geojson

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geojson aims to deal only with geojson data, without requiring any of the sp/rgdal/rgeos stack. That means this package is light weight.

We’ve defined classes (S3) following the GeoJSON spec. These classes sort of overlap with sp’s classes, but not really. There’s also some overlap in GeoJSON classes with Well-Known Text (WKT) classes, but GeoJSON has a subset of WKT’s classes.

The package geoops supports manipulations on the classes defined in this package. This package is used within geojsonio to make some tasks easier.

Installation

Stable CRAN version

install.packages("geojson")

Dev version

remotes::install_github("ropensci/geojson")
library("geojson")

geojson class

Essentially a character string with S3 class geojson attached to make it easy to perform operations on

x <- "{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Point\",\"coordinates\":[-99.74,32.45]},\"properties\":{}}]}"
as.geojson(x)
#> <geojson> 
#>   type:  FeatureCollection 
#>   features (n): 1 
#>   features (geometry / length) [first 5]:
#>     Point / 2

geometrycollection

x <- '{
 "type": "GeometryCollection",
 "geometries": [
   {
     "type": "Point",
     "coordinates": [100.0, 0.0]
   },
   {
     "type": "LineString",
     "coordinates": [ [101.0, 0.0], [102.0, 1.0] ]
   }
  ]
}'
(y <- geometrycollection(x))
#> <GeometryCollection> 
#>   geometries (n): 2 
#>   geometries (geometry / length):
#>     Point / 2
#>     LineString / 2

inspect the object

get the string

y[[1]]
#> [1] "{\n \"type\": \"GeometryCollection\",\n \"geometries\": [\n   {\n     \"type\": \"Point\",\n     \"coordinates\": [100.0, 0.0]\n   },\n   {\n     \"type\": \"LineString\",\n     \"coordinates\": [ [101.0, 0.0], [102.0, 1.0] ]\n   }\n  ]\n}"

get the type

geo_type(y)
#> [1] "GeometryCollection"

pretty print the geojson

geo_pretty(y)
#> {
#>     "type": "GeometryCollection",
#>     "geometries": [
#>         {
#>             "type": "Point",
#>             "coordinates": [
#>                 100.0,
#>                 0.0
#>             ]
#>         },
#>         {
#>             "type": "LineString",
#>             "coordinates": [
#>                 [
#>                     101.0,
#>                     0.0
#>                 ],
#>                 [
#>                     102.0,
#>                     1.0
#>                 ]
#>             ]
#>         }
#>     ]
#> }
#>

write to disk

geo_write(y, f <- tempfile(fileext = ".geojson"))
jsonlite::fromJSON(f, FALSE)
#> $type
#> [1] "GeometryCollection"
#> 
#> $geometries
#> $geometries[[1]]
#> $geometries[[1]]$type
#> [1] "Point"
#> 
#> $geometries[[1]]$coordinates
#> $geometries[[1]]$coordinates[[1]]
#> [1] 100
#> 
#> $geometries[[1]]$coordinates[[2]]
#> [1] 0
#> 
#> 
#> 
#> $geometries[[2]]
#> $geometries[[2]]$type
#> [1] "LineString"
#> 
#> $geometries[[2]]$coordinates
#> $geometries[[2]]$coordinates[[1]]
#> $geometries[[2]]$coordinates[[1]][[1]]
#> [1] 101
#> 
#> $geometries[[2]]$coordinates[[1]][[2]]
#> [1] 0
#> 
#> 
#> $geometries[[2]]$coordinates[[2]]
#> $geometries[[2]]$coordinates[[2]][[1]]
#> [1] 102
#> 
#> $geometries[[2]]$coordinates[[2]][[2]]
#> [1] 1

properties

Add properties

x <- '{ "type": "LineString", "coordinates": [ [100.0, 0.0], [101.0, 1.0] ]}'
res <- linestring(x) %>% feature() %>% properties_add(population = 1000)
res
#> <Feature> 
#>   type:  LineString 
#>   coordinates:  [[100,0],[101,1]]

Get a property

properties_get(res, property = 'population')
#> 1000

crs

Add crs

crs <- '{
  "type": "name",
  "properties": {
     "name": "urn:ogc:def:crs:OGC:1.3:CRS84"
  }
}'
z <- x %>% feature() %>% crs_add(crs)
z
#> {
#>     "type": "Feature",
#>     "properties": {
#> 
#>     },
#>     "geometry": {
#>         "type": "LineString",
#>         "coordinates": [
#>             [
#>                 100,
#>                 0
#>             ],
#>             [
#>                 101,
#>                 1
#>             ]
#>         ]
#>     },
#>     "crs": {
#>         "type": "name",
#>         "properties": {
#>             "name": "urn:ogc:def:crs:OGC:1.3:CRS84"
#>         }
#>     }
#> }

Get crs

crs_get(z)
#> $type
#> [1] "name"
#> 
#> $properties
#> $properties$name
#> [1] "urn:ogc:def:crs:OGC:1.3:CRS84"

bbox

Add bbox

tt <- x %>% feature() %>% bbox_add()
tt
#> {
#>     "type": "Feature",
#>     "properties": {
#> 
#>     },
#>     "geometry": {
#>         "type": "LineString",
#>         "coordinates": [
#>             [
#>                 100,
#>                 0
#>             ],
#>             [
#>                 101,
#>                 1
#>             ]
#>         ]
#>     },
#>     "bbox": [
#>         100,
#>         0,
#>         101,
#>         1
#>     ]
#> }

Get bbox

bbox_get(tt)
#> [1] 100   0 101   1

geojson in data.frame’s

x <- '{ "type": "Point", "coordinates": [100.0, 0.0] }'
(pt <- point(x))
#> <Point> 
#>   coordinates:  [100,0]
library("tibble")
tibble(a = 1:5, b = list(pt))
#> # A tibble: 5 x 2
#>       a b             
#>   <int> <list>        
#> 1     1 <geopoint [1]>
#> 2     2 <geopoint [1]>
#> 3     3 <geopoint [1]>
#> 4     4 <geopoint [1]>
#> 5     5 <geopoint [1]>
x <- '{ "type": "MultiLineString",
  "coordinates": [ [ [100.0, 0.0], [101.0, 1.0] ], [ [102.0, 2.0], [103.0, 3.0] ] ] }'
(mls <- multilinestring(x))
#> <MultiLineString> 
#>   no. lines:  2 
#>   no. nodes / line:  2, 2 
#>   coordinates:  [[[100,0],[101,1]],[[102,2],[103,3]]]
tibble(a = 1:5, b = list(mls))
#> # A tibble: 5 x 2
#>       a b             
#>   <int> <list>        
#> 1     1 <gmltlnst [1]>
#> 2     2 <gmltlnst [1]>
#> 3     3 <gmltlnst [1]>
#> 4     4 <gmltlnst [1]>
#> 5     5 <gmltlnst [1]>
tibble(a = 1:5, b = list(pt), c = list(mls))
#> # A tibble: 5 x 3
#>       a b              c             
#>   <int> <list>         <list>        
#> 1     1 <geopoint [1]> <gmltlnst [1]>
#> 2     2 <geopoint [1]> <gmltlnst [1]>
#> 3     3 <geopoint [1]> <gmltlnst [1]>
#> 4     4 <geopoint [1]> <gmltlnst [1]>
#> 5     5 <geopoint [1]> <gmltlnst [1]>

geobuf

Geobuf is a compact binary encoding for geographic data using protocol buffers https://github.com/mapbox/geobuf (via the protolite) package.

file <- system.file("examples/test.pb", package = "geojson")
(json <- from_geobuf(file))
#> {"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"Point","coordinates":[102,0.5]},"id":999,"properties":{"prop0":"value0","double":0.0123,"negative_int":-100,"positive_int":100,"negative_double":-1.2345e+16,"positive_double":1.2345e+16,"null":null,"array":[1,2,3.1],"object":{"foo":[5,6,7]}},"blabla":{"foo":[1,1,1]}},{"type":"Feature","geometry":{"type":"LineString","coordinates":[[102,0],[103,-1.1],[104,-3],[105,1]]},"id":123,"properties":{"custom1":"test","prop0":"value0","prop1":0}},{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[100,0],[101,0],[101,1],[100,1],[100,0]],[[99,10],[101,0],[100,1],[99,10]]]},"id":"test-id","properties":{"prop0":"value0","prop1":{"this":"that"}},"custom1":"jeroen"},{"type":"Feature","geometry":{"type":"MultiPolygon","coordinates":[[[[102,2],[103,2],[103,3],[102,2]]],[[[100,0],[101,0],[101,1],[100,1],[100,0]],[[100.2,0.2],[100.2,0.8],[100.2,0.2]]]]}},{"type":"Feature","geometry":{"type":"GeometryCollection","geometries":[{"type":"Point","coordinates":[100,0]},{"type":"LineString","coordinates":[[101,0],[102,1]]},{"type":"MultiPoint","coordinates":[[100,0],[101,1]]},{"type":"MultiLineString","coordinates":[[[100,0],[101,1]],[[102,2],[103,3]]]},{"type":"MultiPolygon","coordinates":[[[[102,2],[103,2],[103,3],[102,3],[102,2]]],[[[100,0],[101,0],[101,1],[100,1],[100,0]],[[100.2,0.2],[100.8,0.2],[100.8,0.8],[100.2,0.8],[100.2,0.2]]]]}]}}]}
pb <- to_geobuf(json)
class(pb)
#> [1] "raw"
f <- tempfile(fileext = ".pb")
to_geobuf(json, f)
from_geobuf(f)
#> {"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"Point","coordinates":[102,0.5]},"id":999,"properties":{"prop0":"value0","double":0.0123,"negative_int":-100,"positive_int":100,"negative_double":-1.2345e+16,"positive_double":1.2345e+16,"null":null,"array":[1,2,3.1],"object":{"foo":[5,6,7]}},"blabla":{"foo":[1,1,1]}},{"type":"Feature","geometry":{"type":"LineString","coordinates":[[102,0],[103,-1.1],[104,-3],[105,1]]},"id":123,"properties":{"custom1":"test","prop0":"value0","prop1":0}},{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[100,0],[101,0],[101,1],[100,1],[100,0]],[[99,10],[101,0],[100,1],[99,10]]]},"id":"test-id","properties":{"prop0":"value0","prop1":{"this":"that"}},"custom1":"jeroen"},{"type":"Feature","geometry":{"type":"MultiPolygon","coordinates":[[[[102,2],[103,2],[103,3],[102,2]]],[[[100,0],[101,0],[101,1],[100,1],[100,0]],[[100.2,0.2],[100.2,0.8],[100.2,0.2]]]]}},{"type":"Feature","geometry":{"type":"GeometryCollection","geometries":[{"type":"Point","coordinates":[100,0]},{"type":"LineString","coordinates":[[101,0],[102,1]]},{"type":"MultiPoint","coordinates":[[100,0],[101,1]]},{"type":"MultiLineString","coordinates":[[[100,0],[101,1]],[[102,2],[103,3]]]},{"type":"MultiPolygon","coordinates":[[[[102,2],[103,2],[103,3],[102,3],[102,2]]],[[[100,0],[101,0],[101,1],[100,1],[100,0]],[[100.2,0.2],[100.8,0.2],[100.8,0.8],[100.2,0.8],[100.2,0.2]]]]}]}}]}

x <- '{ "type": "Polygon",
"coordinates": [
  [ [100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0] ]
  ]
}'
y <- polygon(x)
to_geobuf(y)
#>  [1] 10 02 18 06 2a 1a 0a 18 08 04 12 01 04 1a 11 80 84 af 5f 00 80 89 7a 00 00
#> [26] 80 89 7a ff 88 7a 00

x <- '{"type": "MultiPoint", "coordinates": [ [100.0, 0.0], [101.0, 1.0] ] }'
y <- multipoint(x)
to_geobuf(y)
#>  [1] 10 02 18 06 2a 11 0a 0f 08 01 1a 0b 80 84 af 5f 00 80 89 7a 80 89 7a

newline-delimited GeoJSON

read nd-GeoJSON

url <- "https://raw.githubusercontent.com/ropensci/geojson/master/inst/examples/ndgeojson1.json"
f <- tempfile(fileext = ".geojsonl")
download.file(url, f)
x <- ndgeo_read(f, verbose = FALSE)
x
#> <geojson> 
#>   type:  FeatureCollection 
#>   features (n): 3 
#>   features (geometry / length) [first 5]:
#>     Point / 2
#>     Point / 2
#>     Point / 2

Write nd-GeoJSON

One would think we could take the output of ndego_read() above and pass to ndgeo_write(). However, in this example, the json is too big for jqr to handle, the underlying parser tool. So here’s a smaller example:

file <- system.file("examples", "featurecollection2.geojson",
  package = "geojson")
str <- paste0(readLines(file), collapse = " ")
(x <- featurecollection(str))
#> <FeatureCollection> 
#>   type:  FeatureCollection 
#>   no. features:  3 
#>   features (1st 5):  Point, Point, Point
outfile <- tempfile(fileext = ".geojson")
ndgeo_write(x, outfile)
jsonlite::stream_in(file(outfile))
#> 
 Found 3 records...
 Imported 3 records. Simplifying...
#>      type id   properties.NOME
#> 1 Feature  0 Sec de segunrança
#> 2 Feature  1             Teste
#> 3 Feature  3 Delacorte Theater
#>                                                            properties.URL
#> 1 http://www.theatermania.com/new-york/theaters/45th-street-theatre_2278/
#> 2          http://www.bestofoffbroadway.com/theaters/47streettheatre.html
#> 3     http://www.centralpark.com/pages/attractions/delacorte-theatre.html
#>                      properties.ADDRESS1 properties.CIDADE properties.CEP
#> 1                   354 West 45th Street           Goiânia       74250010
#> 2                   304 West 47th Street          New York             NA
#> 3 Central Park - Mid-Park at 80th Street          New York             NA
#>   properties.ZIP geometry.type geometry.coordinates
#> 1             NA         Point -49.25624, -16.68961
#> 2       74250010         Point -49.27624, -16.65561
#> 3       74250010         Point -49.27726, -16.67906

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