999')}set.seed(1)x = st_multipoint(matrix(runif(10),,2))box = st_polygon(list(rbind(c(0,0),c(1,0),c(1,1),c(0,1),c(0,0))))if (compareVersion(sf_extSoftVersion()[["GEOS"]], "3.5.0") > -1) { v = st_sfc(st_voronoi(x, st_sfc(box))) plot(v, col = 0, border = 1, axes = TRUE) plot(box, add = TRUE, col = 0, border = 1) # a larger box is returned, as documented plot(x, add = TRUE, col = 'red', cex=2, pch=16) plot(st_intersection(st_cast(v), box)) # clip to smaller box plot(x, add = TRUE, col = 'red', cex=2, pch=16) # matching Voronoi polygons to data points: # https://github.com/r-spatial/sf/issues/1030 # generate 50 random unif points: n = 100 pts = st_as_sf(data.frame(matrix(runif(n), , 2), id = 1:(n/2)), coords = c("X1", "X2")) # compute Voronoi polygons: pols = st_collection_extract(st_voronoi(do.call(c, st_geometry(pts)))) # match them to points: pts_pol = st_intersects(pts, pols) pts$pols = pols[unlist(pts_pol)] # re-order if (isTRUE(try(compareVersion(sf_extSoftVersion()["GEOS"], "3.12.0") > -1,   silent = TRUE))) {   pols_po = st_collection_extract(st_voronoi(do.call(c, st_geometry(pts)),     point_order = TRUE)) # GEOS >= 3.12 can preserve order of inputs   pts_pol_po = st_intersects(pts, pols_po)   print(all(unlist(pts_pol_po) == 1:(n/2))) } plot(pts["id"], pch = 16) # ID is color plot(st_set_geometry(pts, "pols")["id"], xlim = c(0,1), ylim = c(0,1), reset = FALSE) plot(st_geometry(pts), add = TRUE) layout(matrix(1)) # reset plot layout}mls = st_multilinestring(list(matrix(c(0,0,0,1,1,1,0,0),,2,byrow=TRUE)))st_polygonize(st_sfc(mls))mls = st_multilinestring(list(rbind(c(0,0), c(1,1)), rbind(c(2,0), c(1,1))))st_line_merge(st_sfc(mls))plot(nc_g, axes = TRUE)plot(st_centroid(nc_g), add = TRUE, pch = 3, col = 'red')mp = st_combine(st_buffer(st_sfc(lapply(1:3, function(x) st_point(c(x,x)))), 0.2 * 1:3))plot(mp)plot(st_centroid(mp), add = TRUE, col = 'red') # centroid of combined geometryplot(st_centroid(mp, of_largest_polygon = TRUE), add = TRUE, col = 'blue', pch = 3)plot(nc_g, axes = TRUE)plot(st_point_on_surface(nc_g), add = TRUE, pch = 3, col = 'red')if (compareVersion(sf_extSoftVersion()[["GEOS"]], "3.7.0") > -1) {  st_reverse(st_linestring(rbind(c(1,1), c(2,2), c(3,3))))}(l = st_linestring(rbind(c(0,0), c(1,1), c(0,1), c(1,0), c(0,0))))st_polygonize(st_node(l))st_node(st_multilinestring(list(rbind(c(0,0), c(1,1), c(0,1), c(1,0), c(0,0)))))sf = st_sf(a=1, geom=st_sfc(st_linestring(rbind(c(0,0),c(1,1)))), crs = 4326)if (require(lwgeom, quietly = TRUE)) { seg = st_segmentize(sf, units::set_units(100, km)) seg = st_segmentize(sf, units::set_units(0.01, rad)) nrow(seg$geom[[1]])}

Areal-weighted interpolation of polygon data

Description

Areal-weighted interpolation of polygon data

Usage

st_interpolate_aw(x, to, extensive, ...)## S3 method for class 'sf'st_interpolate_aw(x, to, extensive, ..., keep_NA = FALSE, na.rm = FALSE)

Arguments

Details

ifextensive isTRUE andna.rm is set toTRUE, geometries withNA are effectively treated as having zero attribute values.

Examples

nc = st_read(system.file("shape/nc.shp", package="sf"))g = st_make_grid(nc, n = c(10, 5))a1 = st_interpolate_aw(nc["BIR74"], g, extensive = FALSE)sum(a1$BIR74) / sum(nc$BIR74) # not close to one: property is assumed spatially intensivea2 = st_interpolate_aw(nc["BIR74"], g, extensive = TRUE)# verify mass preservation (pycnophylactic) property:sum(a2$BIR74) / sum(nc$BIR74)a1$intensive = a1$BIR74a1$extensive = a2$BIR74plot(a1[c("intensive", "extensive")], key.pos = 4)

Check if driver is available

Description

Search through the driver table if driver is listed

Usage

is_driver_available(drv, drivers = st_drivers())

Arguments

Check if a driver can perform an action

Description

Search through the driver table to match a driver name withan action (e.g."write") and check if the action is supported.

Usage

is_driver_can(drv, drivers = st_drivers(), operation = "write")

Arguments

Check if the columns could be of a coercable type for sf

Description

Check if the columns could be of a coercable type for sf

Usage

is_geometry_column(con, x, classes = "")

Arguments

merge method for sf and data.frame object

Description

merge method for sf and data.frame object

Usage

## S3 method for class 'sf'merge(x, y, ...)

Arguments

Examples

a = data.frame(a = 1:3, b = 5:7)st_geometry(a) = st_sfc(st_point(c(0,0)), st_point(c(1,1)), st_point(c(2,2)))b = data.frame(x = c("a", "b", "c"), b = c(2,5,6))merge(a, b)merge(a, b, all = TRUE)

North Carolina SIDS data

Description

Sudden Infant Death Syndrome (SIDS) sample data for North Carolina counties,two time periods (1974-78 and 1979-84). The details of the columns can befound in aspdep package vignette.Please note that, though this is basically the same asnc.sids dataset in spDatapackage,nc only contains a subset of variables. The differences arealso discussed on the vignette.

Format

Asf object

See Also

https://r-spatial.github.io/spdep/articles/sids.html

Examples

nc <- st_read(system.file("shape/nc.shp", package="sf"))

plot sf object

Description

plot one or more attributes of an sf object on a mapPlot sf object

Usage

## S3 method for class 'sf'plot(  x,  y,  ...,  main,  pal = NULL,  nbreaks = 10,  breaks = "pretty",  max.plot = getOption("sf_max.plot", default = 9),  key.pos = get_key_pos(x, ...),  key.length = 0.618,  key.width = kw_dflt(x, key.pos),  reset = TRUE,  logz = FALSE,  extent = x,  xlim = st_bbox(extent)[c(1, 3)],  ylim = st_bbox(extent)[c(2, 4)],  compact = FALSE)get_key_pos(x, ...)## S3 method for class 'sfc_POINT'plot(  x,  y,  ...,  pch = 1,  cex = 1,  col = 1,  bg = 0,  lwd = 1,  lty = 1,  type = "p",  add = FALSE)## S3 method for class 'sfc_MULTIPOINT'plot(  x,  y,  ...,  pch = 1,  cex = 1,  col = 1,  bg = 0,  lwd = 1,  lty = 1,  type = "p",  add = FALSE)## S3 method for class 'sfc_LINESTRING'plot(x, y, ..., lty = 1, lwd = 1, col = 1, pch = 1, type = "l", add = FALSE)## S3 method for class 'sfc_CIRCULARSTRING'plot(x, y, ...)## S3 method for class 'sfc_MULTILINESTRING'plot(x, y, ..., lty = 1, lwd = 1, col = 1, pch = 1, type = "l", add = FALSE)## S3 method for class 'sfc_POLYGON'plot(  x,  y,  ...,  lty = 1,  lwd = 1,  col = NA,  cex = 1,  pch = NA,  border = 1,  add = FALSE,  rule = "evenodd",  xpd = par("xpd"))## S3 method for class 'sfc_MULTIPOLYGON'plot(  x,  y,  ...,  lty = 1,  lwd = 1,  col = NA,  border = 1,  add = FALSE,  rule = "evenodd",  xpd = par("xpd"))## S3 method for class 'sfc_GEOMETRYCOLLECTION'plot(  x,  y,  ...,  pch = 1,  cex = 1,  bg = 0,  lty = 1,  lwd = 1,  col = 1,  border = 1,  add = FALSE)## S3 method for class 'sfc_GEOMETRY'plot(  x,  y,  ...,  pch = 1,  cex = 1,  bg = 0,  lty = 1,  lwd = 1,  col = ifelse(st_dimension(x) == 2, NA, 1),  border = 1,  add = FALSE)## S3 method for class 'sfg'plot(x, ...)plot_sf(  x,  xlim = NULL,  ylim = NULL,  asp = NA,  axes = FALSE,  bgc = par("bg"),  ...,  xaxs,  yaxs,  lab,  setParUsrBB = FALSE,  bgMap = NULL,  expandBB = c(0, 0, 0, 0),  graticule = NA_crs_,  col_graticule = "grey",  border,  extent = x)sf.colors(n = 10, cutoff.tails = c(0.35, 0.2), alpha = 1, categorical = FALSE)## S3 method for class 'sf'text(x, labels = row.names(x), ...)## S3 method for class 'sfc'text(x, labels = seq_along(x), ..., of_largest_polygon = FALSE)## S3 method for class 'sf'points(x, ...)## S3 method for class 'sfc'points(x, ..., of_largest_polygon = FALSE)

Arguments

Details

plot.sf maximally plotsmax.plot maps with colors following from attribute columns,one map per attribute. It usessf.colors for default colors. For more control over placement of individual maps,set parametermfrow withpar prior to plotting, and plot single maps one by one; note that this only worksin combination with setting parameterskey.pos=NULL (no legend) andreset=FALSE.

plot.sfc plots the geometry, additional parameters can be passed onto control color, lines or symbols.

When settingreset toFALSE, the original device parameters are lost, and the device must be reset usingdev.off() in order to reset it.

parameterat can be set to specify where labels are placed along the key; see examples.

The features are plotted in the order as they apppear in the sf object. See examples for when a different plotting order is wanted.

plot_sf sets up the plotting area, axes, graticule, or webmap background; itis called by allplot methods before anything is drawn.

The argumentsetParUsrBB may be used to pass the logical valueTRUE to functions withinplot.Spatial. When set toTRUE, par(“usr”) will be overwritten withc(xlim, ylim), which defaults to the bounding box of the spatial object. This is only needed in the particular context of graphic output to a specified device with given width and height, to be matched to the spatial object, when using par(“xaxs”) and par(“yaxs”) in addition topar(mar=c(0,0,0,0)).

The default aspect for map plots is 1; if however data are notprojected (coordinates are long/lat), the aspect is by default set to1/cos(My * pi/180) with My the y coordinate of the middle of the map(the mean ofylim, which defaults to the y range of bounding box). Thisimplies anEquirectangular projection.

non-categorical colors fromsf.colors were taken frombpy.colors, with modifiedcutoff.tails defaultsIf categorical isTRUE, default colors are fromhttps://colorbrewer2.org/ (if n < 9, Set2, else Set3).

text.sf adds text to an existing base graphic. Text is placed at the centroid ofeach feature inx. Provide POINT features for further control of placement.points.sf adds point symbols to an existing base graphic. If points of text are not showncorrectly, try setting argumentreset toFALSE in theplot() call.

Examples

nc = st_read(system.file("gpkg/nc.gpkg", package="sf"), quiet = TRUE)# plot single attribute, auto-legend:plot(nc["SID74"])# plot multiple:plot(nc[c("SID74", "SID79")]) # better use ggplot2::geom_sf to facet and get a single legend!# adding to a plot of an sf object only works when using reset=FALSE in the first plot:plot(nc["SID74"], reset = FALSE)plot(st_centroid(st_geometry(nc)), add = TRUE)# log10 z-scale:plot(nc["SID74"], logz = TRUE, breaks = c(0,.5,1,1.5,2), at = c(0,.5,1,1.5,2))# and we need to reset the plotting device after that, e.g. bylayout(1)# when plotting only geometries, the reset=FALSE is not needed:plot(st_geometry(nc))plot(st_geometry(nc)[1], col = 'red', add = TRUE)# add a custom legend to an arbitray plot:layout(matrix(1:2, ncol = 2), widths = c(1, lcm(2)))plot(1).image_scale(1:10, col = sf.colors(9), key.length = lcm(8), key.pos = 4, at = 1:10)# manipulate plotting order, plot largest polygons first:p = st_polygon(list(rbind(c(0,0), c(1,0), c(1,1), c(0,1), c(0,0))))x = st_sf(a=1:4, st_sfc(p, p * 2, p * 3, p * 4)) # plot(x, col=2:5) only shows the largest polygon!plot(x[order(st_area(x), decreasing = TRUE),], col = 2:5) # plot largest polygons firstsf.colors(10)text(nc, labels = substring(nc$NAME,1,1))

Map prefix to driver

Description

Map prefix to driver

Usage

prefix_map

Format

An object of classlist of length 10.

Manage PROJ settings

Description

Query or manage PROJ search path and network settings

Usage

sf_proj_search_paths(paths = character(0), with_proj = NA)sf_proj_network(enable = FALSE, url = character(0))sf_proj_pipelines(  source_crs,  target_crs,  authority = character(0),  AOI = numeric(0),  Use = "NONE",  grid_availability = "USED",  desired_accuracy = -1,  strict_containment = FALSE,  axis_order_authority_compliant = st_axis_order())

Arguments

Value

sf_proj_search_paths() returns the search path (possibly after setting it)

sf_proj_network when called without arguments returns a logical indicating whethernetwork search of datum grids is enabled, when called with arguments it returns a charactervector with the URL of the CDN used (or specified withurl).

sf_proj_pipelines() returns a table with candidate coordinate transformationpipelines along with their accuracy;NA accuracy indicates ballpark accuracy.

Convert raw vector(s) into hexadecimal character string(s)

Description

Convert raw vector(s) into hexadecimal character string(s)

Usage

rawToHex(x)

Arguments

Objects exported from other packages

Description

These objects are imported from other packages. Follow the linksbelow to see their documentation.

magrittr

%>%

functions for spherical geometry, using s2 package

Description

functions for spherical geometry, using the s2 package based on the google s2geometry.io library

Usage

sf_use_s2(use_s2)st_as_s2(x, ...)## S3 method for class 'sf'st_as_s2(x, ...)## S3 method for class 'sfc'st_as_s2(  x,  ...,  oriented = getOption("s2_oriented", FALSE) || isTRUE(attr(x, "oriented")),  rebuild = FALSE)

Arguments

Details

st_as_s2 converts ansf POLYGON object into a form readable bys2.

Value

sf_use_s2 returns the value of this variable before (re)setting it,invisibly ifuse_s2 is not missing.

Examples

m = rbind(c(-1,-1), c(1,-1), c(1,1), c(-1,1), c(-1,-1))m1 = rbind(c(-1,-1), c(1,-1), c(1,1), c(-1,1), c(-1,0), c(-1,-1))m0 = m[5:1,]mp = st_multipolygon(list(list(m, 0.8 * m0, 0.01 * m1 + 0.9),list(0.7* m, 0.6*m0),list(0.5 * m0),list(m+2),list(m+4,(.9*m0)+4)))sf = st_sfc(mp, mp, crs = 'EPSG:4326')s2 = st_as_s2(sf)

Create sf object

Description

Create sf, which extends data.frame-like objects with a simple feature list column.To convert a data frame object tosf, usest_as_sf()

Usage

st_sf(  ...,  agr = NA_agr_,  row.names,  stringsAsFactors = sf_stringsAsFactors(),  crs,  precision,  sf_column_name = NULL,  check_ring_dir = FALSE,  sfc_last = TRUE)## S3 method for class 'sf'x[i, j, ..., drop = FALSE, op = st_intersects]## S3 method for class 'sf'print(x, ..., n = getOption("sf_max_print", default = 10))

Arguments

Details

agr, attribute-geometry-relationship, specifies for each non-geometry attribute column how it relates to the geometry, and can have one of following values: "constant", "aggregate", "identity". "constant" is used for attributes that are constant throughout the geometry (e.g. land use), "aggregate" where the attribute is an aggregate value over the geometry (e.g. population density or population count), "identity" when the attributes uniquely identifies the geometry of particular "thing", such as a building ID or a city name. The default value,NA_agr_, implies we don't know.

When a single value is provided toagr, it is cascaded across all input columns; otherwise, a named vector likec(feature1='constant', ...) will setagr value to'constant' for the input column namedfeature1. Seedemo(nc) for a worked example of this.

When confronted with a data.frame-like object,st_sf will try to find a geometry column of classsfc, and otherwise try to convert list-columns when available into a geometry column, usingst_as_sfc.

[.sf will return adata.frame or vector if the geometry column (of classsfc) is dropped (drop=TRUE), ansfc object if only the geometry column is selected, and otherwise return ansf object; see also[.data.frame; for[.sf... arguments are passed toop.

Examples

g = st_sfc(st_point(1:2))st_sf(a=3,g)st_sf(g, a=3)st_sf(a=3, st_sfc(st_point(1:2))) # better to name it!# create empty structure with preallocated empty geometries:nrows <- 10geometry = st_sfc(lapply(1:nrows, function(x) st_geometrycollection()))df <- st_sf(id = 1:nrows, geometry = geometry)g = st_sfc(st_point(1:2), st_point(3:4))s = st_sf(a=3:4, g)s[1,]class(s[1,])s[,1]class(s[,1])s[,2]class(s[,2])g = st_sf(a=2:3, g)pol = st_sfc(st_polygon(list(cbind(c(0,3,3,0,0),c(0,0,3,3,0)))))h = st_sf(r = 5, pol)g[h,]h[g,]

Deprecated functions insf

Description

These functions are provided for compatibility with older version ofsf.They will eventually be completely removed.

• Usest_read() instead ofst_read_db().

• Usest_write() instead_ofst_write_db()

Usage

st_read_db(  conn = NULL,  table = NULL,  query = NULL,  geom_column = NULL,  EWKB = TRUE,  ...)st_write_db(  conn = NULL,  obj,  table = deparse(substitute(obj)),  ...,  drop = FALSE,  append = FALSE)

Arguments

Details

Thegeom_column argument is deprecated. The function willautomatically find thegeometry type columns. For theRPostgreSQL driversit will try to cast all the character columns, which can be long for very widetables.

Provide the external dependencies versions of the libraries linked to sf

Description

Provide the external dependencies versions of the libraries linked to sf

Usage

sf_extSoftVersion()

directly transform a set of coordinates

Description

directly transform a set of coordinates

Usage

sf_add_proj_units()sf_project(  from = character(0),  to = character(0),  pts,  keep = FALSE,  warn = TRUE,  authority_compliant = st_axis_order())

Arguments

Details

sf_add_proj_units loads the PROJ unitslink,us_in,ind_yd,ind_ft, andind_ch into the udunits database, and returnsTRUE invisibly on success.

Value

two-column numeric matrix with transformed/converted coordinates, returning invalid values asInf

Examples

sf_add_proj_units()

Create simple feature geometry list column

Description

Create simple feature geometry list column, set class, and add coordinate reference system and precision.For data.frame alternatives seest_sf(). To convert a foreign object tosfc, seest_as_sfc()

Usage

st_sfc(  ...,  crs = NA_crs_,  precision = 0,  check_ring_dir = FALSE,  dim,  recompute_bbox = FALSE,  oriented = NA)## S3 method for class 'sfc'x[i, j, ..., op = st_intersects]

Arguments

Details

A simple feature geometry list-column is a list of classc("stc_TYPE", "sfc") which most often contains objects of identical type;in case of a mix of types or an empty set,TYPE is set to thesuperclassGEOMETRY.

ifx has adim attribute (i.e. is anarray ormatrix) thenop cannot be used.

Value

an object of classsfc, which is a classed list-column with simple feature geometries.

Examples

pt1 = st_point(c(0,1))pt2 = st_point(c(1,1))(sfc = st_sfc(pt1, pt2))sfc[sfc[1], op = st_is_within_distance, dist = 0.5]d = st_sf(data.frame(a=1:2, geom=sfc))

Methods for dealing with sparse geometry binary predicate lists

Description

Methods for dealing with sparse geometry binary predicate lists

Usage

## S3 method for class 'sgbp'print(x, ..., n = 10, max_nb = 10)## S3 method for class 'sgbp't(x)## S3 method for class 'sgbp'as.matrix(x, ...)## S3 method for class 'sgbp'dim(x)## S3 method for class 'sgbp'Ops(e1, e2)## S3 method for class 'sgbp'as.data.frame(x, ...)

Arguments

Details

sgbp are sparse matrices, stored as a list with integer vectors holding the orderedTRUE indices of each row. This means that for a dense,m \times n matrixQ and a listL, ifQ[i,j] isTRUE thenj is an element ofL[[i]]. Reversed: whenk is the value ofL[[i]][j], thenQ[i,k] isTRUE.

== compares only the dimension and index values, not the attributes of twosgbp object; useidentical to check for equality of everything.

Create simple feature from a numeric vector, matrix or list

Description

Create simple feature from a numeric vector, matrix or list

Usage

st_point(x = c(NA_real_, NA_real_), dim = "XYZ")st_multipoint(x = matrix(numeric(0), 0, 2), dim = "XYZ")st_linestring(x = matrix(numeric(0), 0, 2), dim = "XYZ")st_polygon(x = list(), dim = if (length(x)) "XYZ" else "XY")st_multilinestring(x = list(), dim = if (length(x)) "XYZ" else "XY")st_multipolygon(x = list(), dim = if (length(x)) "XYZ" else "XY")st_geometrycollection(x = list(), dims = "XY")## S3 method for class 'sfg'print(x, ..., width = 0)## S3 method for class 'sfg'head(x, n = 10L, ...)## S3 method for class 'sfg'format(x, ..., width = 30)## S3 method for class 'sfg'c(..., recursive = FALSE, flatten = TRUE)## S3 method for class 'sfg'as.matrix(x, ...)

Arguments

Details

"XYZ" refers to coordinates where the third dimension represents altitude, "XYM" refers to three-dimensional coordinates where the third dimension refers to something else ("M" for measure); checking of the sanity ofx may be only partial.

Whenflatten=TRUE, this method may merge points into a multipoint structure, and may not preserve order, and hence cannot be reverted. When given fish, it returns fish soup.

Value

object of the same nature asx, but with appropriate class attribute set

as.matrix returns the set of points that form a geometry as a single matrix, where each point is a row; useunlist(x, recursive = FALSE) to get sets of matrices.

Examples

(p1 = st_point(c(1,2)))class(p1)st_bbox(p1)(p2 = st_point(c(1,2,3)))class(p2)(p3 = st_point(c(1,2,3), "XYM"))pts = matrix(1:10, , 2)(mp1 = st_multipoint(pts))pts = matrix(1:15, , 3)(mp2 = st_multipoint(pts))(mp3 = st_multipoint(pts, "XYM"))pts = matrix(1:20, , 4)(mp4 = st_multipoint(pts))pts = matrix(1:10, , 2)(ls1 = st_linestring(pts))pts = matrix(1:15, , 3)(ls2 = st_linestring(pts))(ls3 = st_linestring(pts, "XYM"))pts = matrix(1:20, , 4)(ls4 = st_linestring(pts))outer = matrix(c(0,0,10,0,10,10,0,10,0,0),ncol=2, byrow=TRUE)hole1 = matrix(c(1,1,1,2,2,2,2,1,1,1),ncol=2, byrow=TRUE)hole2 = matrix(c(5,5,5,6,6,6,6,5,5,5),ncol=2, byrow=TRUE)pts = list(outer, hole1, hole2)(ml1 = st_multilinestring(pts))pts3 = lapply(pts, function(x) cbind(x, 0))(ml2 = st_multilinestring(pts3))(ml3 = st_multilinestring(pts3, "XYM"))pts4 = lapply(pts3, function(x) cbind(x, 0))(ml4 = st_multilinestring(pts4))outer = matrix(c(0,0,10,0,10,10,0,10,0,0),ncol=2, byrow=TRUE)hole1 = matrix(c(1,1,1,2,2,2,2,1,1,1),ncol=2, byrow=TRUE)hole2 = matrix(c(5,5,5,6,6,6,6,5,5,5),ncol=2, byrow=TRUE)pts = list(outer, hole1, hole2)(pl1 = st_polygon(pts))pts3 = lapply(pts, function(x) cbind(x, 0))(pl2 = st_polygon(pts3))(pl3 = st_polygon(pts3, "XYM"))pts4 = lapply(pts3, function(x) cbind(x, 0))(pl4 = st_polygon(pts4))pol1 = list(outer, hole1, hole2)pol2 = list(outer + 12, hole1 + 12)pol3 = list(outer + 24)mp = list(pol1,pol2,pol3)(mp1 = st_multipolygon(mp))pts3 = lapply(mp, function(x) lapply(x, function(y) cbind(y, 0)))(mp2 = st_multipolygon(pts3))(mp3 = st_multipolygon(pts3, "XYM"))pts4 = lapply(mp2, function(x) lapply(x, function(y) cbind(y, 0)))(mp4 = st_multipolygon(pts4))(gc = st_geometrycollection(list(p1, ls1, pl1, mp1)))st_geometrycollection() # empty geometryc(st_point(1:2), st_point(5:6))c(st_point(1:2), st_multipoint(matrix(5:8,2)))c(st_multipoint(matrix(1:4,2)), st_multipoint(matrix(5:8,2)))c(st_linestring(matrix(1:6,3)), st_linestring(matrix(11:16,3)))c(st_multilinestring(list(matrix(1:6,3))), st_multilinestring(list(matrix(11:16,3))))pl = list(rbind(c(0,0), c(1,0), c(1,1), c(0,1), c(0,0)))c(st_polygon(pl), st_polygon(pl))c(st_polygon(pl), st_multipolygon(list(pl)))c(st_linestring(matrix(1:6,3)), st_point(1:2))c(st_geometrycollection(list(st_point(1:2), st_linestring(matrix(1:6,3)))),  st_geometrycollection(list(st_multilinestring(list(matrix(11:16,3))))))c(st_geometrycollection(list(st_point(1:2), st_linestring(matrix(1:6,3)))),  st_multilinestring(list(matrix(11:16,3))), st_point(5:6),  st_geometrycollection(list(st_point(10:11))))

get or set relation_to_geometry attribute of ansf object

Description

get or set relation_to_geometry attribute of ansf object

Usage

NA_agr_st_agr(x, ...)st_agr(x) <- valuest_set_agr(x, value)

Arguments

Format

An object of classfactor of length 1.

Details

NA_agr_ is theagr object with a missing value.

Convert sfc object to an WKB object

Description

Convert sfc object to an WKB object

Usage

st_as_binary(x, ...)## S3 method for class 'sfc'st_as_binary(  x,  ...,  EWKB = FALSE,  endian = .Platform$endian,  pureR = FALSE,  precision = attr(x, "precision"),  hex = FALSE)## S3 method for class 'sfg'st_as_binary(  x,  ...,  endian = .Platform$endian,  EWKB = FALSE,  pureR = FALSE,  hex = FALSE,  srid = 0)

Arguments

Details

st_as_binary is called on sfc objects on their way to the GDAL or GEOS libraries, and hence does rounding (if requested) on the fly before e.g. computing spatial predicates likest_intersects. The examples show a round-trip of ansfc to and from binary.

For the precision model used, see alsohttps://locationtech.github.io/jts/javadoc/org/locationtech/jts/geom/PrecisionModel.html. There, it is written that: “... to specify 3 decimal places of precision, use a scale factor of 1000. To specify -3 decimal places of precision (i.e. rounding to the nearest 1000), use a scale factor of 0.001.”. Note that ALL coordinates, so also Z or M values (if present) are affected.

Examples

# examples of setting precision:st_point(c(1/3, 1/6)) %>% st_sfc(precision = 1000) %>% st_as_binary %>% st_as_sfcst_point(c(1/3, 1/6)) %>% st_sfc(precision =  100) %>% st_as_binary %>% st_as_sfcst_point(1e6 * c(1/3, 1/6)) %>% st_sfc(precision = 0.01) %>% st_as_binary %>% st_as_sfcst_point(1e6 * c(1/3, 1/6)) %>% st_sfc(precision = 0.001) %>% st_as_binary %>% st_as_sfc

Convert sf* object to a grob

Description

Convert sf* object to an grid graphics object (grob)

Usage

st_as_grob(x, ...)

Arguments

Convert foreign object to an sf object

Description

Convert foreign object to an sf object

Usage

st_as_sf(x, ...)## S3 method for class 'data.frame'st_as_sf(  x,  ...,  agr = NA_agr_,  coords,  wkt,  dim = "XYZ",  remove = TRUE,  na.fail = TRUE,  sf_column_name = NULL)## S3 method for class 'sf'st_as_sf(x, ...)## S3 method for class 'sfc'st_as_sf(x, ...)## S3 method for class 'Spatial'st_as_sf(x, ...)## S3 method for class 'map'st_as_sf(x, ..., fill = TRUE, group = TRUE)## S3 method for class 'ppp'st_as_sf(x, ...)## S3 method for class 'psp'st_as_sf(x, ...)## S3 method for class 'lpp'st_as_sf(x, ...)## S3 method for class 's2_geography'st_as_sf(x, ..., crs = st_crs(4326))

Arguments

Details

setting argumentwkt annihilates the use of argumentcoords. Ifx contains a column called "geometry",coords will result in overwriting of this column by thesfc geometry list-column. Settingwkt will replace this column with the geometry list-column, unlessremove isFALSE.

Ifcoords has length 4, anddim is notXYZM, the four columns are taken as the xmin, ymin, xmax, ymax corner coordinates of a rectangle, and polygons are returned.

Examples

pt1 = st_point(c(0,1))pt2 = st_point(c(1,1))st_sfc(pt1, pt2)d = data.frame(a = 1:2)d$geom = st_sfc(pt1, pt2)df = st_as_sf(d)d$geom = c("POINT(0 0)", "POINT(0 1)")df = st_as_sf(d, wkt = "geom")d$geom2 = st_sfc(pt1, pt2)st_as_sf(d) # should warnif (require(sp, quietly = TRUE)) { data(meuse, package = "sp") meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant") meuse_sf[1:3,] summary(meuse_sf)}if (require(sp, quietly = TRUE)) {x = rbind(c(-1,-1), c(1,-1), c(1,1), c(-1,1), c(-1,-1))x1 = 0.1 * x + 0.1x2 = 0.1 * x + 0.4x3 = 0.1 * x + 0.7y = x + 3y1 = x1 + 3y3 = x3 + 3m = matrix(c(3, 0), 5, 2, byrow = TRUE)z = x + mz1 = x1 + mz2 = x2 + mz3 = x3 + mp1 = Polygons(list( Polygon(x[5:1,]), Polygon(x2), Polygon(x3),   Polygon(y[5:1,]), Polygon(y1), Polygon(x1), Polygon(y3)), "ID1")p2 = Polygons(list( Polygon(z[5:1,]), Polygon(z2), Polygon(z3), Polygon(z1)),  "ID2")r = SpatialPolygons(list(p1,p2))a = suppressWarnings(st_as_sf(r))summary(a)demo(meuse, ask = FALSE, echo = FALSE)summary(st_as_sf(meuse))summary(st_as_sf(meuse.grid))summary(st_as_sf(meuse.area))summary(st_as_sf(meuse.riv))summary(st_as_sf(as(meuse.riv, "SpatialLines")))pol.grd = as(meuse.grid, "SpatialPolygonsDataFrame")# summary(st_as_sf(pol.grd))# summary(st_as_sf(as(pol.grd, "SpatialLinesDataFrame")))}if (require(spatstat.geom)) {  g = st_as_sf(gorillas)  # select only the points:  g[st_is(g, "POINT"),]}if (require(spatstat.linnet)) { data(chicago) plot(st_as_sf(chicago)["label"]) plot(st_as_sf(chicago)[-1,"label"])}

Convert foreign geometry object to an sfc object

Description

Convert foreign geometry object to an sfc object

Usage

## S3 method for class 'pq_geometry'st_as_sfc(  x,  ...,  EWKB = TRUE,  spatialite = FALSE,  pureR = FALSE,  crs = NA_crs_)## S3 method for class 'list'st_as_sfc(x, ..., crs = NA_crs_)## S3 method for class 'blob'st_as_sfc(x, ...)## S3 method for class 'bbox'st_as_sfc(x, ...)## S3 method for class 'WKB'st_as_sfc(  x,  ...,  EWKB = FALSE,  spatialite = FALSE,  pureR = FALSE,  crs = NA_crs_)## S3 method for class 'raw'st_as_sfc(x, ...)## S3 method for class 'character'st_as_sfc(x, crs = NA_integer_, ..., GeoJSON = FALSE)## S3 method for class 'factor'st_as_sfc(x, ...)st_as_sfc(x, ...)## S3 method for class 'SpatialPoints'st_as_sfc(x, ..., precision = 0)## S3 method for class 'SpatialPixels'st_as_sfc(x, ..., precision = 0)## S3 method for class 'SpatialMultiPoints'st_as_sfc(x, ..., precision = 0)## S3 method for class 'SpatialLines'st_as_sfc(x, ..., precision = 0, forceMulti = FALSE)## S3 method for class 'SpatialPolygons'st_as_sfc(x, ..., precision = 0, forceMulti = FALSE)## S3 method for class 'map'st_as_sfc(x, ...)## S3 method for class 's2_geography'st_as_sfc(  x,  ...,  crs = st_crs(4326),  endian = match(.Platform$endian, c("big", "little")) - 1L)

Arguments

Details

When converting from WKB, the objectx is either a character vector such as typically obtained from PostGIS (either with leading "0x" or without), or a list with raw vectors representing the features in binary (raw) form.

Ifx is a character vector, it should be a vector containingwell-known-text, orPostgis EWKT or GeoJSON representations of a single geometry for each vector element.

Ifx is afactor, it is converted tocharacter.

Examples

wkb = structure(list("01010000204071000000000000801A064100000000AC5C1441"), class = "WKB")st_as_sfc(wkb, EWKB = TRUE)wkb = structure(list("0x01010000204071000000000000801A064100000000AC5C1441"), class = "WKB")st_as_sfc(wkb, EWKB = TRUE)st_as_sfc(st_as_binary(st_sfc(st_point(0:1)))[[1]], crs = 4326)st_as_sfc("SRID=3978;LINESTRING(1663106 -105415,1664320 -104617)")

Return Well-known Text representation of simple feature geometry or coordinate reference system

Description

Return Well-known Text representation of simple feature geometry or coordinate reference system

Usage

## S3 method for class 'crs'st_as_text(x, ..., projjson = FALSE, pretty = FALSE)st_as_text(x, ...)## S3 method for class 'sfg'st_as_text(x, ...)## S3 method for class 'sfc'st_as_text(x, ..., EWKT = FALSE)

Arguments

Details

The returned WKT representation of simple feature geometry conforms to thesimple features access specification and extensions(known as EWKT, supported by PostGIS and other simple features implementations for addition ofa SRID to a WKT string).

Note

To improve conversion performance, the lwgeom package can be used (it must be installedbeforehand) and set theSys.setenv("LWGEOM_WKT" = "true") environment variable. Thiswill also result in faster printing of complex geometries. Note that the representation as WKT isdifferent from the sf package and may cause reproducibility problems. An alternative solution isto use thelwgeom::st_astext() orwk::as_wkt() functions.

Examples

st_as_text(st_point(1:2))st_as_text(st_sfc(st_point(c(-90,40)), crs = 4326), EWKT = TRUE)

Return bounding of a simple feature or simple feature set

Description

Return bounding of a simple feature or simple feature set

Usage

## S3 method for class 'bbox'is.na(x)st_bbox(obj, ...)## S3 method for class 'POINT'st_bbox(obj, ...)## S3 method for class 'MULTIPOINT'st_bbox(obj, ...)## S3 method for class 'LINESTRING'st_bbox(obj, ...)## S3 method for class 'POLYGON'st_bbox(obj, ...)## S3 method for class 'MULTILINESTRING'st_bbox(obj, ...)## S3 method for class 'MULTIPOLYGON'st_bbox(obj, ...)## S3 method for class 'GEOMETRYCOLLECTION'st_bbox(obj, ...)## S3 method for class 'MULTISURFACE'st_bbox(obj, ...)## S3 method for class 'MULTICURVE'st_bbox(obj, ...)## S3 method for class 'CURVEPOLYGON'st_bbox(obj, ...)## S3 method for class 'COMPOUNDCURVE'st_bbox(obj, ...)## S3 method for class 'POLYHEDRALSURFACE'st_bbox(obj, ...)## S3 method for class 'TIN'st_bbox(obj, ...)## S3 method for class 'TRIANGLE'st_bbox(obj, ...)## S3 method for class 'CIRCULARSTRING'st_bbox(obj, ...)## S3 method for class 'sfc'st_bbox(obj, ...)## S3 method for class 'sf'st_bbox(obj, ...)## S3 method for class 'Spatial'st_bbox(obj, ...)## S3 method for class 'Raster'st_bbox(obj, ...)## S3 method for class 'Extent'st_bbox(obj, ..., crs = NA_crs_)## S3 method for class 'numeric'st_bbox(obj, ..., crs = NA_crs_)NA_bbox_FULL_bbox_## S3 method for class 'bbox'format(x, ...)

Arguments

Format

An object of classbbox of length 4.

An object of classbbox of length 4.

Details

NA_bbox_ represents the missing value for abbox object

NA_bbox_ represents the missing value for abbox object

Value

a numeric vector of length four, withxmin,ymin,xmaxandymax values; ifobj is of classsf,sfc,Spatial orRaster, the objectreturned has a classbbox, an attributecrs and a method to print thebbox and anst_crs method to retrieve the coordinate reference systemcorresponding toobj (and hence the bounding box).st_as_sfc has amethods forbbox objects to generate a polygon around the four bounding box points.

Examples

a = st_sf(a = 1:2, geom = st_sfc(st_point(0:1), st_point(1:2)), crs = 4326)st_bbox(a)st_as_sfc(st_bbox(a))st_bbox(c(xmin = 16.1, xmax = 16.6, ymax = 48.6, ymin = 47.9), crs = st_crs(4326))

Break antimeridian for plotting not centred on Greenwich

Description

Longitudes can be broken at the antimeridian of a target central longitudeto permit plotting of (usually world) line or polygon objects centredon the chosen central longitude. The method may only be used withnon-projected, geographical coordinates and linestring or polygon objects.s2 is turned off internally to permit the use of a rectangular boundingbox. If the input geometries go outside⁠[-180, 180]⁠ degrees longitude,the protruding geometries will also be split using the sametol=values; in this case empty geometries will be dropped first.

Usage

st_break_antimeridian(x, lon_0 = 0, tol = 1e-04, ...)## S3 method for class 'sf'st_break_antimeridian(x, lon_0 = 0, tol = 1e-04, ...)## S3 method for class 'sfc'st_break_antimeridian(x, lon_0 = 0, tol = 1e-04, ...)

Arguments

Examples

if (require("maps", quietly=TRUE)) { opar = par(mfrow=c(3, 2)) wld = st_as_sf(map(fill=FALSE, interior=FALSE, plot=FALSE), fill=FALSE) for (lon_0 in c(-170, -90, -10, 10, 90, 170)) {   br = st_break_antimeridian(wld, lon_0 = lon_0)   tr = st_transform(br, paste0("+proj=natearth +lon_0=", lon_0))   plot(st_geometry(tr), main=lon_0) } par(opar)}

Cast geometry to another type: either simplify, or cast explicitly

Description

Cast geometry to another type: either simplify, or cast explicitly

Usage

## S3 method for class 'MULTIPOLYGON'st_cast(x, to, ...)## S3 method for class 'MULTILINESTRING'st_cast(x, to, ...)## S3 method for class 'MULTIPOINT'st_cast(x, to, ...)## S3 method for class 'POLYGON'st_cast(x, to, ...)## S3 method for class 'LINESTRING'st_cast(x, to, ...)## S3 method for class 'POINT'st_cast(x, to, ...)## S3 method for class 'GEOMETRYCOLLECTION'st_cast(x, to, ...)## S3 method for class 'CIRCULARSTRING'st_cast(x, to, ...)## S3 method for class 'MULTISURFACE'st_cast(x, to, ...)## S3 method for class 'COMPOUNDCURVE'st_cast(x, to, ...)## S3 method for class 'MULTICURVE'st_cast(x, to, ...)## S3 method for class 'CURVE'st_cast(x, to, ...)st_cast(x, to, ...)## S3 method for class 'sfc'st_cast(x, to, ..., ids = seq_along(x), group_or_split = TRUE)## S3 method for class 'sf'st_cast(x, to, ..., warn = TRUE, do_split = TRUE)## S3 method for class 'sfc_CIRCULARSTRING'st_cast(x, to, ...)

Arguments

Details

When converting a GEOMETRYCOLLECTION to COMPOUNDCURVE, MULTISURFACE or CURVEPOLYGON, the user is responsible for the validity of the resulting object: no checks are being carried out by the software.

When converting mixed, GEOMETRY sets, it may help to first convert to the MULTI-type, see examples

thest_cast method forsf objects can only split geometries, e.g. castMULTIPOINT into multiplePOINT features. In case of splitting, attributes are repeated and a warning is issued when non-constant attributes are assigned to sub-geometries. To merge feature geometries and attribute values, useaggregate orsummarise.

Value

object of classto if successful, or unmodified object if unsuccessful. If information gets lost while type casting, a warning is raised.

In caseto is missing,st_cast.sfc will coerce combinations of "POINT" and "MULTIPOINT", "LINESTRING" and "MULTILINESTRING", "POLYGON" and "MULTIPOLYGON" into their "MULTI..." form, or in case all geometries are "GEOMETRYCOLLECTION" will return a list of all the contents of the "GEOMETRYCOLLECTION" objects, or else do nothing. In caseto is specified, ifto is "GEOMETRY", geometries are not converted, else,st_cast will try to coerce all elements intoto;ids may be specified to group e.g. "POINT" objects into a "MULTIPOINT", if not specified no grouping takes place. If e.g. a "sfc_MULTIPOINT" is cast to a "sfc_POINT", the objects are split, so no information gets lost, unlessgroup_or_split isFALSE.

Examples

# example(st_read)nc = st_read(system.file("shape/nc.shp", package="sf"))mpl <- st_geometry(nc)[[4]]#st_cast(x) ## error 'argument "to" is missing, with no default'cast_all <- function(xg) {  lapply(c("MULTIPOLYGON", "MULTILINESTRING", "MULTIPOINT", "POLYGON", "LINESTRING", "POINT"),       function(x) st_cast(xg, x))}st_sfc(cast_all(mpl))## no closing coordinates should remain for multipointany(duplicated(unclass(st_cast(mpl, "MULTIPOINT"))))  ## should be FALSE## number of duplicated coordinates in the linestrings should equal the number of polygon rings ## (... in this case, won't always be true)sum(duplicated(do.call(rbind, unclass(st_cast(mpl, "MULTILINESTRING"))))     ) == sum(unlist(lapply(mpl, length)))  ## should be TRUEp1 <- structure(c(0, 1, 3, 2, 1, 0, 0, 0, 2, 4, 4, 0), .Dim = c(6L, 2L))p2 <- structure(c(1, 1, 2, 1, 1, 2, 2, 1), .Dim = c(4L, 2L))st_polygon(list(p1, p2))mls <- st_cast(st_geometry(nc)[[4]], "MULTILINESTRING")st_sfc(cast_all(mls))mpt <- st_cast(st_geometry(nc)[[4]], "MULTIPOINT")st_sfc(cast_all(mpt))pl <- st_cast(st_geometry(nc)[[4]], "POLYGON")st_sfc(cast_all(pl))ls <- st_cast(st_geometry(nc)[[4]], "LINESTRING")st_sfc(cast_all(ls))pt <- st_cast(st_geometry(nc)[[4]], "POINT")## st_sfc(cast_all(pt))  ## Error: cannot create MULTIPOLYGON from POINT st_sfc(lapply(c("POINT", "MULTIPOINT"), function(x) st_cast(pt, x)))s = st_multipoint(rbind(c(1,0)))st_cast(s, "POINT")# https://github.com/r-spatial/sf/issues/1930:pt1 <- st_point(c(0,1))pt23 <- st_multipoint(matrix(c(1,2,3,4), ncol = 2, byrow = TRUE))d <- st_sf(geom = st_sfc(pt1, pt23))st_cast(d, "POINT") # will not convert the entire MULTIPOINT, and warnsst_cast(d, "MULTIPOINT") %>% st_cast("POINT")

Coerce geometry to MULTI* geometry

Description

Mixes of POINTS and MULTIPOINTS, LINESTRING and MULTILINESTRING,POLYGON and MULTIPOLYGON are returned as MULTIPOINTS, MULTILINESTRING and MULTIPOLYGONS respectively

Usage

st_cast_sfc_default(x)

Arguments

Details

Geometries that are already MULTI* are left unchanged.Features that can't be cast to a single MULTI* geometry are return as aGEOMETRYCOLLECTION

Given an object with geometries of typeGEOMETRY orGEOMETRYCOLLECTION,return an object consisting only of elements of the specified type.

Description

Similar to ST_CollectionExtract in PostGIS. If there are no sub-geometriesof the specified type, an empty geometry is returned.

Usage

st_collection_extract(  x,  type = c("POLYGON", "POINT", "LINESTRING"),  warn = FALSE)## S3 method for class 'sfg'st_collection_extract(  x,  type = c("POLYGON", "POINT", "LINESTRING"),  warn = FALSE)## S3 method for class 'sfc'st_collection_extract(  x,  type = c("POLYGON", "POINT", "LINESTRING"),  warn = FALSE)## S3 method for class 'sf'st_collection_extract(  x,  type = c("POLYGON", "POINT", "LINESTRING"),  warn = FALSE)

Arguments

Value

An object having the same class asx, with geometriesconsisting only of elements of the specified type.Forsfg objects, ansfg object is returned if there is onlyone geometry of the specified type, otherwise the geometries are combinedinto ansfc object of the relevant type. If any subgeometries in theinput are MULTI, then all of the subgeometries in the output will be MULTI.

Examples

pt <- st_point(c(1, 0))ls <- st_linestring(matrix(c(4, 3, 0, 0), ncol = 2))poly1 <- st_polygon(list(matrix(c(5.5, 7, 7, 6, 5.5, 0, 0, -0.5, -0.5, 0), ncol = 2)))poly2 <- st_polygon(list(matrix(c(6.6, 8, 8, 7, 6.6, 1, 1, 1.5, 1.5, 1), ncol = 2)))multipoly <- st_multipolygon(list(poly1, poly2))i <- st_geometrycollection(list(pt, ls, poly1, poly2))j <- st_geometrycollection(list(pt, ls, poly1, poly2, multipoly))st_collection_extract(i, "POLYGON")st_collection_extract(i, "POINT")st_collection_extract(i, "LINESTRING")## A GEOMETRYCOLLECTIONaa <- rbind(st_sf(a=1, geom = st_sfc(i)),st_sf(a=2, geom = st_sfc(j)))## With sf objectsst_collection_extract(aa, "POLYGON")st_collection_extract(aa, "LINESTRING")st_collection_extract(aa, "POINT")## With sfc objectsst_collection_extract(st_geometry(aa), "POLYGON")st_collection_extract(st_geometry(aa), "LINESTRING")st_collection_extract(st_geometry(aa), "POINT")## A GEOMETRY of single typesbb <- rbind(st_sf(a = 1, geom = st_sfc(pt)),st_sf(a = 2, geom = st_sfc(ls)),st_sf(a = 3, geom = st_sfc(poly1)),st_sf(a = 4, geom = st_sfc(multipoly)))st_collection_extract(bb, "POLYGON")## A GEOMETRY of mixed single types and GEOMETRYCOLLECTIONScc <- rbind(aa, bb)st_collection_extract(cc, "POLYGON")

retrieve coordinates in matrix form

Description

retrieve coordinates in matrix form

Usage

st_coordinates(x, ...)

Arguments

Value

matrix with coordinates (X, Y, possibly Z and/or M) in rows, possibly followed by integer indicatorsL1,...,L3 that point out to which structure the coordinate belongs; forPOINT this is absent (each coordinate is a feature), forLINESTRINGL1 refers to the feature, forMULTILINESTRINGL1 refers to the part andL2 to the simple feature, forPOLYGONL1 refers to the main ring or holes andL2 to the simple feature, forMULTIPOLYGONL1 refers to the main ring or holes,L2 to the ring id in theMULTIPOLYGON, andL3 to the simple feature.

ForPOLYGONS,L1 can be used to identify exterior rings and inner holes.The exterior ring is whenL1 is equal to 1. Interior rings are identifiedwhenL1 is greater than 1.L2 can be used to differentiate between thefeature. Whereas forMULTIPOLYGON,L3 refers to theMULTIPOLYGONfeature andL2 refers to the componentPOLYGON.

crop an sf object to a specific rectangle

Description

crop an sf object to a specific rectangle

Usage

st_crop(x, y, ...)## S3 method for class 'sfc'st_crop(x, y, ..., xmin, ymin, xmax, ymax)## S3 method for class 'sf'st_crop(x, y, ...)

Arguments

Details

setting argumentsxmin,ymin,xmax andymax implies that argumenty gets ignored.

Examples

box = c(xmin = 0, ymin = 0, xmax = 1, ymax = 1)pol = st_sfc(st_buffer(st_point(c(.5, .5)), .6))pol_sf = st_sf(a=1, geom=pol)plot(st_crop(pol, box))plot(st_crop(pol_sf, st_bbox(box)))# alternative:plot(st_crop(pol, xmin = 0, ymin = 0, xmax = 1, ymax = 1))

Retrieve coordinate reference system from object

Description

Retrieve coordinate reference system from sf or sfc object

Set or replace retrieve coordinate reference system from object

Usage

st_crs(x, ...)## S3 method for class 'sf'st_crs(x, ...)## S3 method for class 'numeric'st_crs(x, ...)## S3 method for class 'character'st_crs(x, ...)## S3 method for class 'sfc'st_crs(x, ..., parameters = FALSE)## S3 method for class 'bbox'st_crs(x, ...)## S3 method for class 'CRS'st_crs(x, ...)## S3 method for class 'crs'st_crs(x, ...)st_crs(x) <- value## S3 replacement method for class 'sf'st_crs(x) <- value## S3 replacement method for class 'sfc'st_crs(x) <- valuest_set_crs(x, value)NA_crs_## S3 method for class 'crs'is.na(x)## S3 method for class 'crs'x$name## S3 method for class 'crs'format(x, ...)st_axis_order(authority_compliant = logical(0))

Arguments

Format

An object of classcrs of length 2.

Details

The *crs functions create, get, set or replace thecrs attributeof a simple feature geometry list-column. This attribute is of classcrs,and is a list consisting ofinput (user input, e.g. "EPSG:4326" or "WGS84"or a proj4string), andwkt, an automatically generated wkt2 representation of the crs.Ifx is identical to the wkt2 representation, and the CRS has a name, this nameis used for theinput field.

Comparison of two objects of classcrs uses the GDAL functionOGRSpatialReference::IsSame.

In case a coordinate reference system is replaced, no transformation takesplace and a warning is raised to stress this.

NA_crs_ is thecrs object with missing values forinput andwkt.

the$ method forcrs objects retrieves named elementsusing the GDAL interface; named elements includeSemiMajor,SemiMinor,InvFlattening,IsGeographic,units_gdal,IsVertical,WktPretty,Wkt,Name,proj4string,epsg,yx,ud_unit, andaxes (this may be subject to changes in future GDAL versions).

Note that not all valid CRS have a correspondingproj4string.

ud_unit returns a validunits object orNULL if units are missing.

format.crs returns NA if the crs is missing valued, or elsethe name of a crs if it is different from "unknown", orelse the user input if it was set, or else its "proj4string" representation;

st_axis_order can be used to get and set the axis order:TRUEindicates axes order according to the authority(e.g. EPSG:4326 defining coordinates to be latitude,longitude pairs),FALSEindicates the usual GIS (display) order (longitude,latitude). This can be usefulwhen data are read, or have to be written, with coordinates in authority compliant order.The return value is the current state of this (FALSE, by default).

Value

Ifx is numeric, returncrs object for EPSG:x;ifx is character, returncrs object forx;ifx is of classsf orsfc, return itscrs object.

Object of classcrs, which is a list with elementsinput (length-1 character)andwkt (length-1 character).Elements may beNA valued; if all elements areNA the CRS is missing valued, and coordinates areassumed to relate to an arbitrary Cartesian coordinate system.

st_axis_order returns the (logical) current value if called withoutargument, or (invisibly) the previous value if it is being set.

Examples

sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))sf = st_sf(a = 1:2, geom = sfc)st_crs(sf) = 4326st_geometry(sf)sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))st_crs(sfc) = 4326sfcsfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))sfc %>% st_set_crs(4326) %>% st_transform(3857)st_crs("EPSG:3857")$inputst_crs(3857)$proj4stringpt = st_sfc(st_point(c(0, 60)), crs = 4326)# st_axis_order() only has effect in GDAL >= 2.5.0:st_axis_order() # query default: FALSE means interpret pt as (longitude latitude)st_transform(pt, 3857)[[1]]old_value = FALSEif (compareVersion(sf_extSoftVersion()["GDAL"], "2.5.0") >= 0)   (old_value = st_axis_order(TRUE))# now interpret pt as (latitude longitude), as EPSG:4326 prescribes:st_axis_order() # query current valuest_transform(pt, 3857)[[1]]st_axis_order(old_value) # set back to old value

Get GDAL drivers

Description

Get a list of the available GDAL drivers

Usage

st_drivers(what = "vector", regex)

Arguments

Details

The drivers available will depend on the installation of GDAL/OGR,and can vary; thest_drivers() function shows all the drivers that arereadable, and which may be written. The fieldvsi refers to the driver'scapability to read/create datasets through the VSI*L API.See GDAL website for additional details on driver support

Value

Adata.frame with driver metadata.

Examples

# The following driver lists depend on the GDAL setup and platform used:st_drivers()st_drivers("raster", "GeoT")

Get, set, replace or rename geometry from an sf object

Description

Get, set, replace or rename geometry from an sf object

Usage

## S3 method for class 'sfc'st_geometry(obj, ...)st_geometry(obj, ...)## S3 method for class 'sf'st_geometry(obj, ...)## S3 method for class 'sfc'st_geometry(obj, ...)## S3 method for class 'sfg'st_geometry(obj, ...)st_geometry(x) <- valuest_set_geometry(x, value)st_drop_geometry(x, ...)## S3 method for class 'sf'st_drop_geometry(x, ...)## Default S3 method:st_drop_geometry(x, ...)

Arguments

Details

when applied to adata.frame and whenvalue is an object of classsfc,st_set_geometry andst_geometry<- will first check for the existence of an attributesf_column and overwrite that, or else look for list-columns of classsfc and overwrite the first of that, or else write the geometry list-column to a column namedgeometry. In casevalue is character andx is of classsf, the "active" geometry column is set tox[[value]].

the replacement function applied tosf objects will overwrite the geometry list-column, ifvalue isNULL, it will remove it and coercex to adata.frame.

ifx is of classsf,st_drop_geometry drops the geometry of its argument, and reclasses it accordingly; otherwise it returnsx unmodified.

Value

st_geometry returns an object of classsfc, a list-column with geometries

st_geometry returns an object of classsfc. Assigning geometry to adata.frame creates ansf object, assigning it to ansf object replaces the geometry list-column.

Examples

df = data.frame(a = 1:2)sfc = st_sfc(st_point(c(3,4)), st_point(c(10,11)))st_geometry(sfc)st_geometry(df) <- sfcclass(df)st_geometry(df)st_geometry(df) <- sfc # replacesst_geometry(df) <- NULL # remove geometry, coerce to data.framesf <- st_set_geometry(df, sfc) # set geometry, return sfst_set_geometry(sf, NULL) # remove geometry, coerce to data.frame

Return geometry type of an object

Description

Return geometry type of an object, as a factor

Usage

st_geometry_type(x, by_geometry = TRUE)

Arguments

Value

a factor with the geometry type of each simple feature geometryinx, or that of the whole set

Compute graticules and their parameters

Description

Compute graticules and their parameters

Usage

st_graticule(  x = c(-180, -90, 180, 90),  crs = st_crs(x),  datum = st_crs(4326),  ...,  lon = NULL,  lat = NULL,  ndiscr = 100,  margin = 0.001)

Arguments

Value

an object of classsf with additional attributes describing the type(E: meridian, N: parallel) degree value, label, start and end coordinates and angle;see example.

Use of graticules

In cartographic visualization, the use of graticules is not advised, unlessthe graphical output will be used for measurement or navigation, or thedirection of North is important for the interpretation of the content, orthe content is intended to display distortions and artifacts created byprojection. Unnecessary use of graticules only adds visual clutter butlittle relevant information. Use of coastlines, administrative boundariesor place names permits most viewers of the output to orient themselvesbetter than a graticule.

Examples

library(sf)if (require(maps, quietly = TRUE)) {usa = st_as_sf(map('usa', plot = FALSE, fill = TRUE))laea = st_crs("+proj=laea +lat_0=30 +lon_0=-95") # Lambert equal areausa <- st_transform(usa, laea)bb = st_bbox(usa)bbox = st_linestring(rbind(c( bb[1],bb[2]),c( bb[3],bb[2]),   c( bb[3],bb[4]),c( bb[1],bb[4]),c( bb[1],bb[2])))g = st_graticule(usa)plot(usa, xlim = 1.2 * c(-2450853.4, 2186391.9), reset = FALSE)plot(g[1], add = TRUE, col = 'grey')plot(bbox, add = TRUE)points(g$x_start, g$y_start, col = 'red')points(g$x_end, g$y_end, col = 'blue')invisible(lapply(seq_len(nrow(g)), function(i) {if (g$type[i] == "N" && g$x_start[i] - min(g$x_start) < 1000)text(g$x_start[i], g$y_start[i], labels = parse(text = g$degree_label[i]), srt = g$angle_start[i], pos = 2, cex = .7)if (g$type[i] == "E" && g$y_start[i] - min(g$y_start) < 1000)text(g$x_start[i], g$y_start[i], labels = parse(text = g$degree_label[i]), srt = g$angle_start[i] - 90, pos = 1, cex = .7)if (g$type[i] == "N" && g$x_end[i] - max(g$x_end) > -1000)text(g$x_end[i], g$y_end[i], labels = parse(text = g$degree_label[i]), srt = g$angle_end[i], pos = 4, cex = .7)if (g$type[i] == "E" && g$y_end[i] - max(g$y_end) > -1000)text(g$x_end[i], g$y_end[i], labels = parse(text = g$degree_label[i]), srt = g$angle_end[i] - 90, pos = 3, cex = .7)}))plot(usa, graticule = st_crs(4326), axes = TRUE, lon = seq(-60,-130,by=-10))}

test equality between the geometry type and a class or set of classes

Description

test equality between the geometry type and a class or set of classes

Usage

st_is(x, type)

Arguments

Examples

st_is(st_point(0:1), "POINT")sfc = st_sfc(st_point(0:1), st_linestring(matrix(1:6,,2)))st_is(sfc, "POINT")st_is(sfc, "POLYGON")st_is(sfc, "LINESTRING")st_is(st_sf(a = 1:2, sfc), "LINESTRING")st_is(sfc, c("POINT", "LINESTRING"))

predicate whether a geometry is equal to a POLYGON FULL

Description

predicate whether a geometry is equal to a POLYGON FULL

Usage

st_is_full(x, ...)## S3 method for class 'sfg'st_is_full(x, ..., is_longlat = NULL)## S3 method for class 'sfc'st_is_full(x, ...)## S3 method for class 'sf'st_is_full(x, ...)## S3 method for class 'bbox'st_is_full(x, ...)

Arguments

Value

logical, indicating whether geometries are POLYGON FULL (a sphericalpolygon covering the entire sphere)

Assert whether simple feature coordinates are longlat degrees

Description

Assert whether simple feature coordinates are longlat degrees

Usage

st_is_longlat(x)

Arguments

Value

TRUE ifx has geographic coordinates,FALSE if it has projected coordinates, orNA ifis.na(st_crs(x)).

jitter geometries

Description

jitter geometries

Usage

st_jitter(x, amount, factor = 0.002)

Arguments

Details

jitters coordinates with an amount such thatrunif(1, -amount, amount) is added to the coordinates. x- and y-coordinates are jittered independently but all coordinates of a single geometry are jittered with the same amount, meaning that the geometry shape does not change. For longlat data, a latitude correction is made such that jittering in East and North directions are identical in distance in the center of the bounding box ofx.

Examples

nc = st_read(system.file("gpkg/nc.gpkg", package="sf"))pts = st_centroid(st_geometry(nc))plot(pts)plot(st_jitter(pts, .05), add = TRUE, col = 'red')plot(st_geometry(nc))plot(st_jitter(st_geometry(nc), factor = .01), add = TRUE, col = '#ff8888')

spatial join, spatial filter

Description

spatial join, spatial filter

Usage

st_join(x, y, join, ...)## S3 method for class 'sf'st_join(  x,  y,  join = st_intersects,  ...,  suffix = c(".x", ".y"),  left = TRUE,  largest = FALSE)st_filter(x, y, ...)## S3 method for class 'sf'st_filter(x, y, ..., .predicate = st_intersects)

Arguments

Details

alternative values for argumentjoin are:

• st_contains_properly,

• st_contains,

• st_covered_by,

• st_covers,

• st_crosses,

• st_disjoint,

• st_equals_exact,

• st_equals,

• st_is_within_distance,

• st_nearest_feature,

• st_overlaps,

• st_touches,

• st_within,

• st_relate (which will requirepattern to be set),

• or any user-defined function of the same profile as the above

A left join returns all records of thex object withy fields for non-matched records filled withNA values; an inner join returns only records that spatially match.

To replicate the results ofst_within(x, y) you will need to usest_join(x, y, join = "st_within", left = FALSE).

Value

an object of classsf, joined based on geometry

Examples

a = st_sf(a = 1:3, geom = st_sfc(st_point(c(1,1)), st_point(c(2,2)), st_point(c(3,3))))b = st_sf(a = 11:14, geom = st_sfc(st_point(c(10,10)), st_point(c(2,2)), st_point(c(2,2)), st_point(c(3,3))))st_join(a, b)st_join(a, b, left = FALSE)# two ways to aggregate y's attribute values outcome over x's geometries:st_join(a, b) %>% aggregate(list(.$a.x), mean)if (require(dplyr, quietly = TRUE)) { st_join(a, b) %>% group_by(a.x) %>% summarise(mean(a.y))}# example of largest = TRUE:nc <- st_transform(st_read(system.file("shape/nc.shp", package="sf")), 2264)                gr = st_sf(    label = apply(expand.grid(1:10, LETTERS[10:1])[,2:1], 1, paste0, collapse = " "),    geom = st_make_grid(st_as_sfc(st_bbox(nc))))gr$col = sf.colors(10, categorical = TRUE, alpha = .3)# cut, to check, NA's work out:gr = gr[-(1:30),]nc_j <- st_join(nc, gr, largest = TRUE)# the two datasets:opar = par(mfrow = c(2,1), mar = rep(0,4))plot(st_geometry(nc_j))plot(st_geometry(gr), add = TRUE, col = gr$col)text(st_coordinates(st_centroid(gr)), labels = gr$label)# the joined dataset:plot(st_geometry(nc_j), border = 'black', col = nc_j$col)text(st_coordinates(st_centroid(nc_j)), labels = nc_j$label, cex = .8)plot(st_geometry(gr), border = 'green', add = TRUE)par(opar)# st_filter keeps the geometries in x where .predicate(x,y) returns any match in y for xst_filter(a, b)# for an anti-join, use the union of yst_filter(a, st_union(b), .predicate = st_disjoint)

Return properties of layers in a datasource

Description

Return properties of layers in a datasource

Usage

st_layers(dsn, options = character(0), do_count = FALSE)

Arguments

Value

list object of classsf_layers with elements

name

name of the layer

geomtype

list with for each layer the geometry types

features

number of features (if reported; seedo_count)

fields

number of fields

crs

list with for each layer thecrs object

Project point on linestring, interpolate along a linestring

Description

Project point on linestring, interpolate along a linestring

Usage

st_line_project(line, point, normalized = FALSE)st_line_interpolate(line, dist, normalized = FALSE)

Arguments

Details

argumentsline,point anddist are recycled to common length when needed

Value

st_line_project returns the distance(s) of point(s) along line(s), when projected on the line(s)

st_line_interpolate returns the point(s) at dist(s), when measured along (interpolated on) the line(s)

Examples

st_line_project(st_as_sfc("LINESTRING (0 0, 10 10)"), st_as_sfc(c("POINT (0 0)", "POINT (5 5)")))st_line_project(st_as_sfc("LINESTRING (0 0, 10 10)"), st_as_sfc("POINT (5 5)"), TRUE)st_line_interpolate(st_as_sfc("LINESTRING (0 0, 1 1)"), 1)st_line_interpolate(st_as_sfc("LINESTRING (0 0, 1 1)"), 1, TRUE)# https://github.com/r-spatial/sf/issues/2542; use for geographic coordinates:l1 <- st_as_sfc("LINESTRING (10.1 50.1, 10.2 50.2)", crs = 'OGC:CRS84')dists = units::set_units(seq(0, sqrt(2)/10, length.out = 5), degrees)st_line_interpolate(l1, dists)

Sample points on a linear geometry

Description

Sample points on a linear geometry

Usage

st_line_sample(x, n, density, type = "regular", sample = NULL)

Arguments

Examples

ls = st_sfc(st_linestring(rbind(c(0,0),c(0,1))),st_linestring(rbind(c(0,0),c(10,0))))st_line_sample(ls, density = 1)ls = st_sfc(st_linestring(rbind(c(0,0),c(0,1))), st_linestring(rbind(c(0,0),c(.1,0))), crs = 4326)try(st_line_sample(ls, density = 1/1000)) # errorst_line_sample(st_transform(ls, 3857), n = 5) # five points for each linest_line_sample(st_transform(ls, 3857), n = c(1, 3)) # one and three pointsst_line_sample(st_transform(ls, 3857), density = 1/1000) # one per kmst_line_sample(st_transform(ls, 3857), density = c(1/1000, 1/10000)) # one per km, one per 10 kmst_line_sample(st_transform(ls, 3857), density = units::set_units(1, 1/km)) # one per km# five equidistant points including start and end:st_line_sample(st_transform(ls, 3857), sample = c(0, 0.25, 0.5, 0.75, 1))

Return 'm' range of a simple feature or simple feature set

Description

Return 'm' range of a simple feature or simple feature set

Usage

## S3 method for class 'm_range'is.na(x)st_m_range(obj, ...)## S3 method for class 'POINT'st_m_range(obj, ...)## S3 method for class 'MULTIPOINT'st_m_range(obj, ...)## S3 method for class 'LINESTRING'st_m_range(obj, ...)## S3 method for class 'POLYGON'st_m_range(obj, ...)## S3 method for class 'MULTILINESTRING'st_m_range(obj, ...)## S3 method for class 'MULTIPOLYGON'st_m_range(obj, ...)## S3 method for class 'GEOMETRYCOLLECTION'st_m_range(obj, ...)## S3 method for class 'MULTISURFACE'st_m_range(obj, ...)## S3 method for class 'MULTICURVE'st_m_range(obj, ...)## S3 method for class 'CURVEPOLYGON'st_m_range(obj, ...)## S3 method for class 'COMPOUNDCURVE'st_m_range(obj, ...)## S3 method for class 'POLYHEDRALSURFACE'st_m_range(obj, ...)## S3 method for class 'TIN'st_m_range(obj, ...)## S3 method for class 'TRIANGLE'st_m_range(obj, ...)## S3 method for class 'CIRCULARSTRING'st_m_range(obj, ...)## S3 method for class 'sfc'st_m_range(obj, ...)## S3 method for class 'sf'st_m_range(obj, ...)## S3 method for class 'numeric'st_m_range(obj, ..., crs = NA_crs_)NA_m_range_

Arguments

Format

An object of classm_range of length 2.

Details

NA_m_range_ represents the missing value for am_range object

Value

a numeric vector of length two, withmmin andmmax values;ifobj is of classsf orsfc the objectifobj is of classsf orsfc the objectreturned has a classm_range

Examples

a = st_sf(a = 1:2, geom = st_sfc(st_point(0:3), st_point(1:4)), crs = 4326)st_m_range(a)st_m_range(c(mmin = 16.1, mmax = 16.6), crs = st_crs(4326))

Create a regular tesselation over the bounding box of an sf or sfc object

Description

Create a square or hexagonal grid covering the bounding box of the geometry of an sf or sfc object

Usage

st_make_grid(  x,  cellsize = c(diff(st_bbox(x)[c(1, 3)]), diff(st_bbox(x)[c(2, 4)]))/n,  offset = st_bbox(x)[c("xmin", "ymin")],  n = c(10, 10),  crs = if (missing(x)) NA_crs_ else st_crs(x),  what = "polygons",  square = TRUE,  flat_topped = FALSE)

Arguments

Value

Object of classsfc (simple feature geometry list column) with, depending onwhat andsquare,square or hexagonal polygons, corner points of these polygons, or center points of these polygons.

Examples

plot(st_make_grid(what = "centers"), axes = TRUE)plot(st_make_grid(what = "corners"), add = TRUE, col = 'green', pch=3)sfc = st_sfc(st_polygon(list(rbind(c(0,0), c(1,0), c(1,1), c(0,0)))))plot(st_make_grid(sfc, cellsize = .1, square = FALSE))plot(sfc, add = TRUE)# non-default offset:plot(st_make_grid(sfc, cellsize = .1, square = FALSE, offset = c(0, .05 / (sqrt(3)/2))))plot(sfc, add = TRUE)nc = st_read(system.file("shape/nc.shp", package="sf"))g = st_make_grid(nc)plot(g)plot(st_geometry(nc), add = TRUE)# g[nc] selects cells that intersect with nc:plot(g[nc], col = '#ff000088', add = TRUE)

get index of nearest feature

Description

get index of nearest feature

Usage

st_nearest_feature(  x,  y,  ...,  check_crs = TRUE,  longlat = isTRUE(st_is_longlat(x)))

Arguments

Value

for each feature (geometry) inx the index of the nearest feature (geometry) insety, or in the remaining set ofx ify is missing;empty geometries result inNA indexes

See Also

st_nearest_points for finding the nearest points for pairs of feature geometries

Examples

ls1 = st_linestring(rbind(c(0,0), c(1,0)))ls2 = st_linestring(rbind(c(0,0.1), c(1,0.1)))ls3 = st_linestring(rbind(c(0,1), c(1,1)))(l = st_sfc(ls1, ls2, ls3))p1 = st_point(c(0.1, -0.1))p2 = st_point(c(0.1, 0.11))p3 = st_point(c(0.1, 0.09))p4 = st_point(c(0.1, 0.9))(p = st_sfc(p1, p2, p3, p4))try(st_nearest_feature(p, l))try(st_nearest_points(p, l[st_nearest_feature(p,l)], pairwise = TRUE))r = sqrt(2)/10b1 = st_buffer(st_point(c(.1,.1)), r)b2 = st_buffer(st_point(c(.9,.9)), r)b3 = st_buffer(st_point(c(.9,.1)), r)circles = st_sfc(b1, b2, b3)plot(circles, col = NA, border = 2:4)pts = st_sfc(st_point(c(.3,.1)), st_point(c(.6,.2)), st_point(c(.6,.6)), st_point(c(.4,.8)))plot(pts, add = TRUE, col = 1)# draw points to nearest circle:nearest = try(st_nearest_feature(pts, circles))if (inherits(nearest, "try-error")) # GEOS 3.6.1 not available  nearest = c(1, 3, 2, 2)ls = st_nearest_points(pts, circles[nearest], pairwise = TRUE)plot(ls, col = 5:8, add = TRUE)# compute distance between pairs of nearest features:st_distance(pts, circles[nearest], by_element = TRUE)

get nearest points between pairs of geometries

Description

get nearest points between pairs of geometries

Usage

st_nearest_points(x, y, ...)## S3 method for class 'sfc'st_nearest_points(x, y, ..., pairwise = FALSE)## S3 method for class 'sfg'st_nearest_points(x, y, ...)## S3 method for class 'sf'st_nearest_points(x, y, ...)

Arguments

Details

in casex lies insidey, when using S2, the end pointsare on polygon boundaries, when using GEOS the end point are identical tox.

Value

ansfc object with all two-pointLINESTRING geometries of point pairs from the first to the second geometry, of length x * y, with y cycling fastest. See examples for ideas how to convert these toPOINT geometries.

See Also

st_nearest_feature for finding the nearest feature

Examples

r = sqrt(2)/10pt1 = st_point(c(.1,.1))pt2 = st_point(c(.9,.9))pt3 = st_point(c(.9,.1))b1 = st_buffer(pt1, r)b2 = st_buffer(pt2, r)b3 = st_buffer(pt3, r)(ls0 = st_nearest_points(b1, b2)) # sfg(ls = st_nearest_points(st_sfc(b1), st_sfc(b2, b3))) # sfcplot(b1, xlim = c(-.2,1.2), ylim = c(-.2,1.2), col = NA, border = 'green')plot(st_sfc(b2, b3), add = TRUE, col = NA, border = 'blue')plot(ls, add = TRUE, col = 'red')nc = st_read(system.file("gpkg/nc.gpkg", package="sf"))plot(st_geometry(nc))ls = st_nearest_points(nc[1,], nc)plot(ls, col = 'red', add = TRUE)pts = st_cast(ls, "POINT") # gives all start & end points# starting, "from" points, corresponding to x:plot(pts[seq(1, 200, 2)], add = TRUE, col = 'blue')# ending, "to" points, corresponding to y:plot(pts[seq(2, 200, 2)], add = TRUE, col = 'green')

Normalize simple features

Description

st_normalize transforms the coordinates in the input feature to fallbetween 0 and 1. By default the current domain is set to the bounding box ofthe input, but other domains can be used as well

Usage

st_normalize(x, domain = st_bbox(x), ...)

Arguments

Examples

p1 = st_point(c(7,52))st_normalize(p1, domain = c(0, 0, 10, 100))p2 = st_point(c(-30,20))sfc = st_sfc(p1, p2, crs = 4326)sfcsfc_norm <- st_normalize(sfc)st_bbox(sfc_norm)

Get precision

Description

Get precision

Set precision

Usage

st_precision(x)st_set_precision(x, precision)st_precision(x) <- value

Arguments

Details

Ifprecision is aunits object, the object on which we set precision must have a coordinate reference system with compatible distance units.

Setting aprecision has no direct effect on coordinates of geometries, but merely set an attribute tag to ansfc object.The effect takes place inst_as_binary or, more precise, in the C++ functionCPL_write_wkb, where simple feature geometries are being serialized to well-known-binary (WKB).This happens always when routines are called in GEOS library (geometrical operations or predicates), for writing geometries usingst_write orwrite_sf,st_make_valid in packagelwgeom; alsoaggregate andsummarise by default union geometries, which calls a GEOS library function.Routines in these libraries receive rounded coordinates, and possibly return results based on them.st_as_binary contains an example of a roundtrip ofsfc geometries through WKB, in order to see the rounding happening to R data.

The reason to support precision is that geometrical operations in GEOS or liblwgeom may work better at reduced precision. For writing data from R to external resources it is harder to think of a good reason to limiting precision.

See Also

st_as_binary for an explanation of what setting precision does, and the examples therein.

Examples

x <- st_sfc(st_point(c(pi, pi)))st_precision(x)st_precision(x) <- 0.01st_precision(x)

Read simple features or layers from file or database

Description

Read simple features from file or database, or retrieve layer names and theirgeometry type(s)

Read PostGIS table directly through DBI and RPostgreSQL interface, convertingWell-Know Binary geometries to sfc

Usage

st_read(dsn, layer, ...)## S3 method for class 'character'st_read(  dsn,  layer,  ...,  query = NA,  options = NULL,  quiet = FALSE,  geometry_column = 1L,  type = 0,  promote_to_multi = TRUE,  stringsAsFactors = sf_stringsAsFactors(),  int64_as_string = FALSE,  check_ring_dir = FALSE,  fid_column_name = character(0),  drivers = character(0),  wkt_filter = character(0),  optional = FALSE,  use_stream = default_st_read_use_stream())read_sf(..., quiet = TRUE, stringsAsFactors = FALSE, as_tibble = TRUE)## S3 method for class 'DBIObject'st_read(  dsn = NULL,  layer = NULL,  query = NULL,  EWKB = TRUE,  quiet = TRUE,  as_tibble = FALSE,  geometry_column = NULL,  ...)

Arguments

Details

forgeometry_column, see alsohttps://gdal.org/en/latest/development/rfc/rfc41_multiple_geometry_fields.html

for values fortype seehttps://en.wikipedia.org/wiki/Well-known_text_representation_of_geometry#Well-known_binary,but note that not every target value may lead to successful conversion. Thetypical conversion from POLYGON (3) to MULTIPOLYGON (6) should work; theother way around (type=3), secondary rings from MULTIPOLYGONS may be droppedwithout warnings.promote_to_multi is handled on a per-geometry columnbasis;type may be specified for each geometry column.

Note that stray files in data source directories (such as*.dbf) maylead to spurious errors that accompanying*.shp are missing.

In case of problems reading shapefiles from USB drives on OSX, please seehttps://github.com/r-spatial/sf/issues/252. Reading shapefiles (or otherdata sources) directly from zip files can be done by prepending the pathwith/vsizip/. This is part of the GDAL Virtual File Systems interfacethat also supports .gz, curl, and other operations, including chaining; seehttps://gdal.org/en/latest/user/virtual_file_systems.html for a completedescription and examples.

Forquery with a characterdsn the query text is handed to'ExecuteSQL' on the GDAL/OGR data set and will result in the creation of anew layer (andlayer is ignored). See 'OGRSQL'https://gdal.org/en/latest/user/ogr_sql_dialect.html for details. Please note that the'FID' special field is driver-dependent, and may be either 0-based (e.g. ESRIShapefile), 1-based (e.g. MapInfo) or arbitrary (e.g. OSM). Other features ofOGRSQL are also likely to be driver dependent. The available layer names maybe obtained withst_layers. Care will be required to properly escape the use of some layer names.

read_sf andwrite_sf are aliases forst_read andst_write, respectively, with somemodified default arguments.read_sf andwrite_sf are quiet by default: they do not print informationabout the data source.read_sf returns an sf-tibble rather than an sf-data.frame.write_sf delete layers by default: it overwrites existing files without asking or warning.

iftable is not given butquery is, the spatialreference system (crs) of the table queried is only available in case ithas been stored into each geometry record (e.g., by PostGIS, when usingEWKB)

The function will automatically find thegeometry type columns fordrivers that support it. For the other drivers, it will try to cast all thecharacter columns, which can be slow for very wide tables.

Value

object of classsf when a layer was successfully read; in caseargumentlayer is missing and data sourcedsn does notcontain a single layer, an object of classsf_layers is returnedwith the layer names, each with their geometry type(s). Note that thenumber of layers may also be zero.

Note

The use ofsystem.file in examples make sure that examples run regardless where R is installed:typical users will not usesystem.file but give the file name directly, either with full path or relativeto the current working directory (seegetwd). "Shapefiles" consist of several files with the same basenamethat reside in the same directory, only one of them having extension.shp.

See Also

st_layers,st_drivers

Examples

nc = st_read(system.file("shape/nc.shp", package="sf"))summary(nc) # note that AREA was computed using Euclidian area on lon/lat degrees## only three fields by select clause## only two features by where clausenc_sql = st_read(system.file("shape/nc.shp", package="sf"),                     query = "SELECT NAME, SID74, FIPS FROM \"nc\" WHERE BIR74 > 20000")## Not run:   library(sp)  example(meuse, ask = FALSE, echo = FALSE)  try(st_write(st_as_sf(meuse), "PG:dbname=postgis", "meuse",       layer_options = "OVERWRITE=true"))  try(st_meuse <- st_read("PG:dbname=postgis", "meuse"))  if (exists("st_meuse"))    summary(st_meuse)## End(Not run)## Not run: ## note that we need special escaping of layer  within single quotes (nc.gpkg)## and that geom needs to be included in the select, otherwise we don't detect itlayer <- st_layers(system.file("gpkg/nc.gpkg", package = "sf"))$name[1]nc_gpkg_sql = st_read(system.file("gpkg/nc.gpkg", package = "sf"),   query = sprintf("SELECT NAME, SID74, FIPS, geom  FROM \"%s\" WHERE BIR74 > 20000", layer))## End(Not run)# spatial filter, as wkt:wkt = st_as_text(st_geometry(nc[1,]))# filter by (bbox overlaps of) first feature geometry:st_read(system.file("gpkg/nc.gpkg", package="sf"), wkt_filter = wkt)# read geojson from string:geojson_txt <- paste("{\"type\":\"MultiPoint\",\"coordinates\":",   "[[3.2,4],[3,4.6],[3.8,4.4],[3.5,3.8],[3.4,3.6],[3.9,4.5]]}")x = st_read(geojson_txt)x## Not run: library(RPostgreSQL)try(conn <- dbConnect(PostgreSQL(), dbname = "postgis"))if (exists("conn") && !inherits(conn, "try-error")) {  x = st_read(conn, "meuse", query = "select * from meuse limit 3;")  x = st_read(conn, table = "public.meuse")  print(st_crs(x)) # SRID resolved by the database, not by GDAL!  dbDisconnect(conn) }## End(Not run)

Compute DE9-IM relation between pairs of geometries, or match it to a given pattern

Description

Compute DE9-IM relation between pairs of geometries, or match it to a given pattern

Usage

st_relate(x, y, pattern = NA_character_, sparse = !is.na(pattern))

Arguments

Value

In casepattern is not given,st_relate returns a densecharacter matrix; element⁠[i,j]⁠ has nine characters, referring to the DE9-IM relationship betweenx[i] andy[j], encoded as IxIy,IxBy,IxEy,BxIy,BxBy,BxEy,ExIy,ExBy,ExEy where I refers to interior, B to boundary, and E to exterior, and e.g. BxIy the dimensionality of the intersection of the the boundary ofx[i] and the interior ofy[j], which is one of: 0, 1, 2, or F; digits denoting dimensionality of intersection, F denoting no intersection. Whenpattern is given, a dense logical matrix or sparse index list returned with matches to the given pattern; seest_intersects for a description of the returned matrix or list. See alsohttps://en.wikipedia.org/wiki/DE-9IM for further explanation.

Examples

p1 = st_point(c(0,0))p2 = st_point(c(2,2))pol1 = st_polygon(list(rbind(c(0,0),c(1,0),c(1,1),c(0,1),c(0,0)))) - 0.5pol2 = pol1 + 1pol3 = pol1 + 2st_relate(st_sfc(p1, p2), st_sfc(pol1, pol2, pol3))sfc = st_sfc(st_point(c(0,0)), st_point(c(3,3)))grd = st_make_grid(sfc, n = c(3,3))st_intersects(grd)st_relate(grd, pattern = "****1****") # sides, not corners, internalsst_relate(grd, pattern = "****0****") # only corners touchst_rook = function(a, b = a) st_relate(a, b, pattern = "F***1****")st_rook(grd)# queen neighbours, see \url{https://github.com/r-spatial/sf/issues/234#issuecomment-300511129}st_queen <- function(a, b = a) st_relate(a, b, pattern = "F***T****")

sample points on or in (sets of) spatial features

Description

Sample points on or in (sets of) spatial features.By default, returns a pre-specified number of points that is equal tosize (iftype = "random" andexact = TRUE) or an approximation ofsize otherwise.spatstat methods areinterfaced and do not use thesize argument, see examples.

Usage

st_sample(x, size, ...)## S3 method for class 'sf'st_sample(x, size, ...)## S3 method for class 'sfc'st_sample(  x,  size,  ...,  type = "random",  exact = TRUE,  warn_if_not_integer = TRUE,  by_polygon = FALSE,  progress = FALSE,  force = FALSE)## S3 method for class 'sfg'st_sample(x, size, ...)## S3 method for class 'bbox'st_sample(  x,  size,  ...,  great_circles = FALSE,  segments = units::set_units(2, "degree", mode = "standard"))

Arguments

Details

The function is vectorised: it samplessize points across all geometries inthe object ifsize is a single number, or the specified number of pointsin each feature ifsize is a vector of integers equal in length to the geometryofx.

ifx has dimension 2 (polygons) and geographical coordinates (long/lat), uniform random sampling on the sphere is applied, see e.g.https://mathworld.wolfram.com/SpherePointPicking.html.

Forregular orhexagonal sampling of polygons, the resulting size is only an approximation.

As parameter calledoffset can be passed to control ("fix") regular or hexagonal sampling: for polygons a length 2 numeric vector (by default: a random point fromst_bbox(x)); for lines use a number likerunif(1).

Fibonacci sampling see: Alvaro Gonzalez, 2010. Measurement of Areas on a Sphere Using Fibonacci and Latitude-Longitude Lattices.Mathematical Geosciences 42(1), p. 49-64

For regular sampling on the sphere, see alsogeosphere::regularCoordinates.

Sampling methods from packagespatstat are interfaced (see examples), and need their own parameters to be set.For instance, to usespatstat.random::rThomas(), settype = "Thomas".

For sampling polygons one can specifyoriented=TRUE to make sure that polygons larger than half the globe are not reverted, e.g. when specifying a polygon from a bounding box of a global dataset. Thest_sample method forbbox does this by default.

Value

ansfc object containing the sampledPOINT geometries

Examples

nc = st_read(system.file("shape/nc.shp", package="sf"))p1 = st_sample(nc[1:3, ], 6)p2 = st_sample(nc[1:3, ], 1:3)plot(st_geometry(nc)[1:3])plot(p1, add = TRUE)plot(p2, add = TRUE, pch = 2)x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,90),c(0,90),c(0,0)))), crs = st_crs(4326))plot(x, axes = TRUE, graticule = TRUE)if (compareVersion(sf_extSoftVersion()["proj.4"], "4.9.0") >= 0)  plot(p <- st_sample(x, 1000), add = TRUE)if (require(lwgeom, quietly = TRUE)) { # for st_segmentize()  x2 = st_transform(st_segmentize(x, 1e4), st_crs("+proj=ortho +lat_0=30 +lon_0=45"))  g = st_transform(st_graticule(), st_crs("+proj=ortho +lat_0=30 +lon_0=45"))  plot(x2, graticule = g)  if (compareVersion(sf_extSoftVersion()["proj.4"], "4.9.0") >= 0) {    p2 = st_transform(p, st_crs("+proj=ortho +lat_0=30 +lon_0=45"))    plot(p2, add = TRUE)  }}x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,10),c(0,90),c(0,0))))) # NOT long/lat:plot(x)p_exact = st_sample(x, 1000, exact = TRUE)p_not_exact = st_sample(x, 1000, exact = FALSE)length(p_exact); length(p_not_exact)plot(st_sample(x, 1000), add = TRUE)x = st_sfc(st_polygon(list(rbind(c(-180,-90),c(180,-90),c(180,90),c(-180,90),c(-180,-90)))), crs=st_crs(4326))# FIXME:#if (compareVersion(sf_extSoftVersion()["proj.4"], "4.9.0") >= 0) {#  p = st_sample(x, 1000)#  st_sample(p, 3)#}# hexagonal:sfc = st_sfc(st_polygon(list(rbind(c(0,0), c(1,0), c(1,1), c(0,0)))))plot(sfc)h = st_sample(sfc, 100, type = "hexagonal")h1 = st_sample(sfc, 100, type = "hexagonal")plot(h, add = TRUE)plot(h1, col = 'red', add = TRUE)c(length(h), length(h1)) # approximate!pt = st_multipoint(matrix(1:20,,2))ls = st_sfc(st_linestring(rbind(c(0,0),c(0,1))), st_linestring(rbind(c(0,0),c(.1,0))), st_linestring(rbind(c(0,1),c(.1,1))), st_linestring(rbind(c(2,2),c(2,2.00001))))st_sample(ls, 80)plot(st_sample(ls, 80))# spatstat example:if (require(spatstat.random)) {  x <- sf::st_sfc(sf::st_polygon(list(rbind(c(0, 0), c(10, 0), c(10, 10), c(0, 0)))))  # for spatstat.random::rThomas(), set type = "Thomas":  pts <- st_sample(x, kappa = 1, mu = 10, scale = 0.1, type = "Thomas") }bbox = st_bbox(c(xmin = 0, xmax = 40, ymax = 70, ymin = 60),crs = st_crs('OGC:CRS84'))set.seed(13531)s1 = st_sample(bbox, 400)st_bbox(s1) # within bboxs2 = st_sample(bbox, 400, great_circles = TRUE)st_bbox(s2) # outside bbox

Shift or re-center geographical coordinates for a Pacific view

Description

All longitudes < 0 are added to 360, to avoid for instance parts of Alaskabeing represented on the far left and right of a plot because they havevalues straddling 180 degrees. In general, using a projectedcoordinate reference system is to be preferred, but this method permits ageographical coordinate reference system to be used. This is the sfequivalent ofrecenter in the sp package andST_ShiftLongitude in PostGIS.

Usage

st_shift_longitude(x)## S3 method for class 'sfc'st_shift_longitude(x, ...)## S3 method for class 'sf'st_shift_longitude(x, ...)

Arguments

Examples

## sfcpt1 = st_point(c(-170, 50))pt2 = st_point(c(170, 50))(sfc = st_sfc(pt1, pt2))sfc = st_set_crs(sfc, 4326)st_shift_longitude(sfc)## sfd = st_as_sf(data.frame(id = 1:2, geometry = sfc))st_shift_longitude(d)

Transform or convert coordinates of simple feature

Description

Transform or convert coordinates of simple feature

Usage

st_can_transform(src, dst)st_transform(x, crs, ...)## S3 method for class 'sfc'st_transform(  x,  crs = st_crs(x),  ...,  aoi = numeric(0),  pipeline = character(0),  reverse = FALSE,  desired_accuracy = -1,  allow_ballpark = TRUE,  partial = TRUE,  check = FALSE)## S3 method for class 'sf'st_transform(x, crs = st_crs(x), ...)## S3 method for class 'sfg'st_transform(x, crs = st_crs(x), ...)## S3 method for class 'bbox'st_transform(x, crs, ..., densify = 21)st_wrap_dateline(x, options, quiet)## S3 method for class 'sfc'st_wrap_dateline(x, options = "WRAPDATELINE=YES", quiet = TRUE)## S3 method for class 'sf'st_wrap_dateline(x, options = "WRAPDATELINE=YES", quiet = TRUE)## S3 method for class 'sfg'st_wrap_dateline(x, options = "WRAPDATELINE=YES", quiet = TRUE)sf_proj_info(type = "proj", path)

Arguments

Details

st_can_transform returns a boolean indicating whethercoordinates with CRS src can be transformed into CRS dst

Transforms coordinates of object to new projection.Features that cannot be transformed are returned as empty geometries.Transforms using thepipeline= argument may fail if there isambiguity in the axis order of the specified coordinate reference system;if you need the traditional GIS order, use"OGC:CRS84", not"EPSG:4326". Extra care is needed with the ESRI Shapefile format,because WKT1 does not store axis order unambiguously.

Thest_transform method forsfg objects assumes that the CRS of the object is available as an attribute of that name.

the method forbbox objects densifies lines for geographic coordinates along Cartesian lines, not great circle arcs

For a discussion of usingoptions, seehttps://github.com/r-spatial/sf/issues/280 andhttps://github.com/r-spatial/sf/issues/1983

sf_proj_info lists the available projections, ellipses, datums, units, or data search path of the PROJ library whentype is equal to proj, ellps, datum, units or path; whentype equalshave_datum_files a boolean is returned indicating whether datum files are installed and accessible (checking forconus).path returns thePROJ_INFO.searchpath field directly, as a single string with path separaters (: or⁠;⁠).

for PROJ >= 6,sf_proj_info does not provide optiontype = "datums".PROJ < 6 does not provide the optiontype = "prime_meridians".

for PROJ >= 7.1.0, the "units" query ofsf_proj_info returns theto_metervariable as numeric, previous versions return a character vector containing a numeric expression.

See Also

st_transform_proj, part of package lwgeom.

sf_project projects a matrix of coordinates, bypassing GDAL altogether

st_break_antimeridian

Examples

p1 = st_point(c(7,52))p2 = st_point(c(-30,20))sfc = st_sfc(p1, p2, crs = 4326)sfcst_transform(sfc, 3857)st_transform(st_sf(a=2:1, geom=sfc), "EPSG:3857")if (compareVersion(sf_extSoftVersion()["GDAL"], "3.0.0") >= 0) {  st_transform(sfc, pipeline =  "+proj=pipeline +step +proj=axisswap +order=2,1") # reverse axes  st_transform(sfc, pipeline =  "+proj=pipeline +step +proj=axisswap +order=2,1", reverse = TRUE) # also reverse axes}nc = st_read(system.file("shape/nc.shp", package="sf"))st_area(nc[1,]) # area from long/latst_area(st_transform(nc[1,], 32119)) # NC state plane, mst_area(st_transform(nc[1,], 2264)) # NC state plane, US footlibrary(units)set_units(st_area(st_transform(nc[1,], 2264)), m^2)st_transform(structure(p1, proj4string = "EPSG:4326"), "EPSG:3857")st_wrap_dateline(st_sfc(st_linestring(rbind(c(-179,0),c(179,0))), crs = 4326))sf_proj_info("datum")

Create viewport from sf, sfc or sfg object

Description

Create viewport from sf, sfc or sfg object

Usage

st_viewport(x, ..., bbox = st_bbox(x), asp)

Arguments

Details

parameterswidth,height,xscale andyscale are set such that aspect ratio is honoured and plot size is maximized in the current viewport; others can be passed as...

Ifasp is missing, it is taken as 1, except whenisTRUE(st_is_longlat(x)), in which case it is set to1.0 /cos(y), withy the middle of the latitude bounding box.

Value

The output of the call toviewport

Examples

library(grid)nc = st_read(system.file("shape/nc.shp", package="sf"))grid.newpage()pushViewport(viewport(width = 0.8, height = 0.8))pushViewport(st_viewport(nc))invisible(lapply(st_geometry(nc), function(x) grid.draw(st_as_grob(x, gp = gpar(fill = 'red')))))

Write simple features object to file or database

Description

Write simple features object to file or database

Usage

st_write(obj, dsn, layer, ...)## S3 method for class 'sfc'st_write(obj, dsn, layer, ...)## S3 method for class 'sf'st_write(  obj,  dsn,  layer = NULL,  ...,  driver = guess_driver_can_write(dsn),  dataset_options = NULL,  layer_options = NULL,  quiet = FALSE,  factorsAsCharacter = TRUE,  append = NA,  delete_dsn = FALSE,  delete_layer = !is.na(append) && !append,  fid_column_name = NULL,  config_options = character(0))## S3 method for class 'data.frame'st_write(obj, dsn, layer = NULL, ...)write_sf(..., quiet = TRUE, append = FALSE, delete_layer = !append)st_delete(  dsn,  layer = character(0),  driver = guess_driver_can_write(dsn),  quiet = FALSE)

Arguments

Details

Columns (variables) of a class not supported are dropped with a warning.

When updating an existing layer, records are appended to it if the updatingobject has the right variable names and types. If names don't match anerror is raised. If types don't match, behaviour is undefined: GDAL mayraise warnings or errors or fail silently.

When deleting layers or data sources is not successful, no error is emitted.delete_dsn anddelete_layer should behandled with care; the former may erase complete directories or databases.

st_delete() deletes layer(s) in a data source, or a data source if layers areomitted; it returnsTRUE on success,FALSE on failure, invisibly.

Value

obj, invisibly

See Also

st_drivers,dbWriteTable

Examples

nc = st_read(system.file("shape/nc.shp", package="sf"))st_write(nc, paste0(tempdir(), "/", "nc.shp"))st_write(nc, paste0(tempdir(), "/", "nc.shp"), delete_layer = TRUE) # overwritesif (require(sp, quietly = TRUE)) { data(meuse, package = "sp") # loads data.frame from sp meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992) # writes X and Y as columns: st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_XY") st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_WKT",   delete_dsn=TRUE) # overwrites## Not run:  library(sp) example(meuse, ask = FALSE, echo = FALSE) try(st_write(st_as_sf(meuse), "PG:dbname=postgis", "meuse_sf",     layer_options = c("OVERWRITE=yes", "LAUNDER=true"))) demo(nc, ask = FALSE) try(st_write(nc, "PG:dbname=postgis", "sids", layer_options = "OVERWRITE=true"))## End(Not run)}

Return 'z' range of a simple feature or simple feature set

Description

Return 'z' range of a simple feature or simple feature set

Usage

## S3 method for class 'z_range'is.na(x)st_z_range(obj, ...)## S3 method for class 'POINT'st_z_range(obj, ...)## S3 method for class 'MULTIPOINT'st_z_range(obj, ...)## S3 method for class 'LINESTRING'st_z_range(obj, ...)## S3 method for class 'POLYGON'st_z_range(obj, ...)## S3 method for class 'MULTILINESTRING'st_z_range(obj, ...)## S3 method for class 'MULTIPOLYGON'st_z_range(obj, ...)## S3 method for class 'GEOMETRYCOLLECTION'st_z_range(obj, ...)## S3 method for class 'MULTISURFACE'st_z_range(obj, ...)## S3 method for class 'MULTICURVE'st_z_range(obj, ...)## S3 method for class 'CURVEPOLYGON'st_z_range(obj, ...)## S3 method for class 'COMPOUNDCURVE'st_z_range(obj, ...)## S3 method for class 'POLYHEDRALSURFACE'st_z_range(obj, ...)## S3 method for class 'TIN'st_z_range(obj, ...)## S3 method for class 'TRIANGLE'st_z_range(obj, ...)## S3 method for class 'CIRCULARSTRING'st_z_range(obj, ...)## S3 method for class 'sfc'st_z_range(obj, ...)## S3 method for class 'sf'st_z_range(obj, ...)## S3 method for class 'numeric'st_z_range(obj, ..., crs = NA_crs_)NA_z_range_

Arguments

Format

An object of classz_range of length 2.

Details

NA_z_range_ represents the missing value for az_range object

Value

a numeric vector of length two, withzmin andzmax values;ifobj is of classsf orsfc the objectreturned has a classz_range

Examples

a = st_sf(a = 1:2, geom = st_sfc(st_point(0:2), st_point(1:3)), crs = 4326)st_z_range(a)st_z_range(c(zmin = 16.1, zmax = 16.6), crs = st_crs(4326))

Drop or add Z and/or M dimensions from feature geometries

Description

Drop Z and/or M dimensions from feature geometries, resetting classes appropriately

Usage

st_zm(x, ..., drop = TRUE, what = "ZM")

Arguments

Details

Only combinationsdrop=TRUE,what = "ZM", anddrop=FALSE,what="Z" are supported so far.In the latter case,x should haveXY geometry, and zero values are added for theZ dimension.

Examples

st_zm(st_linestring(matrix(1:32,8)))x = st_sfc(st_linestring(matrix(1:32,8)), st_linestring(matrix(1:8,2)))st_zm(x)a = st_sf(a = 1:2, geom=x)st_zm(a)

functions only exported to be used internally by stars

Description

functions only exported to be used internally by stars

Usage

.get_layout(bb, n, total_size, key.pos, key.width, mfrow = NULL, main = NULL).degAxis(side, at, labels, ..., lon, lat, ndiscr, reset).image_scale(  z,  col,  breaks = NULL,  key.pos,  add.axis = TRUE,  at = NULL,  ...,  axes = FALSE,  key.length,  logz = FALSE,  lab = "",  cex.axis = par("cex.axis")).image_scale_factor(  z,  col,  key.pos,  add.axis = TRUE,  ...,  axes = FALSE,  key.width,  key.length,  cex.axis = par("cex.axis"))

Arguments

Summarize simple feature column

Description

Summarize simple feature column

Usage

## S3 method for class 'sfc'summary(object, ..., maxsum = 7L, maxp4s = 10L)

Arguments

Summarize simple feature type for tibble

Description

Summarize simple feature type / item for tibble

Usage

type_sum.sfc(x, ...)obj_sum.sfc(x)pillar_shaft.sfc(x, ...)

Arguments

Details

seetype_sum

Tidyverse methods for sf objects

Description

Tidyverse methods for sf objects. Geometries are sticky, useas.data.frame to letdplyr's own methods drop them.Use these methods after loading the tidyverse package with the generic (or after loading package tidyverse).

Usage

filter.sf(.data, ..., .dots)arrange.sf(.data, ..., .dots)group_by.sf(.data, ..., add = FALSE)ungroup.sf(x, ...)rowwise.sf(x, ...)mutate.sf(.data, ..., .dots)transmute.sf(.data, ..., .dots)select.sf(.data, ...)rename.sf(.data, ...)rename_with.sf(.data, .fn, .cols, ...)slice.sf(.data, ..., .dots)summarise.sf(.data, ..., .dots, do_union = TRUE, is_coverage = FALSE)distinct.sf(.data, ..., .keep_all = FALSE, exact = FALSE, par = 0)gather.sf(  data,  key,  value,  ...,  na.rm = FALSE,  convert = FALSE,  factor_key = FALSE)pivot_longer.sf(  data,  cols,  names_to = "name",  names_prefix = NULL,  names_sep = NULL,  names_pattern = NULL,  names_ptypes = NULL,  names_transform = NULL,  names_repair = "check_unique",  values_to = "value",  values_drop_na = FALSE,  values_ptypes = NULL,  values_transform = NULL,  ...)pivot_wider.sf(  data,  ...,  id_cols = NULL,  id_expand = FALSE,  names_from = name,  names_prefix = "",  names_sep = "_",  names_glue = NULL,  names_sort = FALSE,  names_vary = "fastest",  names_expand = FALSE,  names_repair = "check_unique",  values_from = value,  values_fill = NULL,  values_fn = NULL,  unused_fn = NULL)spread.sf(  data,  key,  value,  fill = NA,  convert = FALSE,  drop = TRUE,  sep = NULL)sample_n.sf(tbl, size, replace = FALSE, weight = NULL, .env = parent.frame())sample_frac.sf(  tbl,  size = 1,  replace = FALSE,  weight = NULL,  .env = parent.frame())group_split.sf(.tbl, ..., .keep = TRUE)nest.sf(.data, ...)separate.sf(  data,  col,  into,  sep = "[^[:alnum:]]+",  remove = TRUE,  convert = FALSE,  extra = "warn",  fill = "warn",  ...)separate_rows.sf(data, ..., sep = "[^[:alnum:]]+", convert = FALSE)unite.sf(data, col, ..., sep = "_", remove = TRUE)unnest.sf(data, ..., .preserve = NULL)drop_na.sf(x, ...)inner_join.sf(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)left_join.sf(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)right_join.sf(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)full_join.sf(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)semi_join.sf(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)anti_join.sf(x, y, by = NULL, copy = FALSE, suffix = c(".x", ".y"), ...)

Arguments

Details

select keeps the geometry regardless whether it is selected or not; to deselect it, first pipe throughas.data.frame to let dplyr's ownselect drop it.

In case one or more of the arguments (expressions) in thesummarise call creates a geometry list-column, the first of these will be the (active) geometry of the returned object. If this is not the case, a geometry column is created, depending on the value ofdo_union.

In casedo_union isFALSE,summarise will simply combine geometries usingc.sfg. When polygons sharing a boundary are combined, this leads to geometries that are invalid; see for instancehttps://github.com/r-spatial/sf/issues/681.

distinct gives distinct records for which all attributes and geometries are distinct;st_equals is used to find out which geometries are distinct.

nest assumes that a simple feature geometry list-column was among the columns that were nested.

Value

an object of classsf

Examples

if (require(dplyr, quietly = TRUE)) { nc = read_sf(system.file("shape/nc.shp", package="sf")) nc %>% filter(AREA > .1) %>% plot() # plot 10 smallest counties in grey: st_geometry(nc) %>% plot() nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey') title("the ten counties with smallest area") nc2 <- nc %>% mutate(area10 = AREA/10) nc %>% slice(1:2)}# plot 10 smallest counties in grey:if (require(dplyr, quietly = TRUE)) { st_geometry(nc) %>% plot() nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey') title("the ten counties with smallest area")}if (require(dplyr, quietly = TRUE)) { nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25)) nc %>% group_by(area_cl) %>% class()}if (require(dplyr, quietly = TRUE)) { nc2 <- nc %>% mutate(area10 = AREA/10)}if (require(dplyr, quietly = TRUE)) { nc %>% transmute(AREA = AREA/10) %>% class()}if (require(dplyr, quietly = TRUE)) { nc %>% select(SID74, SID79) %>% names() nc %>% select(SID74, SID79) %>% class()}if (require(dplyr, quietly = TRUE)) { nc2 <- nc %>% rename(area = AREA)}if (require(dplyr, quietly = TRUE)) { nc %>% slice(1:2)}if (require(dplyr, quietly = TRUE)) { nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25)) nc.g <- nc %>% group_by(area_cl) nc.g %>% summarise(mean(AREA)) nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7)) nc %>% as.data.frame %>% summarise(mean(AREA))}if (require(dplyr, quietly = TRUE)) { nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()}if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE) && "geometry" %in% names(nc)) { nc %>% select(SID74, SID79) %>% gather("VAR", "SID", -geometry) %>% summary()}if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE) && "geometry" %in% names(nc)) { nc$row = 1:100 # needed for spread to work nc %>% select(SID74, SID79, geometry, row) %>%gather("VAR", "SID", -geometry, -row) %>%spread(VAR, SID) %>% head()}if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE)) { storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326) x <- storms.sf %>% group_by(name, year) %>% nest trs = lapply(x$data, function(tr) st_cast(st_combine(tr), "LINESTRING")[[1]]) %>%    st_sfc(crs = 4326) trs.sf = st_sf(x[,1:2], trs) plot(trs.sf["year"], axes = TRUE)}

transform method for sf objects

Description

Can be used to create or modify attribute variables; for transforming geometries seest_transform, and all other functions starting withst_.

Usage

## S3 method for class 'sf'transform(`_data`, ...)

Arguments

Examples

a = data.frame(x1 = 1:3, x2 = 5:7)st_geometry(a) = st_sfc(st_point(c(0,0)), st_point(c(1,1)), st_point(c(2,2)))transform(a, x1_sq = x1^2)transform(a, x1_x2 = x1*x2)

Check validity or make an invalid geometry valid

Description

Checks whether a geometry is valid, or makes an invalid geometry valid

Usage

st_is_valid(x, ...)## S3 method for class 'sfc'st_is_valid(x, ..., NA_on_exception = TRUE, reason = FALSE)## S3 method for class 'sf'st_is_valid(x, ...)## S3 method for class 'sfg'st_is_valid(x, ...)st_make_valid(x, ...)## S3 method for class 'sfg'st_make_valid(x, ...)## S3 method for class 'sfc'st_make_valid(  x,  ...,  oriented = FALSE,  s2_options = s2::s2_options(snap = s2::s2_snap_precision(1e+07), ...),  geos_method = "valid_structure",  geos_keep_collapsed = TRUE)

Arguments

Details

For projected geometries,st_make_valid uses thelwgeom_makevalid method also used by the PostGIS commandST_makevalid if the GEOS version linked to is smaller than 3.8.0, and otherwise the version shipped in GEOS; for geometries having ellipsoidal coordinatess2::s2_rebuild is being used.

ifs2_options is not specified andx has a non-zero precision set, then this precision value will be used as the value ins2_snap_precision, passed on tos2_options, rather than the 1e7 default.

Value

st_is_valid returns a logical vector indicating for each geometries ofx whether it is valid.st_make_valid returns an object with a topologically valid geometry.

Object of the same class asx

Examples

p1 = st_as_sfc("POLYGON((0 0, 0 10, 10 0, 10 10, 0 0))")st_is_valid(p1)st_is_valid(st_sfc(st_point(0:1), p1[[1]]), reason = TRUE)library(sf)x = st_sfc(st_polygon(list(rbind(c(0,0),c(0.5,0),c(0.5,0.5),c(0.5,0),c(1,0),c(1,1),c(0,1),c(0,0)))))suppressWarnings(st_is_valid(x))y = st_make_valid(x)st_is_valid(y)y %>% st_cast()

vctrs methods for sf objects

Description

vctrs methods for sf objects

Usage

vec_ptype2.sfc(x, y, ...)## Default S3 method:vec_ptype2.sfc(x, y, ..., x_arg = "x", y_arg = "y")## S3 method for class 'sfc'vec_ptype2.sfc(x, y, ...)vec_cast.sfc(x, to, ...)## S3 method for class 'sfc'vec_cast.sfc(x, to, ...)## Default S3 method:vec_cast.sfc(x, to, ...)

Arguments