geojson_list function

Convert many input types with spatial data to geojson specified as a list

Convert many input types with spatial data to geojson specified as a list

geojson_list( input, lat = NULL, lon = NULL, group = NULL, geometry = "point", type = "FeatureCollection", convert_wgs84 = FALSE, crs = NULL, precision = NULL, ... )

Arguments

  • input: Input list, data.frame, spatial class, or sf class. Inputs can also be dplyr tbl_df class since it inherits from data.frame

  • lat: (character) Latitude name. The default is NULL, and we attempt to guess.

  • lon: (character) Longitude name. The default is NULL, and we attempt to guess.

  • group: (character) A grouping variable to perform grouping for polygons - doesn't apply for points

  • geometry: (character) One of point (Default) or polygon.

  • type: (character) The type of collection. One of FeatureCollection (default) or GeometryCollection.

  • convert_wgs84: Should the input be converted to the standard CRS for GeoJSON (https://tools.ietf.org/html/rfc7946) (geographic coordinate reference system, using the WGS84 datum, with longitude and latitude units of decimal degrees; EPSG: 4326). Default is FALSE though this may change in a future package version. This will only work for sf or Spatial objects with a CRS already defined. If one is not defined but you know what it is, you may define it in the crs argument below.

  • crs: The CRS of the input if it is not already defined. This can be an epsg code as a four or five digit integer or a valid proj4 string. This argument will be ignored if convert_wgs84 is FALSE

    or the object already has a CRS.

  • precision: (integer) desired number of decimal places for coordinates. Only used with classes from sp classes; ignored for other classes. Using fewer decimal places decreases object sizes (at the cost of precision). This changes the underlying precision stored in the data. options(digits = <some number>) changes the maximum number of digits displayed (to find out what yours is set at see getOption("digits")); the value of this parameter will change what's displayed in your console up to the value of getOption("digits")

  • ...: Ignored

Details

This function creates a geojson structure as an R list; it does not write a file - see geojson_write() for that.

Note that all sp class objects will output as FeatureCollection objects, while other classes (numeric, list, data.frame) can be output as FeatureCollection or GeometryCollection objects. We're working on allowing GeometryCollection option for sp class objects.

Also note that with sp classes we do make a round-trip, using sf::st_write() to write GeoJSON to disk, then read it back in. This is fast and we don't have to think about it too much, but this disk round-trip is not ideal.

For sf classes (sf, sfc, sfg), the following conversions are made:

  • sfg: the appropriate geometry Point, LineString, Polygon, MultiPoint, MultiLineString, MultiPolygon,GeometryCollection
  • sfc: GeometryCollection, unless the sfc is length 1, then the geometry as above
  • sf: FeatureCollection

For list and data.frame objects, you don't have to pass in lat and lon parameters if they are named appropriately (e.g., lat/latitude, lon/long/longitude), as they will be auto-detected. If they can not be found, the function will stop and warn you to specify the parameters specifically.

Examples

## Not run: # From a numeric vector of length 2 to a point vec <- c(-99.74, 32.45) geojson_list(vec) # Lists ## From a list mylist <- list( list(latitude = 30, longitude = 120, marker = "red"), list(latitude = 30, longitude = 130, marker = "blue") ) geojson_list(mylist) ## From a list of numeric vectors to a polygon vecs <- list( c(100.0, 0.0), c(101.0, 0.0), c(101.0, 1.0), c(100.0, 1.0), c(100.0, 0.0) ) geojson_list(vecs, geometry = "polygon") # from data.frame to points (res <- geojson_list(us_cities[1:2, ], lat = "lat", lon = "long")) as.json(res) ## guess lat/long columns geojson_list(us_cities[1:2, ]) geojson_list(states[1:3, ]) geojson_list(states[1:351, ], geometry = "polygon", group = "group") geojson_list(canada_cities[1:30, ]) ## a data.frame with columsn not named appropriately, but you can ## specify them # dat <- data.frame(a = c(31, 41), b = c(-120, -110)) # geojson_list(dat) # geojson_list(dat, lat="a", lon="b") # from data.frame to polygons head(states) geojson_list(states[1:351, ], lat = "lat", lon = "long", geometry = "polygon", group = "group" ) # From SpatialPolygons class library("sp") poly1 <- Polygons(list(Polygon(cbind( c(-100, -90, -85, -100), c(40, 50, 45, 40) ))), "1") poly2 <- Polygons(list(Polygon(cbind( c(-90, -80, -75, -90), c(30, 40, 35, 30) ))), "2") sp_poly <- SpatialPolygons(list(poly1, poly2), 1:2) geojson_list(sp_poly) # From SpatialPolygons class with precision agreement x_coord <- c( -114.345703125, -114.345703125, -106.61132812499999, -106.61132812499999, -114.345703125 ) y_coord <- c( 39.436192999314095, 43.45291889355468, 43.45291889355468, 39.436192999314095, 39.436192999314095 ) coords <- cbind(x_coord, y_coord) poly <- Polygon(coords) polys <- Polygons(list(poly), 1) sp_poly2 <- SpatialPolygons(list(polys)) geojson_list(sp_poly2, geometry = "polygon", precision = 4) geojson_list(sp_poly2, geometry = "polygon", precision = 3) geojson_list(sp_poly2, geometry = "polygon", precision = 2) # From SpatialPoints class with precision points <- SpatialPoints(cbind(x_coord, y_coord)) geojson_list(points) # From SpatialPolygonsDataFrame class sp_polydf <- as(sp_poly, "SpatialPolygonsDataFrame") geojson_list(input = sp_polydf) # From SpatialPoints class x <- c(1, 2, 3, 4, 5) y <- c(3, 2, 5, 1, 4) s <- SpatialPoints(cbind(x, y)) geojson_list(s) # From SpatialPointsDataFrame class s <- SpatialPointsDataFrame(cbind(x, y), mtcars[1:5, ]) geojson_list(s) # From SpatialLines class library("sp") c1 <- cbind(c(1, 2, 3), c(3, 2, 2)) c2 <- cbind(c1[, 1] + .05, c1[, 2] + .05) c3 <- cbind(c(1, 2, 3), c(1, 1.5, 1)) L1 <- Line(c1) L2 <- Line(c2) L3 <- Line(c3) Ls1 <- Lines(list(L1), ID = "a") Ls2 <- Lines(list(L2, L3), ID = "b") sl1 <- SpatialLines(list(Ls1)) sl12 <- SpatialLines(list(Ls1, Ls2)) geojson_list(sl1) geojson_list(sl12) as.json(geojson_list(sl12)) as.json(geojson_list(sl12), pretty = TRUE) # From SpatialLinesDataFrame class dat <- data.frame( X = c("Blue", "Green"), Y = c("Train", "Plane"), Z = c("Road", "River"), row.names = c("a", "b") ) sldf <- SpatialLinesDataFrame(sl12, dat) geojson_list(sldf) as.json(geojson_list(sldf)) as.json(geojson_list(sldf), pretty = TRUE) # From SpatialGrid x <- GridTopology(c(0, 0), c(1, 1), c(5, 5)) y <- SpatialGrid(x) geojson_list(y) # From SpatialGridDataFrame sgdim <- c(3, 4) sg <- SpatialGrid(GridTopology(rep(0, 2), rep(10, 2), sgdim)) sgdf <- SpatialGridDataFrame(sg, data.frame(val = 1:12)) geojson_list(sgdf) # From SpatialPixels library("sp") pixels <- suppressWarnings( SpatialPixels(SpatialPoints(us_cities[c("long", "lat")])) ) summary(pixels) geojson_list(pixels) # From SpatialPixelsDataFrame library("sp") pixelsdf <- suppressWarnings( SpatialPixelsDataFrame( points = canada_cities[c("long", "lat")], data = canada_cities ) ) geojson_list(pixelsdf) # From sf classes: if (require(sf)) { ## sfg (a single simple features geometry) p1 <- rbind(c(0, 0), c(1, 0), c(3, 2), c(2, 4), c(1, 4), c(0, 0)) poly <- rbind(c(1, 1), c(1, 2), c(2, 2), c(1, 1)) poly_sfg <- st_polygon(list(p1)) geojson_list(poly_sfg) ## sfc (a collection of geometries) p1 <- rbind(c(0, 0), c(1, 0), c(3, 2), c(2, 4), c(1, 4), c(0, 0)) p2 <- rbind(c(5, 5), c(5, 6), c(4, 5), c(5, 5)) poly_sfc <- st_sfc(st_polygon(list(p1)), st_polygon(list(p2))) geojson_list(poly_sfc) ## sf (collection of geometries with attributes) p1 <- rbind(c(0, 0), c(1, 0), c(3, 2), c(2, 4), c(1, 4), c(0, 0)) p2 <- rbind(c(5, 5), c(5, 6), c(4, 5), c(5, 5)) poly_sfc <- st_sfc(st_polygon(list(p1)), st_polygon(list(p2))) poly_sf <- st_sf(foo = c("a", "b"), bar = 1:2, poly_sfc) geojson_list(poly_sf) } ## End(Not run)