lawn

lawn is an R wrapper for the Javascript library turf.js. In addition, we have a few functions to interface with the geojson-random and geojsonhint Javascript libraries, for generating random GeoJSON objects and linting GeoJSON, respectively.

Install

The latest release of lawn is available from CRAN. To install:

install.packages("lawn")

To install the development version:

install.packages("devtools")
devtools::install_github("ropensci/lawn")

library("lawn")

count

Count number of points within polygons

lawn_count(polygons = lawn_data$polygons_count, points = lawn_data$points_count)
#> <FeatureCollection>
#>   Bounding box: -112.1 46.6 -112.0 46.6
#>   No. features: 2
#>   No. points: 20
#>   Properties: NULL

average

Average value of a field for a set of points within a set of polygons

lawn_average(polygons = lawn_data$polygons_average, points = lawn_data$points_average, 'population')
#> <FeatureCollection>
#>   Bounding box: 10.7 59.9 10.9 59.9
#>   No. features: 2
#>   No. points: 20
#>   Properties: NULL

distance

Define two points

from <- '{
 "type": "Feature",
 "properties": {},
 "geometry": {
   "type": "Point",
   "coordinates": [-75.343, 39.984]
 }
}'
to <- '{
  "type": "Feature",
  "properties": {},
  "geometry": {
    "type": "Point",
    "coordinates": [-75.534, 39.123]
  }
}'

Calculate distance, default units is kilometers (km)

lawn_distance(from, to)
#> [1] 97.15958

random set of points

lawn_random(n = 2)
#> <FeatureCollection>
#>   Bounding box: -60.9 43.4 59.9 57.9
#>   No. features: 2
#>   No. points: 4
#>   Properties: NULL

lawn_random(n = 5)
#> <FeatureCollection>
#>   Bounding box: -137.6 -77.2 167.4 85.8
#>   No. features: 5
#>   No. points: 10
#>   Properties: NULL

random features with geojson-random

Points

gr_point(2)
#> <FeatureCollection>
#>   Bounding box: -80.6 71.6 -60.2 88.1
#>   No. features: 2
#>   No. points: 4
#>   Properties: NULL

Positions

gr_position()
#> [1] 24.779369  6.632737

Polygons

gr_polygon(n = 1, vertices = 5, max_radial_length = 5)
#> <FeatureCollection>
#>   Bounding box: 129.8 55.9 136.0 59.8
#>   No. features: 1
#>   No. points: 12
#>   Properties: NULL

sample from a FeatureCollection

dat <- lawn_data$points_average
lawn_sample(dat, 1)
#> <FeatureCollection>
#>   Bounding box: 10.8 59.9 10.8 59.9
#>   No. features: 1
#>   No. points: 2
#>   Properties: NULL

lawn_sample(dat, 2)
#> <FeatureCollection>
#>   Bounding box: 10.7 59.9 10.8 59.9
#>   No. features: 2
#>   No. points: 4
#>   Properties: NULL

lawn_sample(dat, 3)
#> <FeatureCollection>
#>   Bounding box: 10.7 59.9 10.8 59.9
#>   No. features: 3
#>   No. points: 6
#>   Properties: NULL

extent

lawn_extent(lawn_data$points_average)
#> [1] 10.71579 59.90478 10.80643 59.93162

within

lawn_within(lawn_data$points_within, lawn_data$polygons_within)
#> <FeatureCollection>
#>   Bounding box: -46.6 -23.6 -46.6 -23.6
#>   No. features: 2
#>   No. points: 4
#>   Properties: NULL

buffer

dat <- '{
 "type": "Feature",
 "properties": {},
 "geometry": {
     "type": "Polygon",
     "coordinates": [[
       [-112.072391,46.586591],
       [-112.072391,46.61761],
       [-112.028102,46.61761],
       [-112.028102,46.586591],
       [-112.072391,46.586591]
     ]]
   }
}'
lawn_buffer(dat, 1, "miles")
#> <FeatureCollection>
#>   Bounding box: -112.1 46.6 -112.0 46.6
#>   No. features: 1
#>   No. points: 74
#>   Properties: NULL

view

lawn includes a tiny helper function for visualizing geojson.

view(lawn_data$points_average)

Or during process of manipulating geojson, view at mostly any time.

Here, we sample at random two points from the same dataset just viewed.

lawn_sample(lawn_data$points_average, 2) %>% view()

Meta

• Please report any issues or bugs.
• License: MIT
• Get citation information for lawn in R doing citation(package = 'lawn')
• 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.