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] TRUEThe sf package uses s2 for geographic coordinates with sf::sf_use_s2(TRUE), and will become the default after sf version 1.0.0. The sf package also supports creating s2 vectors using as_s2_geography():
library(dplyr)
library(sf)
nc_s2 <- read_sf(system.file("shape/nc.shp", package = "sf")) %>%
mutate(geometry = as_s2_geography(geometry)) %>%
as_tibble() %>%
select(NAME, geometry)
nc_s2
#> # A tibble: 100 x 2
#> NAME geometry
#> <chr> <s2_geography>
#> 1 Ashe <POLYGON ((-81.4528885 36.2395859, -81.4310379 36.2607193, -81.4…
#> 2 Alleghany <POLYGON ((-81.1766739 36.4154434, -81.1533661 36.4247398, -81.1…
#> 3 Surry <POLYGON ((-80.4530106 36.2570877, -80.4353104 36.5510445, -80.6…
#> 4 Currituck <MULTIPOLYGON (((-75.9419327 36.2943382, -75.9575119 36.2594528,…
#> 5 Northampton <POLYGON ((-77.1419601 36.4170647, -77.1393204 36.4564781, -77.1…
#> 6 Hertford <POLYGON ((-76.7074966 36.2661324, -76.7413483 36.3151665, -76.9…
#> 7 Camden <POLYGON ((-76.0173492 36.3377304, -76.0328751 36.3359756, -76.0…
#> 8 Gates <POLYGON ((-76.46035 36.3738976, -76.5024643 36.4522858, -76.498…
#> 9 Warren <POLYGON ((-78.1347198 36.2365837, -78.1096268 36.2135086, -78.0…
#> 10 Stokes <POLYGON ((-80.0240555 36.5450249, -80.0480957 36.5471344, -80.4…
#> # … with 90 more rowsUse 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 ((-81.4528885 36.2395859, -81.4310379 … 1.14e9 141627.
#> 2 Alleghany <POLYGON ((-81.1766739 36.4154434, -81.1533661 … 6.11e8 119876.
#> 3 Surry <POLYGON ((-80.4530106 36.2570877, -80.4353104 … 1.42e9 160458.
#> 4 Currituck <MULTIPOLYGON (((-75.9419327 36.2943382, -75.95… 6.94e8 301644.
#> 5 Northamp… <POLYGON ((-77.1419601 36.4170647, -77.1393204 … 1.52e9 211794.
#> 6 Hertford <POLYGON ((-76.7074966 36.2661324, -76.7413483 … 9.68e8 160780.
#> 7 Camden <POLYGON ((-76.0173492 36.3377304, -76.0328751 … 6.16e8 150430.
#> 8 Gates <POLYGON ((-76.46035 36.3738976, -76.5024643 36… 9.03e8 123170.
#> 9 Warren <POLYGON ((-78.1347198 36.2365837, -78.1096268 … 1.18e9 141073.
#> 10 Stokes <POLYGON ((-80.0240555 36.5450249, -80.0480957 … 1.23e9 140583.
#> # … with 90 more rowsUse 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 ((-80.9312744 35.6195908, -81.0035782 35.6970558, -81.054779…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 (-81.4528885 36.2395859, -81.4310379 36.2607193, -81…
#> 2 Alleghany <LINESTRING (-81.1766739 36.4154434, -81.1533661 36.4247398, -81…
#> 3 Surry <LINESTRING (-80.4530106 36.2570877, -80.4353104 36.5510445, -80…
#> 4 Currituck <MULTILINESTRING ((-75.9419327 36.2943382, -75.9575119 36.259452…
#> 5 Northampton <LINESTRING (-77.1419601 36.4170647, -77.1393204 36.4564781, -77…
#> 6 Hertford <LINESTRING (-76.7074966 36.2661324, -76.7413483 36.3151665, -76…
#> 7 Camden <LINESTRING (-76.0173492 36.3377304, -76.0328751 36.3359756, -76…
#> 8 Gates <LINESTRING (-76.46035 36.3738976, -76.5024643 36.4522858, -76.4…
#> 9 Warren <LINESTRING (-78.1347198 36.2365837, -78.1096268 36.2135086, -78…
#> 10 Stokes <LINESTRING (-80.0240555 36.5450249, -80.0480957 36.5471344, -80…
#> # … with 90 more rowsFinally, 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
