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

Description

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

Usage

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geojson_json(input, lat = NULL, lon = NULL, group = NULL,
  geometry = "point", type = "FeatureCollection", ...)

Arguments

input

Input list, data.frame, or spatial 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.

...

Further args passed on to toJSON

Details

This function creates a geojson structure as a json character string; it does not write a file using rgdal - 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 writeOGR 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.

Value

An object of class geo_json (and json)

Examples

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## Not run: 
# From a numeric vector of length 2, making a point type
geojson_json(c(-99.74,32.45), pretty=TRUE)
geojson_json(c(-99.74,32.45), type = "GeometryCollection", pretty=TRUE)

## polygon type
### this requires numeric class input, so inputting a list will dispatch on the list method
poly <- c(c(-114.345703125,39.436192999314095),
          c(-114.345703125,43.45291889355468),
          c(-106.61132812499999,43.45291889355468),
          c(-106.61132812499999,39.436192999314095),
          c(-114.345703125,39.436192999314095))
geojson_json(poly, geometry = "polygon", pretty=TRUE)

# Lists
## 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_json(vecs, geometry="polygon", pretty=TRUE)

## from a named list
mylist <- list(list(latitude=30, longitude=120, marker="red"),
               list(latitude=30, longitude=130, marker="blue"))
geojson_json(mylist, lat='latitude', lon='longitude')

# From a data.frame to points
geojson_json(us_cities[1:2,], lat='lat', lon='long', pretty=TRUE)
geojson_json(us_cities[1:2,], lat='lat', lon='long',
   type="GeometryCollection", pretty=TRUE)

# from data.frame to polygons
head(states)
## make list for input to e.g., rMaps
geojson_json(states[1:351, ], lat='lat', lon='long', geometry="polygon", group='group')

# from a geo_list
a <- geojson_list(us_cities[1:2,], lat='lat', lon='long')
geojson_json(a)

# sp classes

## 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_json(sp_poly)
geojson_json(sp_poly, pretty=TRUE)

## Another SpatialPolygons
library("sp")
library("rgeos")
pt <- SpatialPoints(coordinates(list(x = 0, y = 0)), CRS("+proj=longlat +datum=WGS84"))
## transfrom to web mercator becuase geos needs project coords
crs <- gsub("\n", "", paste0("+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x_0=0.0
   +y_0=0 +k=1.0 +units=m +nadgrids=@null +wktext +no_defs", collapse = ""))
pt <- spTransform(pt, CRS(crs))
## buffer
pt <- gBuffer(pt, width = 100)
pt <- spTransform(pt, CRS("+proj=longlat +datum=WGS84"))
geojson_json(pt)

## data.frame to geojson
geojson_write(us_cities[1:2,], lat='lat', lon='long') %>% as.json

# From SpatialPoints class
x <- c(1,2,3,4,5)
y <- c(3,2,5,1,4)
s <- SpatialPoints(cbind(x,y))
geojson_json(s)

## From SpatialPointsDataFrame class
s <- SpatialPointsDataFrame(cbind(x,y), mtcars[1:5,])
geojson_json(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_json(sl1)
geojson_json(sl12)

## 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_json(sldf)
geojson_json(sldf, pretty=TRUE)

## From SpatialGrid
x <- GridTopology(c(0,0), c(1,1), c(5,5))
y <- SpatialGrid(x)
geojson_json(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_json(sgdf)

# From SpatialRings
library("rgeos")
r1 <- Ring(cbind(x=c(1,1,2,2,1), y=c(1,2,2,1,1)), ID="1")
r2 <- Ring(cbind(x=c(1,1,2,2,1), y=c(1,2,2,1,1)), ID="2")
r1r2 <- SpatialRings(list(r1, r2))
geojson_json(r1r2)

# From SpatialRingsDataFrame
dat <- data.frame(id = c(1,2), value = 3:4)
r1r2df <- SpatialRingsDataFrame(r1r2, data = dat)
geojson_json(r1r2df)

# From SpatialPixels
library("sp")
pixels <- suppressWarnings(SpatialPixels(SpatialPoints(us_cities[c("long", "lat")])))
summary(pixels)
geojson_json(pixels)

# From SpatialPixelsDataFrame
library("sp")
pixelsdf <- suppressWarnings(
 SpatialPixelsDataFrame(points = canada_cities[c("long", "lat")], data = canada_cities)
)
geojson_json(pixelsdf)

# From SpatialCollections
library("sp")
library("rgeos")
pts <- SpatialPoints(cbind(c(1,2,3,4,5), c(3,2,5,1,4)))
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")
poly <- SpatialPolygons(list(poly1, poly2), 1:2)
dat <- SpatialCollections(pts, polygons = poly)
geojson_json(dat)

## Pretty print a json string
geojson_json(c(-99.74,32.45))
geojson_json(c(-99.74,32.45)) %>% pretty

## End(Not run)

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