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Getting started with osmnxr

library(osmnxr)

What is osmnxr?

osmnxr is OSMnx for R: it downloads, models, analyzes and visualizes street networks from OpenStreetMap. The public API is tidyverse-friendly and returns sf objects; the heavy graph computation (routing, metrics, simplification) runs in a bundled Rust core.

The central object is the osm_graph: a pair of sf tables (nodes and edges) plus metadata.

A real network

The usual entry point is a place name, which downloads from OpenStreetMap:

g <- ox_graph_from_place("Olinda, Brazil", network_type = "drive")
g <- ox_simplify(g)

So this vignette runs offline, we load that exact network — the historic centre of Olinda, Brazil — from the copy bundled with the package:

g <- ox_example("olinda")
g
#> 
#> ── osm_graph ───────────────────────────────────────────────────────────────────
#> 498 nodes, 1191 edges
#> Network type: "unknown"
#> Simplified: FALSE
#> CRS: "WGS 84"
plot(g)

Network statistics

ox_basic_stats(g)
#> # A tibble: 1 × 7
#>   n_nodes n_edges total_length mean_length mean_out_degree self_loops circuity
#>     <int>   <int>        <dbl>       <dbl>           <dbl>      <int>    <dbl>
#> 1     498    1191       95484.        80.2            2.39          1     1.06

Routing

Snap coordinates to graph nodes, then compute the shortest path (Dijkstra, in Rust):

orig <- ox_nearest_nodes(g, x = -34.8553, y = -8.0089)
dest <- ox_nearest_nodes(g, x = -34.8505, y = -8.0125)
route <- ox_shortest_path(g, orig, dest)
length(route) # nodes along the route
#> [1] 8
route_xy <- sf::st_coordinates(g$nodes)[match(route, g$nodes$osmid), ]
plot(g, col = "grey80", lwd = 0.6)
lines(route_xy, col = "#b7410e", lwd = 3)

Where to next

No network needed at all? example_osm_graph() builds a synthetic grid for quick experiments.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.