Discover how OpenStreetMap powers urban planning and city development—building better communities through maps made by people like you.
As urban populations surge and cities struggle to keep pace—managing housing, infrastructure, and public services under mounting pressure—planners and policymakers need accurate, ground-level geographic data to make decisions that shape lives for generations. OpenStreetMap, with its open data and global community, fills critical urban mapping gaps in fast-growing and underrepresented cities across the world. Powered by volunteers and supported by civic organizations, OSM enables urban planners, local governments, and communities to design, develop, and advocate for cities that work for everyone.
OSMnx is a Python package developed by Geoff Boeing at USC that allows planners and researchers to download, model, and analyze street networks for any city in the world using OSM data. It is used for urban form analysis, walkability studies, accessibility modeling, and resilience assessments. It solves the challenge of making OSM street data easily accessible and analyzable for urban planning without writing extensive custom code.
This open-source QGIS and Python tool uses OSM pedestrian network and amenity data to measure how well a city conforms to the 15-minute city concept, where all essential services are reachable on foot within 15 minutes. It queries OSM for walkable streets and points of interest, calculates walking isochrones, and generates a scored walkability map for urban planners and policymakers.
The Know Your City 2.0 project by HOT and Slum Dwellers International uses OSM, drone imagery, and the HOT Tasking Manager to map building footprints in slum and informal urban settlements across cities in Africa, Asia, and Latin America. The data supports community-led urban upgrading, land tenure, and infrastructure planning in areas that are otherwise invisible on official maps.
Researchers developed a nationwide building classification dataset for the United States covering over 67 million buildings, using OSM building footprints and metadata as the primary data source. The dataset classifies buildings as residential or non-residential and supports urban planning applications including population estimation, energy use modeling, land use mapping, and digital twin construction.
A project from the Institute for Advanced Architecture of Catalonia uses OSM data to conduct spatial analysis of urban form across cities worldwide. Using the Grasshopper Elk plugin, OSM road networks, building footprints, and land use data are extracted and analyzed for computational urban design and city comparison studies, addressing challenges of access to consistent global urban datasets.
A/B Street turns OpenStreetMap road, lane, signal, parking, and transit-stop data into interactive traffic simulations. Citizens and planners can test street redesigns, bike lanes, bus priority, parking changes, and intersection edits, then compare how proposals affect drivers, cyclists, pedestrians, transit users, and neighborhood accessibility outcomes before implementation during public consultations.
An American Planning Association article highlights five open-source tools for multimodal urban planning, including the Overture Maps Foundation platform, which integrates OSM data with additional sources from Esri and TomTom. The article addresses the challenge that incomplete data and lack of affordable planning tools have hampered communities from identifying and analyzing multimodal network improvements.
Humanitarian OpenStreetMap Team (HOT) documents how Mexican communities use OSM to map streetlights and urban features. By integrating mapped roads, amenities, and green spaces into GIS, planners support local development, simulate urban growth, and identify priority areas for infrastructure and public-service improvements.
Birmingham City Council collaborated with the OpenStreetMap community to open up traffic sensor and road data. By publishing real-time sensor locations and mapping them in OSM, the council enabled open-source traffic modelling and predictive tools.
The Map Kibera project trained young residents of Kibera (Nairobi’s largest informal settlement) to create the first detailed map of their community on OpenStreetMap. They mapped roads, homes, clinics, water points, and even “black spots” where crimes occurred. This citizen map made Kibera visible to authorities and NGOs, one direct result was a new police post.
Ramani Huria (“Open Map” in Swahili) was a World Bank-funded community mapping project (2015–2020) in Dar es Salaam, Tanzania. Local university students and residents mapped thousands of buildings, roads, and drains in flood-prone wards using OSM. These open maps have strengthened the city’s flood planning.
The World Bank launched the Open Cities Project in November 2012 which used OpenStreetMap to create to create open data ecosystems that will facilitate innovative, data-driven urban planning and disaster., Open Cities has brought together stakeholders from government, donor agencies, the private sector, universities, and civil society groups to create usable information through community mapping techniques.
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