The goal of s2 is to provide R bindings to Google’s S2Geometry library. The package exposes an API similar to Google’s BigQuery Geography API, whose functions also operate on spherical geometries. This package is a complete rewrite of an earlier CRAN package s2 with versions up to 0.4-2, for which the sources are found here.
Installation
You can install the released version of s2 from CRAN with:
install.packages("s2")
And the development version from GitHub with:
# install.packages("remotes") remotes::install_github("r-spatial/s2")
Example
The s2 package provides geometry transformers and predicates similar to those found in GEOS, except instead of assuming a planar geometry, s2’s functions work in latitude and longitude and assume a spherical geometry:
library(s2) s2_contains( # polygon containing much of the northern hemisphere "POLYGON ((-63.5 44.6, -149.75 61.20, 116.4 40.2, 13.5 52.51, -63.5 44.6))", # ...should contain the north pole "POINT (0 90)" ) #> [1] TRUE
The sf package will soon support s2 natively, but s2 can also read well-known text and well-known binary:
library(dplyr) library(sf) nc_s2 <- read_sf(system.file("shape/nc.shp", package = "sf")) %>% mutate(geometry = s2_geog_from_wkb(st_as_binary(geometry))) %>% as_tibble() %>% select(NAME, geometry) nc_s2 #> # A tibble: 100 x 2 #> NAME geometry #> <chr> <s2_geography> #> 1 Ashe <POLYGON ((-81.4529 36.2396, -81.431 36.2607, -81.4123 36.2673, … #> 2 Alleghany <POLYGON ((-81.1767 36.4154, -81.1534 36.4247, -81.1384 36.4176,… #> 3 Surry <POLYGON ((-80.453 36.2571, -80.4353 36.551, -80.6111 36.5573, -… #> 4 Currituck <MULTIPOLYGON (((-75.9419 36.2943, -75.9575 36.2595, -75.9138 36… #> 5 Northampton <POLYGON ((-77.142 36.4171, -77.1393 36.4565, -77.1273 36.4707, … #> 6 Hertford <POLYGON ((-76.7075 36.2661, -76.7413 36.3152, -76.9241 36.3924,… #> 7 Camden <POLYGON ((-76.0173 36.3377, -76.0329 36.336, -76.044 36.3536, -… #> 8 Gates <POLYGON ((-76.4604 36.3739, -76.5025 36.4523, -76.4983 36.5039,… #> 9 Warren <POLYGON ((-78.1347 36.2366, -78.1096 36.2135, -78.0583 36.2113,… #> 10 Stokes <POLYGON ((-80.0241 36.545, -80.0481 36.5471, -80.4353 36.551, -… #> # … with 90 more rows
Use accessors to extract information about geometries:
nc_s2 %>% mutate( area = s2_area(geometry), perimeter = s2_perimeter(geometry) ) #> # A tibble: 100 x 4 #> NAME geometry area perimeter #> <chr> <s2_geography> <dbl> <dbl> #> 1 Ashe <POLYGON ((-81.4529 36.2396, -81.431 36.2607, -… 1.14e9 141627. #> 2 Alleghany <POLYGON ((-81.1767 36.4154, -81.1534 36.4247, … 6.11e8 119876. #> 3 Surry <POLYGON ((-80.453 36.2571, -80.4353 36.551, -8… 1.42e9 160458. #> 4 Currituck <MULTIPOLYGON (((-75.9419 36.2943, -75.9575 36.… 6.94e8 301644. #> 5 Northamp… <POLYGON ((-77.142 36.4171, -77.1393 36.4565, -… 1.52e9 211794. #> 6 Hertford <POLYGON ((-76.7075 36.2661, -76.7413 36.3152, … 9.68e8 160780. #> 7 Camden <POLYGON ((-76.0173 36.3377, -76.0329 36.336, -… 6.16e8 150430. #> 8 Gates <POLYGON ((-76.4604 36.3739, -76.5025 36.4523, … 9.03e8 123170. #> 9 Warren <POLYGON ((-78.1347 36.2366, -78.1096 36.2135, … 1.18e9 141073. #> 10 Stokes <POLYGON ((-80.0241 36.545, -80.0481 36.5471, -… 1.23e9 140583. #> # … with 90 more rows
Use predicates to subset vectors:
nc_s2 %>% filter(s2_contains(geometry, "POINT (-80.9313 35.6196)")) #> # A tibble: 1 x 2 #> NAME geometry #> <chr> <s2_geography> #> 1 Catawba <POLYGON ((-80.9313 35.6196, -81.0036 35.6971, -81.0548 35.7134, -81.…
Use transformers to create new geometries:
nc_s2 %>% mutate(geometry = s2_boundary(geometry)) #> # A tibble: 100 x 2 #> NAME geometry #> <chr> <s2_geography> #> 1 Ashe <LINESTRING (-81.4529 36.2396, -81.431 36.2607, -81.4123 36.2673… #> 2 Alleghany <LINESTRING (-81.1767 36.4154, -81.1534 36.4247, -81.1384 36.417… #> 3 Surry <LINESTRING (-80.453 36.2571, -80.4353 36.551, -80.6111 36.5573,… #> 4 Currituck <MULTILINESTRING ((-75.9419 36.2943, -75.9575 36.2595, -75.9138 … #> 5 Northampton <LINESTRING (-77.142 36.4171, -77.1393 36.4565, -77.1273 36.4707… #> 6 Hertford <LINESTRING (-76.7075 36.2661, -76.7413 36.3152, -76.9241 36.392… #> 7 Camden <LINESTRING (-76.0173 36.3377, -76.0329 36.336, -76.044 36.3536,… #> 8 Gates <LINESTRING (-76.4604 36.3739, -76.5025 36.4523, -76.4983 36.503… #> 9 Warren <LINESTRING (-78.1347 36.2366, -78.1096 36.2135, -78.0583 36.211… #> 10 Stokes <LINESTRING (-80.0241 36.545, -80.0481 36.5471, -80.4353 36.551,… #> # … with 90 more rows
Finally, use the WKB or WKT exporters to export to sf or some other package:
nc_s2 %>% mutate(geometry = st_as_sfc(s2_as_binary(geometry))) %>% st_as_sf() #> Simple feature collection with 100 features and 1 field #> geometry type: GEOMETRY #> dimension: XY #> bbox: xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965 #> CRS: NA #> # A tibble: 100 x 2 #> NAME geometry #> <chr> <GEOMETRY> #> 1 Ashe POLYGON ((-81.45289 36.23959, -81.43104 36.26072, -81.41233 36.26… #> 2 Alleghany POLYGON ((-81.17667 36.41544, -81.15337 36.42474, -81.1384 36.417… #> 3 Surry POLYGON ((-80.45301 36.25709, -80.43531 36.55104, -80.61105 36.55… #> 4 Currituck MULTIPOLYGON (((-75.94193 36.29434, -75.95751 36.25945, -75.91376… #> 5 Northampt… POLYGON ((-77.14196 36.41706, -77.13932 36.45648, -77.12733 36.47… #> 6 Hertford POLYGON ((-76.7075 36.26613, -76.74135 36.31517, -76.92408 36.392… #> 7 Camden POLYGON ((-76.01735 36.33773, -76.03288 36.33598, -76.04395 36.35… #> 8 Gates POLYGON ((-76.46035 36.3739, -76.50246 36.45229, -76.49834 36.503… #> 9 Warren POLYGON ((-78.13472 36.23658, -78.10963 36.21351, -78.05835 36.21… #> 10 Stokes POLYGON ((-80.02406 36.54502, -80.0481 36.54713, -80.43531 36.551… #> # … with 90 more rows
