In ropensci/lawn: Client for 'Turfjs' for 'Geospatial' Analysis

library("knitr")
hook_output <- knitr::knit_hooks$get("output")
knitr::knit_hooks$set(output = function(x, options) {
   lines <- options$output.lines
   if (is.null(lines)) {
     return(hook_output(x, options))  # pass to default hook
   }
   x <- unlist(strsplit(x, "\n"))
   more <- "..."
   if (length(lines)==1) {        # first n lines
     if (length(x) > lines) {
       # truncate the output, but add ....
       x <- c(head(x, lines), more)
     }
   } else {
     x <- c(if (abs(lines[1])>1) more else NULL,
            x[lines],
            if (length(x)>lines[abs(length(lines))]) more else NULL
           )
   }
   # paste these lines together
   x <- paste(c(x, ""), collapse = "\n")
   hook_output(x, options)
 })

knitr::opts_chunk$set(
  comment = "#>",
  collapse = TRUE,
  warning = FALSE,
  message = FALSE
)

lawn is an R wrapper for the Javascript library turf.js for advanced geospatial analysis. In addition, we have a few functions to interface with the geojson-random Javascript library.

lawn includes traditional spatial operations, helper functions for creating GeoJSON data, and data classification and statistics tools.

There is an additional helper function (see view()) in this package to help visualize data with interactive maps via the leaflet package (https://github.com/rstudio/leaflet). Note that leaflet is not required to install lawn - it's in Suggests, not Imports or Depends.

Install

If installing leaflet

devtools::install_github("rstudio/leaflet")

Stable lawn version from CRAN

install.packages("lawn")

Or, the development version from Github

devtools::install_github("ropensci/lawn")

library("lawn")

Make some geojson data

Point

lawn_point(c(-74.5, 40))

Polygon

rings <- list(list(
  c(-2.275543, 53.464547),
  c(-2.275543, 53.489271),
  c(-2.215118, 53.489271),
  c(-2.215118, 53.464547),
  c(-2.275543, 53.464547)
))
lawn_polygon(rings)

count

Count number of points within polygons

lawn_count(polygons = lawn_data$polygons_count, points = lawn_data$points_count, "population")

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, 
             in_field = 'population')

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 (default output: km)

lawn_distance(from, to)

random set of points

lawn_random(n = 2)

lawn_random(n = 5)

random features with geojson-random

Positions

gr_position()

Points

gr_point(2)

Polygons

gr_polygon(n = 1, vertices = 5, max_radial_length = 5)

sample from a FeatureCollection

dat <- lawn_data$points_average
lawn_sample(dat, 1)

lawn_sample(dat, 2)

lawn_sample(dat, 3)

extent

lawn_extent(lawn_data$points_average)

within

lawn_within(lawn_data$points_within, lawn_data$polygons_within)

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")

lint input geojson

For most functions, you can lint your input geojson data to make sure it is proper geojson. We use the javascript library geojsonhint. See the lint parameter where available.

Good GeoJSON

dat <- '{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {
        "population": 200
      },
      "geometry": {
        "type": "Point",
        "coordinates": [10.724029, 59.926807]
      }
    },
      {
      "type": "Feature",
      "properties": {
        "population": 600
      },
      "geometry": {
        "type": "Point",
        "coordinates": [10.715789, 59.904778]
      }
    }
  ]
}'
lawn_extent(dat)

Bad GeoJSON

dat <- '{
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "properties": {
        "population": 200
      },
      "geometry": {
        "type": "Point"
      }
    },
      {
      "type": "Feature",
      "properties": {
        "population": 600
      },
      "geometry": {
        "type": "Point",
        "coordinates": [10.715789, 59.904778]
      }
    }
  ]
}'
lawn_extent(dat, lint = TRUE)

#> Error: Line 1 - "coordinates" member required

view

lawn includes a tiny helper function for visualizing geojson.

view(lawn_data$points_average)

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

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

ropensci/lawn documentation built on May 18, 2022, 9:58 a.m.