OpenStreetMap road network parser

Generate equidistant points along urban area road network

This repo. contains code + a set of scripts for extracting equidistant points for cities/urban areas in a national road network. Specifically, for each road within a city, a set of points are generated at equal distances along with the associated heading/bearing for each point. The points/bearings are then output to a CSV.

This is part of a larger project which uses these sample points and associated bearings to query Google street view API for all images on the left and right hand side of a road network. The sample points may be useful as inputs into other projects or may be used in isolation to derive city specific geospatial features. For example, we have found that the distribution of sample point bearings for most UK cities is biased toward North, East, South, West and not uniform:

This could be related to historical relationships with neighboring towns and is representative of the overall spatial layout of a town's road network. We plan to explore this idea/finding at a later date. For example, it may be interesting to compare this data with road safety: towns with a predominant East, West road orientation may exhibit higher occurrence of incidents with respect to traveling in the direction of a rising/setting sun.

Dependencies

osmium
nodejs, npm
osmtogeojson
geojsplit
json_pp

osmium

mkdir osmium ;cd osmium
git clone https://github.com/mapbox/protozero
git clone https://github.com/osmcode/libosmium
git clone https://github.com/osmcode/osmium-tool
cd osmium-tool
mkdir build ;cd build
cmake ..
make
sudo make install

geojsplit + osmtogeojson

sudo npm -g install geojsplit
sudo npm -g install osmtogeojson

Building

make

Running

The whole process can be executed by invoking the run.sh script.

./run.sh

This will perform the following steps:

Get ONS major towns and cities polygon data. data/area_geojson will download the 112 major towns and cities geojson data from ONS Geography portal, then extract each city into individual geojson files in data/area_geojson/split/.
Extract the road network for each city. extract_roads.sh will download the latest open street map data for Great Britain, extract the road network using osmium, and then for each city, extract the road network bounded by the city polygon obtained in step (1) and convert to geojson:

Generate sample points for each city. For each individual city road network in data/city_roads_geojson/ extracted in step (2), sample_points.sh will generate a set of 10 metre equidistant points along each road, storing the result in data/csv_output. For convenience, the resulting sample points are also aggregated into a single file data/csv_output/final/england_and_wales.csv.

Output

The result is a csv file for each city stored in data/csv_output/CITY_NAME.csv. For example:

osm_way_id	road_name	road_type	abutters	lanes	lighting	surface	speed_limit	sequence	area	latitude	longitude	bearing
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	40	Manchester	53.43965	-2.275101	170.17
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	41	Manchester	53.43957	-2.275076	170.17
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	42	Manchester	53.43948	-2.275051	170.17
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	43	Manchester	53.43939	-2.275026	170.17
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	44	Manchester	53.43931	-2.275001	170.17
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	45	Manchester	53.43922	-2.274976	170.17
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	46	Manchester	53.43913	-2.274951	170.17
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	47	Manchester	53.43905	-2.274925	170.17
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	48	Manchester	53.43896	-2.274897	158.42
way/4355028	Barlow Moor Road	secondary	retail	2	yes	asphalt	30	49	Manchester	53.43889	-2.274844	151.79

Where:

Column	Description
osm_way_id	Road network "Edge" id
road_name	Road name
road_type	Road network classification (see below)
sidewalk	Path on left,right?
abutters	Road features
lanes	Number of lanes
lighting	Road has lighting?
surface	Surface type
speed_limit	Speed limit
sequence	Sample point order
area	City
latitude	Latitude
longitude	Longitude
bearing	Heading (angle of line from previous to next point.)

Road network classifications

OSM label	UK Meaning
motorway	M- road
trunk	A- road
primary	A- non-primary
secondary	B- road
tertiary	Significant minor road (with road markings etc)
unclassified	Less significant road
residential	Residential road

Licence

Open Government license v3 OGL v3.