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stplanr is a package for sustainable transport planning with R.

It provides functions for solving common problems in transport planning and modelling, such as how to best get from point A to point B. The overall aim is to provide a reproducible, transparent and accessible toolkit to help people better understand transport systems and inform policy.

The initial work on the project was funded by the Department of Transport (DfT) as part of the development of the Propensity to Cycle Tool (PCT). The PCT uses origin-destination data as the basis of spatial analysis and modelling work to identify where bicycle paths are most needed. See the package vignette (e.g. via vignette("introducing-stplanr")) or an academic paper on the Propensity to Cycle Tool (PCT) for more information on how it can be used. This README gives some basics.

stplanr should be useful to researchers everywhere. The function route_graphhopper(), for example, works anywhere in the world using the graphhopper routing API and read_table_builder() reads-in Australian data. We welcome contributions that make transport research easier worldwide.

Key functions

Data frames representing flows between origins and destinations must be combined with geo-referenced zones or points to generate meaningful analyses and visualisations of 'flows' or origin-destination (OD) data. stplanr facilitates this with od2line(), which takes flow and geographical data as inputs and outputs a SpatialLinesDataFrame. Some example data is provided in the package:

library(stplanr)
data(cents, flow)

Let's take a look at this data:

flow[1:3, 1:3] # typical form of flow data
#>        Area.of.residence Area.of.workplace All
#> 920573         E02002361         E02002361 109
#> 920575         E02002361         E02002363  38
#> 920578         E02002361         E02002367  10
cents[1:3,] # points representing origins and destinations
#> class       : SpatialPointsDataFrame 
#> features    : 3 
#> extent      : -1.546463, -1.511861, 53.8041, 53.81161  (xmin, xmax, ymin, ymax)
#> coord. ref. : +init=epsg:4326 +proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0 
#> variables   : 4
#> names       :  geo_code,  MSOA11NM, percent_fem,  avslope 
#> min values  : E02002382, Leeds 053,    0.408759, 2.284782 
#> max values  : E02002393, Leeds 064,    0.458721, 2.856563

These datasets can be combined as follows:

travel_network <- od2line(flow = flow, zones = cents)
w <- flow$All / max(flow$All) *10
plot(travel_network, lwd = w)

The package can also allocate flows to the road network, for example through a link to the CycleStreets.net API.

Route functions take lat/lon inputs:

trip <-
  route_cyclestreet(from = c(-1, 53), to = c(-1.1, 53), plan = "balanced")

and place names, found using the Google Map API:

if(!Sys.getenv("CYCLESTREET") == ""){
  trip <- route_cyclestreet("Bradford, UK", "Leeds, UK", plan = "balanced")
  plot(trip)
}

We can replicate this call to CycleStreets.net multiple times using line2route.

intrazone <- travel_network$Area.of.residence == travel_network$Area.of.workplace
travel_network <- travel_network[!intrazone,]
if(Sys.getenv("CYCLESTREET") == ""){
  t_routes = routes_fast
} else {
  t_routes <- line2route(travel_network)
}
plot(t_routes)

Another way to visualise this is with the leaflet package:

library(leaflet)
leaflet() %>% addTiles() %>% addPolylines(data = t_routes)

For more examples, example("line2route").

overline is a function which takes a series of route-allocated lines, splits them into unique segments and aggregates the values of overlapping lines. This can represent where there will be most traffic on the transport system, as illustrated below.

t_routes$All <- travel_network$All
rnet <- overline(sldf = t_routes, attrib = "All", fun = sum)

lwd <- rnet$All / mean(rnet$All)
plot(rnet, lwd = lwd)
points(cents)

Installation

To install the stable version, use:

install.packages("stplanr")

The development version can be installed using devtools:

# install.packages("devtools") # if not already installed
devtools::install_github("ropensci/stplanr")
library(stplanr)

stplanr depends on rgdal, which can be tricky to install.

Installing rgdal on Ubuntu and Mac

On Ubuntu rgdal can be installed with:

sudo apt-get install r-cran-rgdal

Using apt-get ensures the system dependencies, such as gdal are also installed.

On Mac, homebrew can install gdal. Full instructions are provided here.

Funtions, help and contributing

The current list of available functions can be seen with:

lsf.str("package:stplanr", all = TRUE)

To get internal help on a specific function, use the standard way.

?od2line

Dependencies

stplanr has many dependencies. These are designed to help make it fast, but may make it slow to install for the first time.

Its dependencies are plotted below using the minCRAN package:

dg <- miniCRAN::makeDepGraph("stplanr")
plot(dg)

Meta

  • Please report issues, feature requests and questions to the github issue tracker
  • License: MIT
  • Get citation information for stplanr in R doing citation(package = 'stplanr')
  • This project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

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Version

Install

install.packages('stplanr')

Monthly Downloads

1,315

Version

0.1.8

License

MIT + file LICENSE

Issues

21

Pull Requests

3

Stars

429

Forks

68

Maintainer

Robin Lovelace

Last Published

June 2nd, 2017

Functions in stplanr (0.1.8)

angle_diff

Calculate the angular difference between lines and a predefined bearing
api_pat

Retrieve personal access token.
calc_catchment

Calculate catchment area and associated summary statistics.
calc_catchment_sum

Calculate summary statistics for catchment area.
bb2poly

Convert a bounding box to a SpatialPolygonsDataFrame
bbox_scale

Scale a bounding box
calc_moving_catchment

Calculate summary statistics for all features independently.
buff_geo

Create a buffer of n metres for non-projected 'geographical' spatial data
ca_local

SpatialPointsDataFrame representing road traffic deaths
decode_gl

Decode Google polyline compressed string
destination_zones

example destinations data
dist_google

Return travel network distances and time using the Google Maps API
dl_stats19

Download Stats19 data
format_stats19_ve

Format UK 'Stats19' road traffic casualty data
gclip

Crops spatial object x to the bounding box of spatial object (or matrix) b
islines

Do the intersections between two geometries create lines?
l_poly

Line polygon
nearest_google

Generate nearest point on the route network of a point using the Google Maps API
nearest_osm

Generate nearest point on the route network of a point from OSRM locate service
od_aggregate

Aggregate OD data between polygon geometries
od_dist

Quickly calculate Euclidean distances of od pairs
read_stats19_ve

Import and format UK 'Stats19' road traffic casualty data
read_table_builder

Import and format Australian Bureau of Statistics (ABS) TableBuilder files
calc_network_catchment

Calculate catchment area and associated summary statistics using network.
gtfs2sldf

Import GTFS shapes and route data to SpatialLinesDataFrame.
is_linepoint

Identify lines that are points
line2df

Convert SpatialLinesDataFrame objects to a data.frame with from and to coords
line2points

Convert a SpatialLinesDataFrame to points
SpatialLinesNetwork-class

An S4 class representing a (typically) transport network
SpatialLinesNetwork

Create object of class SpatialLinesNetwork from SpatialLinesDataFrame
cents

SpatialPointsDataFrame of home locations for flow analysis.
crs_select_aeq

Select a custom projected CRS for the area of interest
gprojected

Perform GIS functions on a temporary, projected version of a spatial object
gsection

Function to split overlapping SpatialLines into segments
line_length

Calculate length of lines in geographic CRS
line_match

Match two sets of lines based on similarity
mapshape_available

Does the computer have mapshaper available?
n_vertices

Retrieve the number of vertices from a SpatialLines or SpatialPolygons object
overline

Convert series of overlapping lines into a route network
plot,SpatialLinesNetwork,ANY-method

Plot a SpatialLinesNetwork
nearest2spdf

Return SpatialPointsDataFrame with nearest street from OSRM nearest service
nearest_cyclestreets

Generate nearest point on the route network of a point using the CycleStreets.net
onewaygeo

Aggregate flows so they become non-directional (by geometry - the slow way)
onewayid

Aggregate ods so they become non-directional
lineLabels

Label SpatialLinesDataFrame objects
line_bearing

Find the bearing of straight lines
locate2spdf

Return SpatialPointsDataFrame with located points from OSRM locate service
mapshape

Simplify geometry of spatial objects with the mapshaper library
points2odf

Convert a series of points into a dataframe of origins and destinations
reproject

Reproject lat/long spatial object so that they are in units of 1m
route_cyclestreet

Plan a single route with CycleStreets.net
sp_aggregate

Aggregate SpatialPolygonsDataFrame to new geometry.
format_stats19_ac

Format UK 'Stats19' road traffic casualty data
format_stats19_ca

Format UK 'Stats19' road traffic casualty data
line_midpoint

Find the mid-point of lines
line_segment

Divide SpatialLines dataset into regular segments
find_network_nodes

Find graph node ID of closest node to given coordinates
flow

data frame of commuter flows
flow_dests

data frame of invented commuter flows with destinations in a different layer than the origins
flowlines

SpatialLinesDataFrame of commuter flows
sum_network_links

Summarise links from shortest paths data
sum_network_routes

Summarise shortest path between nodes on network
viaroute

Query OSRM service and return json string result
viaroute2sldf

Convert json result of OSRM routing query to SpatialLinesDataFrame
stplanr-package

stplanr: Sustainable Transport Planning with R
weightfield

Get or set weight field in SpatialLinesNetwork
writeGeoJSON

Write to geojson easily
points2flow

Convert a series of points into geographical flows
points2line

Convert a series of points, or a matrix of coordinates, into a line
toptail

Clip the first and last n metres of SpatialLines
toptail_buff

Clip the beginning and ends SpatialLines to the edge of SpatialPolygon borders
zones

SpatialPolygonsDataFrame of home locations for flow analysis.
quadrant

Split a spatial object into quadrants
route_graphhopper

Plan a route with the graphhopper routing engine
line2route

Convert straight SpatialLinesDataFrame from flow data into routes
line2routeRetry

Convert straight SpatialLinesDataFrame from flow data into routes retrying on connection (or other) intermittent failures
od_id_order

Generate ordered ids of OD pairs so lowest is always first
od_radiation

Function that estimates flow between points or zones using the radiation model
route_transportapi_public

Plan a single route with TransportAPI.com
routes_fast

SpatialLinesDataFrame of commuter flows on the travel network
toptailgs

Clip the first and last n metres of SpatialLines
update_line_geometry

Update line geometry
route_network

SpatialLinesDataFrame representing a route network
od2line

Convert flow data to SpatialLinesDataFrame
od2odf

Extract coordinates from OD data
read_stats19_ac

Import and format UK 'Stats19' road traffic casualty data
read_stats19_ca

Import and format UK 'Stats19' road traffic casualty data
routes_slow

SpatialLinesDataFrame of commuter flows on the travel network
sln2points

Generate spatial points representing nodes on a SpatialLinesNetwork
summary,SpatialLinesNetwork-method

Print a summary of a SpatialLinesNetwork
table2matrix

Return Matrix containing travel times between origins and destinations