OpenStreetMap Data for Urban Planning

OpenStreetMap is the world's largest open map, created by a community of 10 million mappers. As of 2026, OSM contains over 8 billion elements: 600+ million buildings, 70+ million kilometers of roads, and 150+ million points of interest. This data is freely available and actively used in urban planning and territorial development.

Why OSM for Urban Planning

Data Currency

OSM is updated daily by thousands of volunteers. In major cities (Moscow, Berlin, New York, Tokyo), changes appear within days of real events: new buildings, road closures, store openings. Commercial maps (Google Maps, Apple Maps) update less frequently and don't provide source data for analysis.

Open License

OSM data is distributed under the ODbL (Open Database License). It can be used for commercial and government projects, modified, and processed. The only requirement is attribution. For urban planning projects, this means: no licensing fees, no user limits, no vendor lock-in.

Detail Level

OSM contains attributes absent from commercial maps: building floor counts, roof material, road surface type, tree age, light pole height. For urban analysis, this detail is critical.

Global Coverage

OSM covers 195 countries. A unified data schema enables cross-city comparisons: building density of Moscow vs Barcelona, park provision of Vienna vs Singapore, walkability of Copenhagen vs Shanghai.

OSM Data Types for Urban Planning

Buildings

OSM contains building footprints with attributes:

• building — type (residential, commercial, industrial, school, hospital).
• building:levels — floor count. Enables FAR calculation, housing density, territory potential assessment.
• building:material — wall material (brick, concrete, wood).
• height — height in meters (for 3D modeling).
• start_date — construction year. Housing stock age analysis.

Applications: FAR (Floor Area Ratio) calculation, housing typology analysis, seismic vulnerability assessment, solar access modeling.

Roads (Highways)

The OSM road network is classified into 15+ types:

• motorway — highways.
• trunk, primary, secondary — arterial roads.
• tertiary — district roads.
• residential — residential streets.
• cycleway — bike paths.
• footway, pedestrian — pedestrian paths.

Attributes: lane count (lanes), speed limit (maxspeed), surface material (surface), sidewalk presence (sidewalk), lighting (lit).

Applications: traffic flow modeling, capacity assessment, pedestrian connectivity analysis, cycling infrastructure planning.

Points of Interest (POI)

150+ categories of infrastructure facilities:

• Education: schools, kindergartens, universities.
• Healthcare: hospitals, clinics, pharmacies.
• Commerce: shops, malls, markets.
• Transport: bus stops, metro stations, parking.
• Recreation: restaurants, cafes, sports facilities, cultural institutions.

Applications: infrastructure provision analysis, service accessibility calculation, walkability assessment (15-minute city concept).

Green Areas

Parks, forests, gardens, grasslands, water features — all with area, name, and functional designation.

Applications: green space provision calculation (m2 per resident, WHO standard — 9 m2), ecological framework analysis, recreational zone planning.

Public Transport

Routes (bus, trolleybus, tram, metro), stops with route assignments, stations.

Applications: transit accessibility analysis, route network optimization, territory coverage assessment.

Quantitative Territory Analysis

Walk Score — Walkability (0-100)

Walk Score evaluates how pedestrian-friendly an area is based on distance to nearest infrastructure:

• 90-100 (Walker's Paradise): all daily needs within walking distance.
• 70-89 (Very Walkable): most errands can be done on foot.
• 50-69 (Somewhat Walkable): some amenities within walking distance.
• 25-49 (Car-Dependent): most trips require a car.
• 0-24 (Very Car-Dependent): almost all trips by car.

Green Score — Green Space Provision (0-100)

Evaluates territory green space provision: park/forest/garden area within 500m and 1km, green-to-total area ratio, diversity of green space types, distance to nearest park over 1 hectare.

Transit Score — Transit Accessibility (0-100)

Evaluates public transit service level: distance to nearest stops, route count through the area, service frequency, transport mode diversity.

Safety Score — Infrastructure Safety (0-100)

Evaluates area safety based on infrastructure data: road and pedestrian path lighting, sidewalk presence, police station proximity, fire stations and ambulance stations, pedestrian crossings on arterial roads.

Real-World Project Examples

Territory Zoning

OSM data enables functional zoning: identifying residential, commercial, industrial, and recreational zones. Analysis of landuse tags combined with actual building use provides an accurate picture.

Transport Accessibility

Building isochrones (equal accessibility zones) from metro stations, hospitals, schools. OSM contains the complete road network with classification — from highways to pedestrian paths — enabling calculation of walking, cycling, and driving times.

Building Density

FAR (Floor Area Ratio) calculation by block: total building floor area / block area. OSM provides building footprints and floor counts — sufficient for baseline calculation.

Pedestrian Network Analysis

The pedestrian path graph (footway, path, pedestrian, steps) enables connectivity assessment. Gaps in the pedestrian network indicate potential locations for new crossings, sidewalks, and pedestrian bridges.

Analysis Tools on osm2cdr.ru

The service provides not only map export but also geo-analysis tools:

• Walk Score, Green Score, Transit Score, Safety Score — automatic calculation for any point or area.
• Building density — FAR and buildings-per-hectare calculation.
• Infrastructure provision — counting schools, hospitals, shops, stops within a given radius.
• Export to GIS formats — GeoJSON, Shapefile, GeoPackage, KML for further analysis in QGIS or ArcGIS.

139 geo-analysis tools are available via API and web interface.

OSM Data Limitations

When using OSM for urban planning, consider:

Uneven coverage. Major cities are mapped in detail (>95% of buildings), rural areas much less so (30-50%). Verify data completeness for your area before use.

Coordinate accuracy. Typical OSM accuracy is 1-3 meters in cities (based on satellite imagery), 5-10 meters in rural areas. Insufficient for cadastral purposes, but adequate for urban analysis.

Attribute completeness. Not all buildings have floor counts, not all roads have lane counts. On average in major cities: floor counts are specified for 40-60% of buildings, lane counts for 50-70% of roads.

Legal status. OSM is not a legal document. For official urban planning decisions, OSM data must be verified against cadastral maps and zoning regulations.

City Examples

Moscow

OSM contains 500,000+ Moscow buildings with footprints and attributes. 85% of buildings have floor count data. Road network coverage is 98%. 15,000+ public transport stops. Data updated daily by 200+ active mappers.

Berlin

340,000+ buildings, detailed cycling infrastructure (2,000+ km of bike paths), complete public transit network (U-Bahn, S-Bahn, trams, buses). Excellent base for sustainable mobility analysis.

Barcelona

280,000+ buildings, including superblocks (superilles) with detailed pedestrian zone mapping. The unique Cerda grid is fully represented in OSM.

Conclusion

OpenStreetMap data is a powerful free resource for urban planning. 600+ million buildings, 70+ million kilometers of roads, 150+ million POIs — all available for download, analysis, and use in projects. Quantitative metrics (Walk Score, Green Score, Transit Score) convert subjective territory assessments into objective numbers. Export to GIS formats via osm2cdr.ru enables integrating OSM data into any workflow: from QGIS and ArcGIS to AutoCAD and BIM systems.