be approaching Ordnance Survey (OS) data quality on UK road network (Haklay, 2010) • Focus on augmentation official datasets (Du et al., 2012) • OSM cycling data found to growing rapidly, outperforming Google Bicycling layer in many locations (Hochmair et al., 2012) • Intersects with wider debate about merits of Volunteered Geographic Information (VGI) (Goodchild, 2007)
Paths is a new data Theme depicting man-made path networks in urban Great Britain ... designed to work with OS MasterMap ITN’s established Road Network Theme.” http:/ /www.ordnancesurvey.co.uk /busin ess-and-government/help-and-support/products/urban-paths.html 1.5 Gb of data provided by OS under strict academic license
anything other than ArcMap (comes in hundreds of .gz files -> .mdb format) • Mostly walking paths: 98% are 'Footpath' • By distance, cycle paths constitute 4.3% of dataset: 2,500 km • Almost exclusively concentrated in urban areas • Very few attributes: Footpath, Cycle Path, Canal Path, Bridleway
format (<1 Gb) from Geofabrik • osmconvert used to convert to .o5m file type (15 Gb) • osmfilter extracted cycleways, bicycle=yes and cycle path relations, e.g.: – Osmfilter map.05m –keep=”highway=*” >ways.osm – Osmfilter map.05m –keep=”highway=cycleway” >cways.osm • Overpass API can be used to access data directly • .osm > .db sqlite database. Filtered tags w. QGIS.
Av. Length (m) Colour highway='cycl eway' 13.6 260 Black bicycle=... 6.3 390 Blue lcn='yes' 5.4 260 Red ncn='yes' 1.1 320 Green rcn='yes' 0.3 530 Yellow Total merge 24.6 280 - • ~80,000 multi-node lines • 1.5 Gb storage, including tags • 14 Mb shapefile (no attributes) • 879,062 nodes • ~30 mins to load on 4th gen i7 processor (in R)
Accessibility Unavailable to public, available for sale (price unknown) Freely accessible, provided skills Network size 2,500 km 13,600 km (just 'highway=cycleway') Coverage Very patchy, lacks continuity, only urban areas Worldwide but dependent on volunteer labour Attributes None Very wide range of attributes allowed
into GIS/CAD systems Integration of how public 'sees' infrastructure into public/private plans Huge opportunities for community engagement Example: Leeds-Bradford Cycle Superhighway Custom OSM map with Leaflet interface used Collection of opinions about proposed route Stopped short of encouraging altering vector data Field testing needed for full evaluation Use in CycleStreets.net for DfT project (current project)
Ordnance Survey for provision of cycle path data • Wider point: crowd sourced data as THE standard? • Encourages public participation • Plans for further analysis and publication: – Spatial comparisons where OSM/OS overlap – Framing as crowd-sourced data becoming mainstream – Aiming for 'public engagement' as well as academic outputs – E.g. Lovelace (2014), CycleStreets.net blog, CTC – Making OSM data accessibe (see next session!)
J., Hart, G., Leibovici, D., … Ware, M. (2012). Geospatial Information Integration for Authoritative and Crowd Sourced Road Vector Data. Transactions in GIS, 16(4), 455–476. doi:10.1111/j.1467- 9671.2012.01303.x • Goodchild, M. F. (2007). Citizens as sensors: the world of volunteered geography. GeoJournal, 69(4), 211–221. doi:10.1007/s10708-007-9111-y • Haklay, M. (2010). How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasets. Environment and Planning B: Planning and Design, 37(4), 682–703. doi:10.1068/b35097 • Hochmair, H., Ziestra, D., & Neis, P. (2012). Assessing the Completeness of Bicycle Trail and Designated Lane Features in OpenStreetMap for the United States and Europe, 1–21. • Lovelace, R. (2014). Harnessing open street map data with R and QGIS. EloGeo. Interested? Contact: [email protected]