Map of cycling, walking and driving routes in R using r5r

path_tree_r5r.md

Creating a map of cycling, walking and driving routes in R

Quick reproducible example showing how to use the r5r package to estimate cycling, walking and driving routes in R.

Prepare R environment

options(java.parameters = "-Xmx4G")

library(r5r)
library(geobr)
library(sf)
library(ggplot2)
library(here)
library(osmextract)
library(magrittr)


# create subdirectories "data" and "img"
dir.create(here::here("data"))
dir.create(here::here("img"))

Download the data

# get OSM data
osmextract::oe_download(
  file_url = osmextract::oe_match("Curitiba, Brazil")[[1]],
  download_directory = here::here("data"), force_download = T)

# get city boundaries and city center
city <- 'Curitiba'
city_code <- lookup_muni(name_muni = city)
city_boundary <- read_municipality(code_muni = city_code$code_muni)
city_center <- read_municipal_seat() %>% subset(code_muni == city_code$code_muni)
city_center$id <- 'center'

# get sample of origins in city
set.seed(42)
origins <- st_sample(city_boundary, size = 2000) %>% st_sf()
origins$id <- 1:nrow(origins)

origins <- st_transform(origins, 4326)
city_center <- st_transform(city_center, 4326)

Routing analysis

# build network
r5r_core <- setup_r5(data_path = here::here("data"), verbose = FALSE)

# routing
df <- detailed_itineraries(r5r_core,
                           origins = origins,
                           destinations = city_center,
                           mode = 'bicycle',
                           departure_datetime = as.POSIXct("13-03-2019 14:00:00", format = "%d-%m-%Y %H:%M:%S"),
                           max_trip_duration = 1440,
                           shortest_path = T)

Plot

fig <- ggplot() +
        geom_sf(data = city_boundary, color='gray70', fill=NA) +
        geom_sf(data = df, color='red', alpha=.1, size=.3) +
        labs(title='Cycling in Curitiba',
             subtitle = '2000 routes to the city center',
             caption = 'Image by @UrbanDemog using r5r') +
        theme_void() +
        theme(plot.title = element_text(color = "gray20"),
              plot.subtitle = element_text(color = "gray40"),
              plot.caption = element_text(color = "gray")
              )

# save figure
ggsave(fig, file=here::here("img", "cycling.png"), 
       dpi=300, width = 14, height = 14, units = 'cm')