Convert foreign object to an sf object

Source: R/sf.R, R/sp.R, R/maps.R, and 1 more

Convert foreign object to an sf object

st_as_sf(x, ...)

# S3 method for 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 sf
st_as_sf(x, ...)

# S3 method for sfc
st_as_sf(x, ...)

# S3 method for Spatial
st_as_sf(x, ...)

# S3 method for map
st_as_sf(x, ..., fill = TRUE, group = TRUE)

# S3 method for ppp
st_as_sf(x, ...)

# S3 method for psp
st_as_sf(x, ...)

# S3 method for lpp
st_as_sf(x, ...)

Arguments

x

object to be converted into an object class sf
...

passed on to st_sf, might included named arguments crs or precision
agr

character vector; see details section of st_sf
coords

in case of point data: names or numbers of the numeric columns holding coordinates
wkt

name or number of the character column that holds WKT encoded geometries
dim

passed on to st_point (only when argument coords is given)
remove

logical; when coords or wkt is given, remove these columns from data.frame?
na.fail

logical; if TRUE, raise an error if coordinates contain missing values
sf_column_name

character; name of the active list-column with simple feature geometries; in case there is more than one and sf_column_name is NULL, the first one is taken.
fill

logical; the value for fill that was used in the call to map.
group

logical; if TRUE, group id labels from map by their prefix before :

Details

setting argument wkt annihilates the use of argument coords. If x contains a column called "geometry", coords will result in overwriting of this column by the sfc geometry list-column. Setting wkt will replace this column with the geometry list-column, unless remove_coordinates is FALSE.

Examples

pt1 = st_point(c(0,1))
pt2 = st_point(c(1,1))
st_sfc(pt1, pt2)
#> Geometry set for 2 features 
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 0 ymin: 1 xmax: 1 ymax: 1
#> CRS:            NA
#> POINT (0 1)
#> POINT (1 1)
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 warn
#> Simple feature collection with 2 features and 2 fields
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 0 ymin: 1 xmax: 1 ymax: 1
#> CRS:            NA
#>   a       geom       geom2
#> 1 1 POINT(0 0) POINT (0 1)
#> 2 2 POINT(0 1) POINT (1 1)
data(meuse, package = "sp")
meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
meuse_sf[1:3,]
#> Simple feature collection with 3 features and 12 fields
#> Attribute-geometry relationship: 12 constant, 0 aggregate, 0 identity
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 181025 ymin: 333537 xmax: 181165 ymax: 333611
#> CRS:            EPSG:28992
#>   cadmium copper lead zinc  elev       dist   om ffreq soil lime landuse dist.m
#> 1    11.7     85  299 1022 7.909 0.00135803 13.6     1    1    1      Ah     50
#> 2     8.6     81  277 1141 6.983 0.01222430 14.0     1    1    1      Ah     30
#> 3     6.5     68  199  640 7.800 0.10302900 13.0     1    1    1      Ah    150
#>                geometry
#> 1 POINT (181072 333611)
#> 2 POINT (181025 333558)
#> 3 POINT (181165 333537)
summary(meuse_sf)
#>     cadmium           copper            lead            zinc       
#>  Min.   : 0.200   Min.   : 14.00   Min.   : 37.0   Min.   : 113.0  
#>  1st Qu.: 0.800   1st Qu.: 23.00   1st Qu.: 72.5   1st Qu.: 198.0  
#>  Median : 2.100   Median : 31.00   Median :123.0   Median : 326.0  
#>  Mean   : 3.246   Mean   : 40.32   Mean   :153.4   Mean   : 469.7  
#>  3rd Qu.: 3.850   3rd Qu.: 49.50   3rd Qu.:207.0   3rd Qu.: 674.5  
#>  Max.   :18.100   Max.   :128.00   Max.   :654.0   Max.   :1839.0  
#>                                                                    
#>       elev             dist               om         ffreq  soil   lime   
#>  Min.   : 5.180   Min.   :0.00000   Min.   : 1.000   1:84   1:97   0:111  
#>  1st Qu.: 7.546   1st Qu.:0.07569   1st Qu.: 5.300   2:48   2:46   1: 44  
#>  Median : 8.180   Median :0.21184   Median : 6.900   3:23   3:12          
#>  Mean   : 8.165   Mean   :0.24002   Mean   : 7.478                        
#>  3rd Qu.: 8.955   3rd Qu.:0.36407   3rd Qu.: 9.000                        
#>  Max.   :10.520   Max.   :0.88039   Max.   :17.000                        
#>                                     NA's   :2                             
#>     landuse       dist.m                geometry  
#>  W      :50   Min.   :  10.0   POINT        :155  
#>  Ah     :39   1st Qu.:  80.0   epsg:28992   :  0  
#>  Am     :22   Median : 270.0   +proj=ster...:  0  
#>  Fw     :10   Mean   : 290.3                      
#>  Ab     : 8   3rd Qu.: 450.0                      
#>  (Other):25   Max.   :1000.0                      
#>  NA's   : 1                                       
library(sp)
x = rbind(c(-1,-1), c(1,-1), c(1,1), c(-1,1), c(-1,-1))
x1 = 0.1 * x + 0.1
x2 = 0.1 * x + 0.4
x3 = 0.1 * x + 0.7
y = x + 3
y1 = x1 + 3
y3 = x3 + 3
m = matrix(c(3, 0), 5, 2, byrow = TRUE)
z = x + m
z1 = x1 + m
z2 = x2 + m
z3 = x3 + m
p1 = 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")
if (require("rgeos")) {
  r = createSPComment(SpatialPolygons(list(p1,p2)))
  comment(r)
  comment(r@polygons[[1]])
  scan(text = comment(r@polygons[[1]]), quiet = TRUE)
  library(sf)
  a = st_as_sf(r)
  summary(a)
}
#> Loading required package: rgeos
#> rgeos version: 0.5-2, (SVN revision 621)
#>  GEOS runtime version: 3.5.0-CAPI-1.9.0 
#>  Linking to sp version: 1.3-2 
#>  Polygon checking: TRUE 
#>          geometry
#>  MULTIPOLYGON:2  
#>  epsg:NA     :0  
demo(meuse, ask = FALSE, echo = FALSE)
summary(st_as_sf(meuse))
#>     cadmium           copper            lead            zinc       
#>  Min.   : 0.200   Min.   : 14.00   Min.   : 37.0   Min.   : 113.0  
#>  1st Qu.: 0.800   1st Qu.: 23.00   1st Qu.: 72.5   1st Qu.: 198.0  
#>  Median : 2.100   Median : 31.00   Median :123.0   Median : 326.0  
#>  Mean   : 3.246   Mean   : 40.32   Mean   :153.4   Mean   : 469.7  
#>  3rd Qu.: 3.850   3rd Qu.: 49.50   3rd Qu.:207.0   3rd Qu.: 674.5  
#>  Max.   :18.100   Max.   :128.00   Max.   :654.0   Max.   :1839.0  
#>                                                                    
#>       elev             dist               om         ffreq  soil   lime   
#>  Min.   : 5.180   Min.   :0.00000   Min.   : 1.000   1:84   1:97   0:111  
#>  1st Qu.: 7.546   1st Qu.:0.07569   1st Qu.: 5.300   2:48   2:46   1: 44  
#>  Median : 8.180   Median :0.21184   Median : 6.900   3:23   3:12          
#>  Mean   : 8.165   Mean   :0.24002   Mean   : 7.478                        
#>  3rd Qu.: 8.955   3rd Qu.:0.36407   3rd Qu.: 9.000                        
#>  Max.   :10.520   Max.   :0.88039   Max.   :17.000                        
#>                                     NA's   :2                             
#>     landuse       dist.m                geometry  
#>  W      :50   Min.   :  10.0   POINT        :155  
#>  Ah     :39   1st Qu.:  80.0   epsg:NA      :  0  
#>  Am     :22   Median : 270.0   +proj=ster...:  0  
#>  Fw     :10   Mean   : 290.3                      
#>  Ab     : 8   3rd Qu.: 450.0                      
#>  (Other):25   Max.   :1000.0                      
#>  NA's   : 1                                       
summary(st_as_sf(meuse.grid))
#>      part.a           part.b            dist        soil     ffreq   
#>  Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   1:1665   1: 779  
#>  1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.1193   2:1084   2:1335  
#>  Median :0.0000   Median :1.0000   Median :0.2715   3: 354   3: 989  
#>  Mean   :0.3986   Mean   :0.6014   Mean   :0.2971                    
#>  3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:0.4402                    
#>  Max.   :1.0000   Max.   :1.0000   Max.   :0.9926                    
#>           geometry   
#>  POINT        :3103  
#>  epsg:NA      :   0  
#>  +proj=ster...:   0  
#>                      
#>                      
#>                      
summary(st_as_sf(meuse.area))
#>           geometry
#>  POLYGON      :1  
#>  epsg:NA      :0  
#>  +proj=ster...:0  
summary(st_as_sf(meuse.riv))
#>           geometry
#>  POLYGON      :1  
#>  epsg:NA      :0  
#>  +proj=ster...:0  
summary(st_as_sf(as(meuse.riv, "SpatialLines")))
#>           geometry
#>  LINESTRING   :1  
#>  epsg:NA      :0  
#>  +proj=ster...:0  
pol.grd = as(meuse.grid, "SpatialPolygonsDataFrame")
summary(st_as_sf(pol.grd))
#>      part.a           part.b            dist        soil     ffreq   
#>  Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   1:1665   1: 779  
#>  1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.1193   2:1084   2:1335  
#>  Median :0.0000   Median :1.0000   Median :0.2715   3: 354   3: 989  
#>  Mean   :0.3986   Mean   :0.6014   Mean   :0.2971                    
#>  3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:0.4402                    
#>  Max.   :1.0000   Max.   :1.0000   Max.   :0.9926                    
#>           geometry   
#>  POLYGON      :3103  
#>  epsg:NA      :   0  
#>  +proj=ster...:   0  
#>                      
#>                      
#>                      
summary(st_as_sf(as(pol.grd, "SpatialLinesDataFrame")))
#>      part.a           part.b            dist        soil     ffreq   
#>  Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   1:1665   1: 779  
#>  1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.1193   2:1084   2:1335  
#>  Median :0.0000   Median :1.0000   Median :0.2715   3: 354   3: 989  
#>  Mean   :0.3986   Mean   :0.6014   Mean   :0.2971                    
#>  3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:0.4402                    
#>  Max.   :1.0000   Max.   :1.0000   Max.   :0.9926                    
#>           geometry   
#>  LINESTRING   :3103  
#>  epsg:NA      :   0  
#>  +proj=ster...:   0  
#>                      
#>                      
#>                      
if (require(spatstat)) {
  g = st_as_sf(gorillas)
  # select only the points:
  g[st_is(g, "POINT"),]
}
#> Loading required package: spatstat
#> Loading required package: spatstat.data
#> Loading required package: nlme
#> 
#> Attaching package: ‘nlme’
#> The following object is masked from ‘package:dplyr’:
#> 
#>     collapse
#> Loading required package: rpart
#> Registered S3 method overwritten by 'spatstat':
#>   method     from
#>   print.boxx cli 
#> 
#> spatstat 1.63-3       (nickname: ‘Wet paint’) 
#> For an introduction to spatstat, type ‘beginner’ 
#> 
#> Note: R version 3.6.2 (2017-01-27) is more than a year old; we strongly recommend upgrading to the latest version
#> Simple feature collection with 647 features and 4 fields
#> geometry type:  POINT
#> dimension:      XY
#> bbox:           xmin: 580797.3 ymin: 675238.7 xmax: 584945.3 ymax: 678313.5
#> CRS:            NA
#> First 10 features:
#>    label group season       date                      geom
#> 1  point major    dry 2006-01-06 POINT (582518.4 676886.2)
#> 2  point major    dry 2006-01-10   POINT (581823 677422.7)
#> 3  point major    dry 2006-01-15   POINT (582131 676937.9)
#> 4  point major    dry 2006-01-24   POINT (582111.9 677420)
#> 5  point minor    dry 2006-01-27 POINT (582585.1 677509.7)
#> 6  point major    dry 2006-01-28 POINT (582302.3 677521.6)
#> 7  point major    dry 2006-02-01 POINT (583167.2 676730.5)
#> 8  point major    dry 2006-02-03 POINT (583584.5 677207.1)
#> 9  point major    dry 2006-02-13 POINT (583117.8 676850.3)
#> 10 point major    dry 2006-02-15 POINT (582902.8 676724.1)
if (require(spatstat)) {
 data(chicago)
 plot(st_as_sf(chicago)["label"])
 plot(st_as_sf(chicago)[-1,"label"])
}