R_Extracting coordinates from SpatialPolygonsDataFrame - r

Question

Is it only me who have the problem with extracting coordinates of a polygon from SpatialPolygonsDataFrame object? I am able to extract other slots of the object (ID,plotOrder) but not coordinates (coords). I don't know what I am doing wrong. Please find below my R session where bdryData being the SpatialPolygonsDataFrame object with two polygons.
> bdryData
An object of class "SpatialPolygonsDataFrame"
Slot "data":
ID GRIDCODE
0 1 0
1 2 0
Slot "polygons":
[[1]]
An object of class "Polygons"
Slot "Polygons":
[[1]]
An object of class "Polygon"
Slot "labpt":
[1] 415499.1 432781.7
Slot "area":
[1] 0.6846572
Slot "hole":
[1] FALSE
Slot "ringDir":
[1] 1
Slot "coords":
[,1] [,2]
[1,] 415499.6 432781.2
[2,] 415498.4 432781.5
[3,] 415499.3 432782.4
[4,] 415499.6 432781.2
Slot "plotOrder":
[1] 1
Slot "labpt":
[1] 415499.1 432781.7
Slot "ID":
[1] "0"
Slot "area":
[1] 0.6846572
[[2]]
An object of class "Polygons"
Slot "Polygons":
[[1]]
An object of class "Polygon"
Slot "labpt":
[1] 415587.3 432779.4
Slot "area":
[1] 20712.98
Slot "hole":
[1] FALSE
Slot "ringDir":
[1] 1
Slot "coords":
[,1] [,2]
[1,] 415499.6 432781.2
[2,] 415505.0 432781.8
[3,] 415506.5 432792.6
[4,] 415508.9 432792.8
[5,] 415515.0 432791.5
[6,] 415517.7 432795.6
[7,] 415528.6 432797.7
[8,] 415538.8 432804.2
[9,] 415543.2 432805.8
[10,] 415545.1 432803.6
[11,] 415547.1 432804.7
[12,] 415551.7 432805.8
[13,] 415557.5 432812.3
[14,] 415564.2 432817.1
[15,] 415568.5 432823.9
[16,] 415571.0 432826.8
[17,] 415573.2 432828.7
[18,] 415574.1 432829.7
[19,] 415576.2 432830.7
[20,] 415580.2 432833.8
[21,] 415589.6 432836.0
[22,] 415593.1 432841.0
[23,] 415592.2 432843.7
[24,] 415590.6 432846.6
[25,] 415589.0 432853.3
[26,] 415584.8 432855.3
[27,] 415579.7 432859.8
[28,] 415577.7 432866.2
[29,] 415575.6 432868.1
[30,] 415566.7 432880.7
[31,] 415562.7 432887.5
[32,] 415559.2 432889.1
[33,] 415561.5 432890.7
[34,] 415586.2 432889.7
[35,] 415587.1 432888.6
[36,] 415588.5 432890.2
[37,] 415598.2 432888.7
[38,] 415599.1 432887.7
[39,] 415601.2 432886.7
[40,] 415603.1 432885.7
[41,] 415605.2 432884.7
[42,] 415606.1 432882.7
[43,] 415607.2 432880.7
[44,] 415608.3 432878.3
[45,] 415612.2 432874.8
[46,] 415614.7 432871.9
[47,] 415617.1 432870.7
[48,] 415622.4 432868.2
[49,] 415622.0 432862.4
[50,] 415624.2 432855.4
[51,] 415633.2 432845.3
[52,] 415639.0 432841.1
[53,] 415642.8 432832.9
[54,] 415647.5 432828.7
[55,] 415654.3 432820.3
[56,] 415654.1 432816.5
[57,] 415658.2 432812.8
[58,] 415661.9 432808.6
[59,] 415663.5 432808.7
[60,] 415668.1 432803.5
[61,] 415676.5 432801.3
[62,] 415679.1 432802.7
[63,] 415680.1 432802.7
[64,] 415681.1 432802.7
[65,] 415682.2 432802.7
[66,] 415685.8 432804.7
[67,] 415691.8 432802.2
[68,] 415693.6 432798.9
[69,] 415696.2 432777.0
[70,] 415689.8 432773.5
[71,] 415683.7 432771.6
[72,] 415680.2 432766.7
[73,] 415679.0 432765.6
[74,] 415676.8 432753.7
[75,] 415671.4 432747.7
[76,] 415662.7 432747.2
[77,] 415658.7 432750.0
[78,] 415657.0 432746.3
[79,] 415654.1 432743.7
[80,] 415652.3 432739.8
[81,] 415649.6 432739.6
[82,] 415648.0 432739.7
[83,] 415641.9 432736.4
[84,] 415633.4 432736.9
[85,] 415630.2 432734.7
[86,] 415622.3 432733.6
[87,] 415614.4 432726.5
[88,] 415617.1 432719.1
[89,] 415612.5 432718.1
[90,] 415610.0 432720.9
[91,] 415606.2 432716.6
[92,] 415603.2 432713.9
[93,] 415601.4 432710.0
[94,] 415580.3 432708.7
[95,] 415545.1 432709.7
[96,] 415543.5 432711.5
[97,] 415534.0 432715.7
[98,] 415527.1 432713.7
[99,] 415521.1 432711.6
[100,] 415505.6 432710.6
[101,] 415501.3 432710.9
[102,] 415499.3 432708.7
[103,] 415495.6 432711.6
[104,] 415482.6 432726.2
[105,] 415477.2 432734.0
[106,] 415478.1 432737.7
[107,] 415479.2 432739.7
[108,] 415480.9 432743.4
[109,] 415486.5 432751.2
[110,] 415493.2 432760.7
[111,] 415494.1 432762.7
[112,] 415498.1 432767.9
[113,] 415497.2 432770.7
[114,] 415490.6 432773.2
[115,] 415493.2 432775.6
[116,] 415496.0 432778.7
[117,] 415499.2 432779.7
[118,] 415499.6 432781.2
Slot "plotOrder":
[1] 1
Slot "labpt":
[1] 415587.3 432779.4
Slot "ID":
[1] "1"
Slot "area":
[1] 20712.98
Slot "plotOrder":
[1] 2 1
Slot "bbox":
min max
x 415477.2 415696.2
y 432708.7 432890.7
Slot "proj4string":
CRS arguments:
+proj=tmerc +lat_0=49 +lon_0=-2 +k=0.9996012717 +x_0=400000 +y_0=-100000
+datum=OSGB36 +units=m +no_defs +ellps=airy
+towgs84=446.448,-125.157,542.060,0.1502,0.2470,0.8421,-20.4894
Subsetting second polygon from bdryData
> bdryData#polygons[[2]]
An object of class "Polygons"
Slot "Polygons":
[[1]]
An object of class "Polygon"
Slot "labpt":
[1] 415587.3 432779.4
Slot "area":
[1] 20712.98
Slot "hole":
[1] FALSE
Slot "ringDir":
[1] 1
Slot "coords":
[,1] [,2]
[1,] 415499.6 432781.2
[2,] 415505.0 432781.8
[3,] 415506.5 432792.6
[4,] 415508.9 432792.8
[5,] 415515.0 432791.5
[6,] 415517.7 432795.6
[7,] 415528.6 432797.7
[8,] 415538.8 432804.2
[9,] 415543.2 432805.8
[10,] 415545.1 432803.6
[11,] 415547.1 432804.7
[12,] 415551.7 432805.8
[13,] 415557.5 432812.3
[14,] 415564.2 432817.1
[15,] 415568.5 432823.9
[16,] 415571.0 432826.8
[17,] 415573.2 432828.7
[18,] 415574.1 432829.7
[19,] 415576.2 432830.7
[20,] 415580.2 432833.8
[21,] 415589.6 432836.0
[22,] 415593.1 432841.0
[23,] 415592.2 432843.7
[24,] 415590.6 432846.6
[25,] 415589.0 432853.3
[26,] 415584.8 432855.3
[27,] 415579.7 432859.8
[28,] 415577.7 432866.2
[29,] 415575.6 432868.1
[30,] 415566.7 432880.7
[31,] 415562.7 432887.5
[32,] 415559.2 432889.1
[33,] 415561.5 432890.7
[34,] 415586.2 432889.7
[35,] 415587.1 432888.6
[36,] 415588.5 432890.2
[37,] 415598.2 432888.7
[38,] 415599.1 432887.7
[39,] 415601.2 432886.7
[40,] 415603.1 432885.7
[41,] 415605.2 432884.7
[42,] 415606.1 432882.7
[43,] 415607.2 432880.7
[44,] 415608.3 432878.3
[45,] 415612.2 432874.8
[46,] 415614.7 432871.9
[47,] 415617.1 432870.7
[48,] 415622.4 432868.2
[49,] 415622.0 432862.4
[50,] 415624.2 432855.4
[51,] 415633.2 432845.3
[52,] 415639.0 432841.1
[53,] 415642.8 432832.9
[54,] 415647.5 432828.7
[55,] 415654.3 432820.3
[56,] 415654.1 432816.5
[57,] 415658.2 432812.8
[58,] 415661.9 432808.6
[59,] 415663.5 432808.7
[60,] 415668.1 432803.5
[61,] 415676.5 432801.3
[62,] 415679.1 432802.7
[63,] 415680.1 432802.7
[64,] 415681.1 432802.7
[65,] 415682.2 432802.7
[66,] 415685.8 432804.7
[67,] 415691.8 432802.2
[68,] 415693.6 432798.9
[69,] 415696.2 432777.0
[70,] 415689.8 432773.5
[71,] 415683.7 432771.6
[72,] 415680.2 432766.7
[73,] 415679.0 432765.6
[74,] 415676.8 432753.7
[75,] 415671.4 432747.7
[76,] 415662.7 432747.2
[77,] 415658.7 432750.0
[78,] 415657.0 432746.3
[79,] 415654.1 432743.7
[80,] 415652.3 432739.8
[81,] 415649.6 432739.6
[82,] 415648.0 432739.7
[83,] 415641.9 432736.4
[84,] 415633.4 432736.9
[85,] 415630.2 432734.7
[86,] 415622.3 432733.6
[87,] 415614.4 432726.5
[88,] 415617.1 432719.1
[89,] 415612.5 432718.1
[90,] 415610.0 432720.9
[91,] 415606.2 432716.6
[92,] 415603.2 432713.9
[93,] 415601.4 432710.0
[94,] 415580.3 432708.7
[95,] 415545.1 432709.7
[96,] 415543.5 432711.5
[97,] 415534.0 432715.7
[98,] 415527.1 432713.7
[99,] 415521.1 432711.6
[100,] 415505.6 432710.6
[101,] 415501.3 432710.9
[102,] 415499.3 432708.7
[103,] 415495.6 432711.6
[104,] 415482.6 432726.2
[105,] 415477.2 432734.0
[106,] 415478.1 432737.7
[107,] 415479.2 432739.7
[108,] 415480.9 432743.4
[109,] 415486.5 432751.2
[110,] 415493.2 432760.7
[111,] 415494.1 432762.7
[112,] 415498.1 432767.9
[113,] 415497.2 432770.7
[114,] 415490.6 432773.2
[115,] 415493.2 432775.6
[116,] 415496.0 432778.7
[117,] 415499.2 432779.7
[118,] 415499.6 432781.2
Slot "plotOrder":
[1] 1
Slot "labpt":
[1] 415587.3 432779.4
Slot "ID":
[1] "1"
Slot "area":
[1] 20712.98
Extracting slots
> bdryData#polygons[[2]]#ID
[1] "1"
> bdryData#polygons[[2]]#plotOrder
[1] 1
But problem with coordinates
> bdryData#polygons[[2]]#coords
Error: no slot of name "coords" for this object of class "Polygons"
Any help is really appreciated. Thanks.

Answer 1

Finally, I figured out that I didn't parse the output correctly. The correct way to do is bdryData#polygons[[2]]#Polygons[[1]]#coords. Mind the difference in command polygons(Polygons and polygons) and it took me ages to find out.

Answer 2

Use the coordinates() function from the sp package. It should give you the values in a list format.
You can also get the Polygon attribute from the shapefile.
mfile = readOGR(dsn=dsn,layer=layername)
polys = attr(mfile,'polygons')
npolys = length(polys)
for (i in 1:npolys){
poly = polys[[i]]
polys2 = attr(poly,'Polygons')
npolys2 = length(polys2)
for (j in 1:npolys2){
#do stuff with these values
coords = coordinates(polys2[[j]])
}
}

Answer 3

This took me a while to figure out too. The following function I wrote worked for me. sp.df should be SpatialPolygonsDataFrame.
extractCoords <- function(sp.df)
{
results <- list()
for(i in 1:length(sp.df#polygons[[1]]#Polygons))
{
results[[i]] <- sp.df#polygons[[1]]#Polygons[[i]]#coords
}
results <- Reduce(rbind, results)
results
}

Answer 4

This question was also addressed on gis.stackexchange, here. I made an example below testing all the options mentioned here by #mdsumner. Also have a look here
library(sp)
library(sf)
#> Warning: package 'sf' was built under R version 3.5.3
#> Linking to GEOS 3.6.1, GDAL 2.2.3, PROJ 4.9.3
library(raster)
library(spbabel)
#> Warning: package 'spbabel' was built under R version 3.5.3
library(tmap)
library(microbenchmark)
library(ggplot2)
# Prepare data
data(World)
# Convert from sf to sp objects
atf_sf <- World[World$iso_a3 == "ATF", ]
atf_sp <- as(atf_sf, "Spatial")
atf_sp
#> class : SpatialPolygonsDataFrame
#> features : 1
#> extent : 5490427, 5660887, -6048972, -5932855 (xmin, xmax, ymin, ymax)
#> coord. ref. : +proj=eck4 +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
#> variables : 15
#> # A tibble: 1 x 15
#> iso_a3 name sovereignt continent area pop_est pop_est_dens economy
#> <fct> <fct> <fct> <fct> <S3:> <dbl> <dbl> <fct>
#> 1 ATF Fr. ~ France Seven se~ 7257~ 140 0.0193 6. Dev~
#> # ... with 7 more variables: income_grp <fct>, gdp_cap_est <dbl>,
#> # life_exp <dbl>, well_being <dbl>, footprint <dbl>, inequality <dbl>,
#> # HPI <dbl>
# Try various functions:
raster::geom(atf_sp)
#> object part cump hole x y
#> [1,] 1 1 1 0 5550200 -5932855
#> [2,] 1 1 1 0 5589907 -5964836
#> [3,] 1 1 1 0 5660887 -5977490
#> [4,] 1 1 1 0 5656160 -5996685
#> [5,] 1 1 1 0 5615621 -6042456
#> [6,] 1 1 1 0 5490427 -6048972
#> [7,] 1 1 1 0 5509148 -5995424
#> [8,] 1 1 1 0 5536900 -5953683
#> [9,] 1 1 1 0 5550200 -5932855
ggplot2::fortify(atf_sp)
#> Regions defined for each Polygons
#> long lat order hole piece id group
#> 1 5550200 -5932855 1 FALSE 1 8 8.1
#> 2 5589907 -5964836 2 FALSE 1 8 8.1
#> 3 5660887 -5977490 3 FALSE 1 8 8.1
#> 4 5656160 -5996685 4 FALSE 1 8 8.1
#> 5 5615621 -6042456 5 FALSE 1 8 8.1
#> 6 5490427 -6048972 6 FALSE 1 8 8.1
#> 7 5509148 -5995424 7 FALSE 1 8 8.1
#> 8 5536900 -5953683 8 FALSE 1 8 8.1
#> 9 5550200 -5932855 9 FALSE 1 8 8.1
spbabel::sptable(atf_sp)
#> # A tibble: 9 x 6
#> object_ branch_ island_ order_ x_ y_
#> <int> <int> <lgl> <int> <dbl> <dbl>
#> 1 1 1 TRUE 1 5550200. -5932855.
#> 2 1 1 TRUE 2 5589907. -5964836.
#> 3 1 1 TRUE 3 5660887. -5977490.
#> 4 1 1 TRUE 4 5656160. -5996685.
#> 5 1 1 TRUE 5 5615621. -6042456.
#> 6 1 1 TRUE 6 5490427. -6048972.
#> 7 1 1 TRUE 7 5509148. -5995424.
#> 8 1 1 TRUE 8 5536900. -5953683.
#> 9 1 1 TRUE 9 5550200. -5932855.
as.data.frame(as(as(atf_sp, "SpatialLinesDataFrame"),"SpatialPointsDataFrame"))
#> iso_a3 name sovereignt continent
#> 8 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> 8.1 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> 8.2 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> 8.3 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> 8.4 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> 8.5 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> 8.6 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> 8.7 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> 8.8 ATF Fr. S. Antarctic Lands France Seven seas (open ocean)
#> area pop_est pop_est_dens economy
#> 8 7257.455 [km^2] 140 0.01929051 6. Developing region
#> 8.1 7257.455 [km^2] 140 0.01929051 6. Developing region
#> 8.2 7257.455 [km^2] 140 0.01929051 6. Developing region
#> 8.3 7257.455 [km^2] 140 0.01929051 6. Developing region
#> 8.4 7257.455 [km^2] 140 0.01929051 6. Developing region
#> 8.5 7257.455 [km^2] 140 0.01929051 6. Developing region
#> 8.6 7257.455 [km^2] 140 0.01929051 6. Developing region
#> 8.7 7257.455 [km^2] 140 0.01929051 6. Developing region
#> 8.8 7257.455 [km^2] 140 0.01929051 6. Developing region
#> income_grp gdp_cap_est life_exp well_being footprint
#> 8 2. High income: nonOECD 114285.7 NA NA NA
#> 8.1 2. High income: nonOECD 114285.7 NA NA NA
#> 8.2 2. High income: nonOECD 114285.7 NA NA NA
#> 8.3 2. High income: nonOECD 114285.7 NA NA NA
#> 8.4 2. High income: nonOECD 114285.7 NA NA NA
#> 8.5 2. High income: nonOECD 114285.7 NA NA NA
#> 8.6 2. High income: nonOECD 114285.7 NA NA NA
#> 8.7 2. High income: nonOECD 114285.7 NA NA NA
#> 8.8 2. High income: nonOECD 114285.7 NA NA NA
#> inequality HPI Lines.NR Lines.ID Line.NR coords.x1 coords.x2
#> 8 NA NA 1 8 1 5550200 -5932855
#> 8.1 NA NA 1 8 1 5589907 -5964836
#> 8.2 NA NA 1 8 1 5660887 -5977490
#> 8.3 NA NA 1 8 1 5656160 -5996685
#> 8.4 NA NA 1 8 1 5615621 -6042456
#> 8.5 NA NA 1 8 1 5490427 -6048972
#> 8.6 NA NA 1 8 1 5509148 -5995424
#> 8.7 NA NA 1 8 1 5536900 -5953683
#> 8.8 NA NA 1 8 1 5550200 -5932855
# What about speed? raster::geom is the fastest
res <- microbenchmark(raster::geom(atf_sp),
ggplot2::fortify(atf_sp),
spbabel::sptable(atf_sp),
as.data.frame(as(as(atf_sp, "SpatialLinesDataFrame"),
"SpatialPointsDataFrame")))
ggplot2::autoplot(res)
#> Coordinate system already present. Adding new coordinate system, which will replace the existing one.
Created on 2019-03-23 by the reprex package (v0.2.1)

Answer 5

ggplot2's fortify() function may be deprecated at some point so the broom package is now suggested
library(broom)
broom::tidy(atf_sp)

Answer 6

The only valid answer on this posting was provided by the author "repres_package" above. See that author's recommended solutions if you want to get the right answer. If you want to obtain the geometry of a polygon dataset, you are seeking the long and lat for every single vertex in the polygon feature class. The author's suggestion of using raster::geom() or ggplot2::fortify(), for example, will give you the total number of vertices that are contained in the spatialpolygonsdataframe. That's what you want. The other author's fail to do so.
For example, in my spatialpolygonsdataframe of North Carolina counties (from US Census), I have a total of 1259547 vertices. By using raster::geom(NC_counties), I am given a dataframe that contains a long and lat for each of those 1259547 vertices. I could also use gglot2::fortify(NC_counties) to obtain coordinates for those 1259547 vertices. All of the valid options are given in the answer by "repres_package".
When I ran the recommended codes in the other answers on this posting, I obtained long and lat coordinates for only 672 vertices, 1041 vertices, or 1721 vertices, which is off by over one million vertices. I'm supposed to get long and lat coordiates for 1259547 vertices. I suspect that those codes are interpolating centroids for the polygons, which is not the geometry of the polygons.