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.
Although not ready yet, geoops supports manipulations on the classes defined in this package.
Stable CRAN version
install.packages("geojson")Dev version
devtools::install_github("ropensci/geojson")library("geojson")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
#> bounding box: 99.74 32.45 99.74 32.45
#> features (n): 1
#> features (geometry / length):
#> Point / 2x <- '{
"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 / 2get 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] 1Add properties
x <- '{ "type": "LineString", "coordinates": [ [100.0, 0.0], [101.0, 1.0] ]}'
res <- linestring(x) %>% feature() %>% properties_add(population = 1000)
res
#> {
#> "type": "Feature",
#> "properties": {
#> "population": 1000
#> },
#> "geometry": {
#> "type": "LineString",
#> "coordinates": [
#> [
#> 100,
#> 0
#> ],
#> [
#> 101,
#> 1
#> ]
#> ]
#> }
#> }Get a property
properties_get(res, property = 'population')
#> 1000Add 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"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 1x <- '{ "type": "Point", "coordinates": [100.0, 0.0] }'
(pt <- point(x))
#> <Point>
#> coordinates: [100,0]library("tibble")
data_frame(a = 1:5, b = list(pt))
#> # A tibble: 5 × 2
#> a b
#> <int> <list>
#> 1 1 <S3: geopoint>
#> 2 2 <S3: geopoint>
#> 3 3 <S3: geopoint>
#> 4 4 <S3: geopoint>
#> 5 5 <S3: geopoint>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]]]data_frame(a = 1:5, b = list(mls))
#> # A tibble: 5 × 2
#> a b
#> <int> <list>
#> 1 1 <S3: geomultilinestring>
#> 2 2 <S3: geomultilinestring>
#> 3 3 <S3: geomultilinestring>
#> 4 4 <S3: geomultilinestring>
#> 5 5 <S3: geomultilinestring>data_frame(a = 1:5, b = list(pt), c = list(mls))
#> # A tibble: 5 × 3
#> a b c
#> <int> <list> <list>
#> 1 1 <S3: geopoint> <S3: geomultilinestring>
#> 2 2 <S3: geopoint> <S3: geomultilinestring>
#> 3 3 <S3: geopoint> <S3: geomultilinestring>
#> 4 4 <S3: geopoint> <S3: geomultilinestring>
#> 5 5 <S3: geopoint> <S3: geomultilinestring>- Please report any issues or bugs.
- License: MIT
- Get citation information for
geojsonin R doingcitation(package = 'geojson') - Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
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