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

install.packages("lawn")

development version

remotes::install_github("ropensci/lawn")

library("lawn")

count

Count number of points within polygons

lawn_count(lawn_data$polygons_count, lawn_data$points_count, 'population')
#> <FeatureCollection>
#>   Bounding box: -112.1 46.6 -112.0 46.6
#>   No. features: 2
#>   No. points: 20
#>   Properties: 
#>     values count
#> 1 200, 600     2
#> 2              0

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: 
#>          values average
#> 1 200, 600, 100     300
#> 2      200, 300     250

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: -74.5 -70.3 11.8 -9.1
#>   No. features: 2
#>   No. points: 4
#>   Properties: NULL

lawn_random(n = 5)
#> <FeatureCollection>
#>   Bounding box: -171.4 -89.8 127.3 84.3
#>   No. features: 5
#>   No. points: 10
#>   Properties: NULL

random features with geojson-random

Points

gr_point(2)
#> <FeatureCollection>
#>   Bounding box: -29.6 -75.5 152.4 57.4
#>   No. features: 2
#>   No. points: 4
#>   Properties: NULL

Positions

gr_position()
#> [1] 100.69716  38.23048

Polygons

gr_polygon(n = 1, vertices = 5, max_radial_length = 5)
#> <FeatureCollection>
#>   Bounding box: 152.6 -0.1 158.6 7.0
#>   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: 
#>   population
#> 1        200

lawn_sample(dat, 2)
#> <FeatureCollection>
#>   Bounding box: 10.7 59.9 10.8 59.9
#>   No. features: 2
#>   No. points: 4
#>   Properties: 
#>   population
#> 1        200
#> 2        200

lawn_sample(dat, 3)
#> <FeatureCollection>
#>   Bounding box: 10.7 59.9 10.8 59.9
#>   No. features: 3
#>   No. points: 6
#>   Properties: 
#>   population
#> 1        300
#> 2        600
#> 3        200

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")
#> <Feature>
#>   Type: Polygon
#>   Bounding box: -112.1 46.6 -112.0 46.6
#>   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()

Contributors

• Scott Chamberlain
• Jeff Hollister
• Thanh Lê

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.

Additional disclaimer

Portions of this code have been contributed by Jeff Hollister, US EPA. As such, that code is subjec to the following disclaimer: https://www.epa.gov/home/github-contribution-disclaimer