https://www.openstreetmap.org/images/osm_logo.png" alt="" /> OpenStreetMap (openstreetmap.org) is a global collaborative mapping project, which offers maps and map data released with an open license, encouraging free re-use and re-distribution. The data is created by a large community of volunteers who use a variety of simple on-the-ground surveying techniques, and wiki-syle editing tools to collaborate as they create the maps, in a process which is open to everyone. The project originated in London, and an active community of mappers and developers are based here. Mapping work in London is ongoing (and you can help!) but the coverage is already good enough for many uses.

Browse the map of London on OpenStreetMap.org

Downloads:

The whole of England updated daily:

• england.osm.bz2 ~185M - .osm formatted raw XML data (compressed)
• england.shp.zip ~156M - ESRI shapefiles

For more details of downloads available from OpenStreetMap, including downloading the whole planet, see 'planet.osm' on the wiki.

Data access APIs:

Download small areas of the map by bounding-box. For example this URL requests the data around Trafalgar Square:
http://api.openstreetmap.org/api/0.6/map?bbox=-0.13062,51.5065,-0.12557,51.50969

Data filtered by "tag". For example this URL returns all elements in London tagged shop=supermarket:
http://www.informationfreeway.org/api/0.6/*[shop=supermarket][bbox=-0.48,51.30,0.21,51.70]

The .osm format

The format of the data is a raw XML represention of all the elements making up the map. OpenStreetMap is composed of interconnected "nodes" and "ways" (and sometimes "relations") each with a set of name=value pairs called "tags". These classify and describe properties of the elements, and ultimately influence how they get drawn on the map. To understand more about tags, and different ways of working with this data format refer to the following pages on the OpenStreetMap wiki.

• .osm - About the raw XML data format of OpenStreetMap
• Downloading data - More details of the API and extract download options
• Xapi - The extended api for filtering by tag
• Map Features - A list of tags, and what map features they represent
• Converting map data between formats - catalogue of tools for converting from .osm to other formats

Simple embedded maps

Rather than working with raw map data, you may prefer to embed maps from OpenStreetMap on your website with a simple bit of javascript. You can also present overlays of other data, in a manner very similar to working with google maps. In fact you can even use the google maps API to do this. See OSM on your own website for details and links to various javascript map libraries.

Help build the map!

The OpenStreetMap project aims to attract large numbers of contributors who all chip in a little bit to help build the map. Although the map editing tools take a little while to learn, they are designed to be as simple as possible, so that everyone can get involved. This project offers an exciting means of allowing local London communities to take ownership of their part of the map.

Read about how to Get Involved and see the London page for details of OpenStreetMap community events.

CANUE staff developed the Green Roads data set by combining street network files from Open Street Map 9OSM) (downloaded Nov 29, 2020) and annual average normalized difference vegetation index (NDVI) data from LandSat 8 circa 2016 from Google Earth Engine. OSM roads categorized as primary, secondary, tertiary, tertiary link, residential, unclassified and unknown were extracted from OSM, combined into a single file and clipped to urban areas. Urban areas were defined as all dissemination blocks classified as small population centres (population 1,000 to 29,999), medium population centres (population 30,000 to 99,999) or large population centres (population 100,000 or greater) in the 2016 Census. The urban roads layer was used to extract all LandSat 8 pixels with NDVI data (30m resolution). All extracted pixels with an NDVI value of 0.3 or greater, indicating green vegetation, were converted into points. Finally, the total number or points and the average NDVI value was calculated within buffers of 250m, 500m, 750m and 1000m of DMTI single-link postal codes from 2016.

This dataset was extracted from OpenStreetMap (OSM) across the geographic area of Australia on 02 December 2021. Its purpose is to display natural features as area (polygon) within Australia. Note, however, as this dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki. Please note: The original data for this dataset has been downloaded from Geofabrik on 02 December 2021. Due to changes in tagging, previous versions of OSM may not be comparable with this release.

This data was downloaded from OpenStreetMap (OSM) roads data for Wisconsin from the OpenStreetMap's GeoFabrik website: http://www.geofabrik.de/data/download.html and reprojected to WTM 83/91. Several attributes were added to facilitate use of the OSM data in DNR basemaps. DNR has made edits to this data to correct errors where known and to hide road features within DNR Managed Lands that are not public roadways.This dataset does not contain Interstate Highway, US Highways, or State Highways.To report errors in this dataset, contact Bill Ceelen at William.Ceelen@wisconsin.gov. Additional information about OSM is available on the GeoFabrik site: http://www.geofabrik.de/geofabrik/openstreetmap.html

Data provided by OSM and Geofabrik

Export des données disponibles dans la base de données Open Street map à partir de l'extraction réalisée de manière hebdomadaire par Geofabrik. Cette extraction peut être importée dans des outils du type Osmium, Osmosis, imposm, osm2pgsql, mkgmap ou dans des outils SIG de type ArcGis ou Quantis.

Il s'agit ici de l'extraction de la base de données collaborative produite par le projet OpenStreetMap. Cette base de données est extrêmement riche et principalement centrée sur l'activité humaine : routes, rues, chemins, points d'intérêts extrêmement variés (mairies, églises, services administratifs, points touristiques, commerces, etc.), etc. Le projet OpenStreetMap est en quelque sorte le wikipedia de la cartographie.

This dataset was extracted from OpenStreetMap (OSM) across the geographic area of Australia on 02 December 2021. Its purpose is to display Traffic-Related as an area (polygon) within Australia. Note, however, as this dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki. Please note: The original data for this dataset has been downloaded from Geofabrik on 02 December 2021. Due to changes in tagging, previous versions of OSM may not be comparable with this release.

Last update: August 20, 2024OverviewThis point data was generated and filtered from OpenStreetMap and is intended to represent places of interest in the state of Utah. These may include businesses, restaurants, places of worship, airports, parks, schools, event centers, apartment complexes, hotels, car dealerships…almost anything that you can find in OpenStreetMap (OSM). There are over 23,000 features in the original dataset (March 2022) and users can directly contribute to it through openstreetmap.org. This data is updated approximately once every month and will likely continue to grow over time with user activity.Data SourcesThe original bulk set of OSM data for the state of Utah is downloaded from Geofabrik: https://download.geofabrik.de/north-america/us/utah-latest-free.shp.zipAdditional attributes for the Utah features are gathered via the Overpass API using the following query: https://overpass-turbo.eu/s/1geRData Creation ProcessThe Open Source Places layer is created by a Python script that pulls statewide OSM data from a nightly archive provided by Geofabrik (https://www.geofabrik.de/data/download.html). The archive data contains nearly 20 shapefiles, some that are relevant to this dataset and some that aren't. The Open Source Places layer is built by filtering the polygon and point data in those shapefiles down to a single point feature class with specific categories and attributes that UGRC determines would be of widest interest. The polygon features (buildings, areas, complexes, etc.) are converted to points using an internal centroid. Spatial filtering is done as the data from multiple shapefiles is combined into a single layer to minimize the occurrence of duplicate features. (For example, a restaurant can be represented in OSM as both a point of interest and as a building polygon. The spatial filtering helps reduce the chances that both of these features are present in the final dataset.) Additional de-duplication is performed by using the 'block_id' field as a spatial index, to ensure that no two features of the same name exist within a census block. Then, additional fields are created and assigned from UGRC's SGID data (county, city, zip, nearby address, etc.) via point-in-polygon and near analyses. A numeric check is done on the 'name' field to remove features where the name is less than 3 characters long or more than 50% numeric characters. This eliminates several features derived from the buildings layer where the 'name' is simply an apartment complex building number (ex: 3A) or house number (ex: 1612). Finally, additional attributes (osm_addr, opening_hours, phone, website, cuisine, etc.) are pulled from the Overpass API (https://wiki.openstreetmap.org/wiki/Overpass_API) and joined to the filtered data using the 'osm_id' field as the join key.Field Descriptionsaddr_dist - the distance (m) to the nearest UGRC address point within 25 mosm_id - the feature ID in the OSM databasecategory - the feature's data class based on the 4-digit code and tags in the OSM databasename - the name of the feature in the OSM databasecounty - the county the feature is located in (assigned from UGRC's county boundaries)city - the city the feature is located in (assigned from UGRC's municipal boundaries)zip - the zip code of the feature (assigned from UGRC's approximation of zip code boundaries)block_id - the census block the feature is located in (assigned from UGRC's census block boundaries)ugrc_addr - the nearest address (within 25 m) from the UGRC address point databasedisclaimer - a note from UGRC about the ugrc_near_addr fieldlon - the approximate longitude of the feature, calculated in WGS84 EPSG:4326lat - the approximate latitude of the feature, calculated in WGS84 EPSG:4326amenity - the amenity available at the feature (if applicable), often similar to the categorycuisine - the type of food available (if applicable), multiple types are separated by semicolons (;)tourism - the type of tourist location, if applicable (zoo, viewpoint, hotel, attraction, etc.)shop - the type of shop, if applicablewebsite - the feature's website in the OSM database, if availablephone - the feature's phone number(s) in the OSM database, if availableopen_hours - the feature's operating hours in the OSM database, if availableosm_addr - the feature's address in the OSM database, if availableMore information can be found on the UGRC data page for this layer:https://gis.utah.gov/data/society/open-source-places/

This road network dataset was created from data extracted from OpenStreetMap (OSM) across the geographic area of Australia on 05 August 2020. Its purpose is to represent motor-vehicle traversable public roads within Australia. Note, however, as the original dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. This road network has been topologically corrected for the purposes of network analysis for motor vehicles. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki. Please note: The original data for this dataset has been downloaded from Geofabrik on 05 August 2020. AURIN has filtered the original data and omitted features to present the topologically correct, motor-vehicle traversable road network.

Twelve maps of continental Europe indicating the protected nature area status in 2019 according to Natura 2000 and the International Union for Conservation of Nature (IUCN). The IUCN status was extracted from crowdsourced data obtained from OpenStreetMap through geofabrik.de.

This dataset contains:

3 raster maps representing Natura 2000 protection status (A, B and C), named Natura2000_[status].tif

8 raster maps representing OSM-derived IUCN protection status (1a, 1b, 2, 3, 4, 5, 6, and 'other'), named OSM_IUCN_[status].tif

1 aggregated map (adm_protected.area_natura2000.osm_p_30m_0..0cm_2019..2021_eumap_epsg3035_v0.1) where each of the 11 protection statuses, as well as pixels where multiple statuses apply, are assigned a unique value. This map can also be accessed interactively at maps.opendatascience.eu.

All files are provided as Cloud Optimized GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files for the aggregated raster are provided in both SLD and QML format.

This dataset was extracted from OpenStreetMap (OSM) across the geographic area of Australia on 02 December 2021. Its purpose is to display Places of Worship as an area (polygon) within Australia. Note, however, as this dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki. Please note: The original data for this dataset has been downloaded from Geofabrik on 02 December 2021. Due to changes in tagging, previous versions of OSM may not be comparable with this release.

This point dataset was extracted from OpenStreetMap (OSM) across the geographic area of Australia on 05 August 2020. Its purpose is to display points or nodes within Australia. Note, however, as …Show full descriptionThis point dataset was extracted from OpenStreetMap (OSM) across the geographic area of Australia on 05 August 2020. Its purpose is to display points or nodes within Australia. Note, however, as this dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki. Please note: The original data for this dataset has been downloaded from Geofabrik on 05 August 2020. Due to changes in tagging, previous versions of OSM may not be comparable with this release. Copyright attribution: OpenStreetMap, (2020): ; accessed from AURIN on 12/3/2020. Licence type: Open Data Commons Open Database License (ODbL) 1.0

This dataset provides a compilation of power plants in Madagascar based on data extracted from Open Street Map data (© OpenStreetMap contributors and Geofabrik GmbH), Artelia Group and Jirama.

This dataset was extracted from OpenStreetMap (OSM) across the geographic area of Australia on 02 December 2021. Its purpose is to display Waterways as lines within Australia. Note, however, as this dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki. Please note: The original data for this dataset has been downloaded from Geofabrik on 02 December 2021. Due to changes in tagging, previous versions of OSM may not be comparable with this release.

OSM data (WMS) on the following topics: Pharmacies, borrow instead of buy, bookcases, libraries, container locations, fire brigade, police, farm shops, parking ticket machines, second hand, repair yourself, playgrounds, gas stations, on the way to replenish drinking water, unpackaged shopping, recycling yards, eco-model regions

Source OSM data: https://download.geofabrik.de/europe/germany/nordrhein-westfalen.html, Area extension: NRW, © OpenStreetMap contributors (see https://www.openstreetmap.org/copyright)

This point of interests dataset was extracted from OpenStreetMap (OSM) across the geographic area of Australia on 05 August 2020. Its purpose is to display points within Australia which people may find of interest, this is not limited to major landmarks and include simple amenities. Note, however, as this dataset is built by a community of mappers, there is no guarantee of its spatial or attribute accuracy. Use at your own risk. For more information about the map features represented in this dataset (including their attributes), refer to the OpenStreetMap Wiki and the Points of Interest. Please note: The original data for this dataset has been downloaded from Geofabrik on 05 August 2020.

The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products of the Scotts Creek Watershed in Lake County, California, using National Agriculture Imagery Program (NAIP) imagery from 2022 and Open Street Map (OSM) from 2019. The imagery was downloaded from United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS) Geospatial Data Gateway (https://datagateway.nrcs.usda.gov/) and Geofabrik GmbH - Open Street Map (https://www.geofabrik.de/geofabrik/openstreetmap.html), respectively. An updated trail map for the Upper Scotts Creek Watershed, including the BLM Recreational Area, was created to estimate trail densities in the watershed. A preview image of the roads and trail maps is attached to this data release (see UpperScottsCreek_Roads_and_Trails_Map_2022_USGS2022_CC0.png).

OpenStreetMap (OSM) is a collaborative project to create a free editable geographic database of the world. The geodata underlying the maps is considered the primary output of the OSM project. The creation and growth of OSM has been motivated by restrictions on use or availability of map data across much of the world, and the advent of inexpensive portable satellite navigation devices. EMODnet bathymetry considers OSM to be the best source for land data to complement the marine environment and to allow easier navigation in the data portal. OpenStreetMap is a free and noncommercial project; everyone can just download OpenStreetMap data free of charge and process it. However EMODnet Bathymetry requires a tailored rendering of OpenStreetMap data as in all standard available visualisations the world oceans are obscured by water features which have no use in a marine environment. In addition, EMODnet requires a non-projected rendering with no land use which is not the OSM render default. The OSM rendering is provided to EMODnet by the German company Geofabrik (www.geofabrik.de).

This dataset was developed by KTH-dESA. It contains power substations in Benin based on data extracted from Open Street Map data (© OpenStreetMap contributors and Geofabrik GmbH)

This dataset shows roads in Chad from an OSM data pull published by Geofabrik on 4/27/2016.