An ARC GIS PRO shapefile mapping the turnpike roads in England and Wales for the 18th and early 19th century. The data includes details of the Turnpike Acts, years of operation, the quality of the road and the routes used by Mail coaches. The data forms the basis of the paper "Government, trusts, and the making of better roads in early nineteenth century England & Wales by Rosevear, Bogart & Shaw-Taylor.

DescriptionThe Highway key is a label from OpenStreetMap which aims to map and document any kind of road, street or path. More information on the tag here. LimitationsBear in mind that OpenStreetMap (OSM) is a digital map database of the world built through crowdsourced volunteered geographic information (VGI). Therefore, there is no systematic quality check performed on the data, and the detail, precision and accuracy varies across space. AttributesOBJECTID: Assigned by WWF. Unique identifierhighway: Type of road facility (motorway, trunk, primary, secondary, tertiary)name: Name of the road facilitysource: Source of the Feature (Landsat, Bing, GPS, Yahoo)surface: Type of surface (paved, unpaved, asphalt, ground) oneway: Direction of flow in only one direction (N: No, Y: Yes).maxspeed: Maximum speed allowed (km/h)lanes: Number of traffic lanes for general purpose traffic, also for buses and other specific classes of vehicleservice: Other type of facilities in the road (alley, driveway, parking_aisle)source: Source of the feature (Landsat, Bing)

Two map files in ARC GIS PRO showing the main roads in England and Wales mapped by John Cary ca 1825. All Post roads, turnpike roads and other main roads designated by Cary are mapped as polylines. A substantial umber of the "other roads", judged to be parish roads are mapped.

At Driver Technologies, we specialize in collecting high-quality, highly-anonymized, driving data crowdsourced using our dash cam app. Our Traffic Light Map Video Data is built from the millions of miles of driving data captured and is optimized to be trained for whatever computer vision models you need and enhancing various applications in transportation and safety.

What Makes Our Data Unique? What sets our Traffic Light Map Video Data apart is its comprehensive approach to road object detection. By leveraging advanced computer vision models, we analyze the captured video to identify and classify various road objects encountered during an end user's trip. This includes road signs, pedestrians, vehicles, traffic signs, and road conditions, resulting in rich, annotated datasets that can be used for a range of applications.

How Is the Data Generally Sourced? Our data is sourced directly from users who utilize our dash cam app, which harnesses the smartphone’s camera and sensors to record during a trip. This direct sourcing method ensures that our data is unbiased and represents a wide variety of conditions and environments. The data is not only authentic and reflective of current road conditions but is also abundant in volume, offering millions of miles of recorded trips that cover diverse scenarios.

Primary Use-Cases and Verticals The Traffic Light Map Video Data is tailored for various sectors, particularly those involved in transportation, urban planning, and autonomous vehicle development. Key use cases include:

Training Computer Vision Models: Clients can utilize our annotated data to develop and refine their own computer vision models for applications in autonomous vehicles, ensuring better object detection and decision-making capabilities in complex road environments.

Urban Planning and Infrastructure Development: Our data helps municipalities understand road usage patterns, enabling them to make informed decisions regarding infrastructure improvements, safety measures, and traffic light placement. Our data can also aid in making sure municipalities have an accurate count of signs in their area.

Integration with Our Broader Data Offering The Traffic Light Map Video Data is a crucial component of our broader data offerings at Driver Technologies. It complements our extensive library of driving data collected from various vehicles and road users, creating a comprehensive data ecosystem that supports multiple verticals, including insurance, automotive technology, and computer vision models.

In summary, Driver Technologies' Traffic Light Map Video Data provides a unique opportunity for data buyers to access high-quality, actionable insights that drive innovation across mobility. By integrating our Traffic Light Map Video Data with other datasets, clients can gain a holistic view of transportation dynamics, enhancing their analytical capabilities and decision-making processes.

Roads in central southern England c.1675, constructed from John Ogilby's strip maps.The .kml file gives a crude preview; please download the shapefiles for discrimination between major routes, minor routes, and speculative spurs.

centres communities community_centres facilities groups lifestyle17

This data is experimental, see the ‘Access Constraints or User Limitations’ section for more details. This dataset has been generalised to 10 metre resolution where it is still but the space needed for downloads will be improved.A set of UK wide estimated travel area geometries (isochrones), from Output Area (across England, Scotland, and Wales) and Small Area (across Northern Ireland) population-weighted centroids. The modes used in the isochrone calculations are limited to public transport and walking. Generated using Open Trip Planner routing software in combination with Open Street Maps and open public transport schedule data (UK and Ireland).The geometries provide an estimate of reachable areas by public transport and on foot between 7:15am and 9:15am for a range of maximum travel durations (15, 30, 45 and 60 minutes). For England, Scotland and Wales, these estimates were generated using public transport schedule data for Tuesday 15th November 2022. For Northern Ireland, the date used is Tuesday 6th December 2022.The data is made available as a set of ESRI shape files, in .zip format. This corresponds to a total of 18 files; one for Northern Ireland, one for Wales, twelve for England (one per English region, where London, South East and North West have been split into two files each) and four for Scotland (one per NUTS2 region, where the ‘North-East’ and ‘Highlands and Islands’ have been combined into one shape file, and South West Scotland has been split into two files).The shape files contain the following attributes. For further details, see the ‘Access Constraints or User Limitations’ section:AttributeDescriptionOA21CD or SA2011 or OA11CDEngland and Wales: The 2021 Output Area code.Northern Ireland: The 2011 Small Area code.Scotland: The 2011 Output Area code.centre_latThe population-weighted centroid latitude.centre_lonThe population-weighted centroid longitude.node_latThe latitude of the nearest Open Street Map “highway” node to the population-weighted centroid.node_lonThe longitude of the nearest Open Street Map “highway” node to the population-weighted centroid.node_distThe distance, in meters, between the population-weighted centroid and the nearest Open Street Map “highway” node.stop_latThe latitude of the nearest public transport stop to the population-weighted centroid.stop_lonThe longitude of the nearest public transport stop to the population-weighted centroid.stop_distThe distance, in metres, between the population-weighted centroid and the nearest public transport stop.centre_inBinary value (0 or 1), where 1 signifies the population-weighted centroid lies within the Output Area/Small Area boundary. 0 indicates the population-weighted centroid lies outside the boundary.node_inBinary value (0 or 1), where 1 signifies the nearest Open Street Map “highway” node lies within the Output Area/Small Area boundary. 0 indicates the nearest Open Street Map node lies outside the boundary.stop_inBinary value (0 or 1), where 1 signifies the nearest public transport stop lies within the Output Area/Small Area boundary. 0 indicates the nearest transport stop lies outside the boundary.iso_cutoffThe maximum travel time, in seconds, to construct the reachable area/isochrone. Values are either 900, 1800, 2700, or 3600 which correspond to 15, 30, 45, and 60 minute limits respectively.iso_dateThe date for which the isochrones were estimated, in YYYY-MM-DD format.iso_typeThe start point from which the estimated isochrone was calculated. Valid values are:from_centroid: calculated using population weighted centroid.from_node: calculated using the nearest Open Street Map “highway” node.from_stop: calculated using the nearest public transport stop.no_trip_found: no isochrone was calculated.geometryThe isochrone geometry.iso_hectarThe area of the isochrone, in hectares.Access constraints or user limitations.These data are experimental and will potentially have a wider degree of uncertainty. They remain subject to testing of quality, volatility, and ability to meet user needs. The methodologies used to generate them are still subject to modification and further evaluation.These experimental data have been published with specific caveats outlined in this section. The data are shared with the analytical community with the purpose of benefitting from the community's scrutiny and in improving the quality and demand of potential future releases. There may be potential modification following user feedback on both its quality and suitability.For England and Wales, where possible, the latest census 2021 Output Area population weighted centroids were used as the starting point from which isochrones were calculated.For Northern Ireland, 2011 Small Area population weighted centroids were used as the starting point from which isochrones were calculated. Small Areas and Output Areas contain a similar number of households within their boundaries. 2011 data was used because this was the most up-to-date data available at the time of generating this dataset. Population weighted centroids for Northern Ireland were calculated internally but may be subject to change - in the future we aim to update these data to be consistent with Census 2021 across the UK.For Scotland, 2011 Output Area population-weighted centroids were used as the starting point from which isochrones were calculated. 2011 data was used because this was the most up-to-date data available at the time of work.The data for England, Scotland and Wales are released with the projection EPSG:27700 (British National Grid).The data for Northern Ireland are released with the projection EPSG:29902 (Irish Grid).The modes used in the isochrone calculations are limited to public transport and walking. Other modes were not considered when generating this data.A maximum value of 1.5 kilometres walking distance was used when generating isochrones. This approximately represents typical walking distances during a commute (based on Department for Transport/Labour Force Survey data and Travel Survey for Northern Ireland technical reports).When generating Northern Ireland data, public transport schedule data for both Northern Ireland and Republic of Ireland were used.Isochrone geometries and calculated areas are subject to public transport schedule data accuracy, Open Trip Planner routing methods and Open Street Map accuracy. The location of the population-weighted centroid can also influence the validity of the isochrones, when this falls on land which is not possible or is difficult to traverse (e.g., private land and very remote locations).The Northern Ireland public transport data were collated from several files, and as such required additional pre-processing. Location data are missing for two bus stops. Some services run by local public transport providers may also be missing. However, the missing data should have limited impact on the isochrone output. Due to the availability of Northern Ireland public transport data, the isochrones for Northern Ireland were calculated on a comparable but slight later date of 6th December 2022. Any potential future releases are likely to contained aligned dates between all four regions of the UK.In cases where isochrones are not calculable from the population-weighted centroid, or when the calculated isochrones are unrealistically small, the nearest Open Street Map ‘highway’ node is used as an alternative starting point. If this then fails to yield a result, the nearest public transport stop is used as the isochrone origin. If this also fails to yield a result, the geometry will be ‘None’ and the ‘iso_hectar’ will be set to zero. The following information shows a further breakdown of the isochrone types for the UK as a whole:from_centroid: 99.8844%from_node: 0.0332%from_stop: 0.0734%no_trip_found: 0.0090%The term ‘unrealistically small’ in the point above refers to outlier isochrones with a significantly smaller area when compared with both their neighbouring Output/Small Areas and the entire regional distribution. These reflect a very small fraction of circumstances whereby the isochrone extent was impacted by the centroid location and/or how Open Trip Planner handled them (e.g. remote location, private roads and/or no means of traversing the land). Analysis showed these outliers were consistently below 100 hectares for 60-minute isochrones. Therefore, In these cases, the isochrone point of origin was adjusted to the nearest node or stop, as outlined above.During the quality assurance checks, the extent of the isochrones was observed to be in good agreement with other routing software and within the limitations stated within this section. Additionally, the use of nearest node, nearest stop, and correction of ‘unrealistically small areas’ was implemented in a small fraction of cases only. This culminates in no data being available for 8 out of 239,768 Output/Small Areas.Data is only available in ESRI shape file format (.zip) at this release.https://www.openstreetmap.org/copyright

Explore the interactive maps showing the average delay and average speed on the Strategic Road Network and local ‘A’ roads in England, in 2022.

On the Strategic Road Network (SRN) for 2022, the average delay is estimated to be 9.3 seconds per vehicle per mile (spvpm), compared to free flow, a 9.4% increase on 2021 and a 2.1% decrease on 2019.

The average speed is estimated to be 58.1 mph, down 1.4% from 2021 and up 0.2% from 2019.

On local ‘A’ roads for 2022, the average delay was estimated to be 45.5 seconds per vehicle per mile compared to free flow, up 2.5% from 2021 and down 2.8% from 2019 (pre-coronavirus)

The average speed is estimated to be 23.7 mph, down 1.7% from 2021 and up 2.2% from 2019 (pre-coronavirus).

Average speeds in 2022 have stabilised towards similar trends observed before the effects of the coronavirus pandemic.

The outbreak of coronavirus (COVID-19) has had a marked impact on everyday life, including on congestion on the road network. As some of these data are affected by the coronavirus pandemic in the UK, caution should be taken when interpreting these statistics and comparing them with other time periods. Additional http://bit.ly/COVID_Congestion_Analysis" class="govuk-link">analysis on the impact of the coronavirus pandemic on road journeys in 2020 is also available. This Storymap contains charts and interactive maps for road journeys in England in 2020.

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Details of all Calderdale establishments registered to sell food including, name, address, ward and type.

Colourful and easy to use, Bartholomew’s maps became a trademark series. The maps were popular and influential, especially for recreation, and the series sold well, particularly with cyclists and tourists. To begin with, Bartholomew printed their half-inch maps in Scotland as stand-alone sheets known as 'District Sheets' and by 1886 the whole of Scotland was covered. They then revised the maps into an ordered set of 29 sheets covering Scotland in a regular format. This was first published under the title Bartholomew’s Reduced Ordnance Survey of Scotland. The half-inch maps of Scotland formed the principal content for Bartholomew's Survey Atlas of Scotland published in 1895. Bartholomew then moved south of the Border to the more lucrative but competitive market in England and Wales, whilst continuing to revise the Scottish sheets. This Bartholomew series at half-inch to the mile, covered Great Britain in 62 sheets in the 1940s, Bartholomew’s first to cover Great Britain at this scale (their previous series covering Scotland and then England and Wales). The series provides an attractive and useful snapshot of 1940s Britain. By this time, Bartholomew had altered the range of information on their maps compared to the 1900s. There were more categories of roads, Ministry of Transport road numbers were added, and new recreational features such as Youth Hostels and Golf Courses. Bartholomew’s topographic information was gathered partly from original Ordnance Survey maps, and partly from information sent in to Bartholomew from map users. One important user community for Bartholomew were cyclists. From the 1890s, Bartholomew entered into a formal relationship with the Cyclists’ Touring Club, then numbering around 60,500 cyclists, proposing that club members supplied Bartholomew with up-to-date information. In return, Bartholomew provided the CTC with discounted half-inch maps. The relationship worked very well, turning CTC members into an unofficial surveying army, feeding back reliable and accurate topographical information which Bartholomew would then use to update their maps. You can read more about this and see selected letters from cyclists at: http://digital.nls.uk/bartholomew/duncan-street-explorer/cyclists-touring-club.html.

Usually Bartholomew made revisions the sheets right up to the time of publication, so the date of publication is the best guide to the approximate date of the features shown on the map. You can view the dates of publication for the series at: https://maps.nls.uk/series/bart_half_great_britain.html

Mapping the location and characteristics of high streets in Great Britain, working with experimental Ordnance Survey High Street extents and Office for National Statistics data.

This global accessibility map enumerates land-based travel time to the nearest densely-populated area for all areas between 85 degrees north and 60 degrees south for a nominal year 2015. Densely-populated areas are defined as contiguous areas with 1,500 or more inhabitants per square kilometre or a majority of built-up land cover types coincident with a population centre of at least 50,000 inhabitants. This map was produced through a collaboration between MAP (University of Oxford), Google, the European Union Joint Research Centre (JRC), and the University of Twente, Netherlands.The underlying datasets used to produce the map include roads (comprising the first ever global-scale use of Open Street Map and Google roads datasets), railways, rivers, lakes, oceans, topographic conditions (slope and elevation), landcover types, and national borders. These datasets were each allocated a speed or speeds of travel in terms of time to cross each pixel of that type. The datasets were then combined to produce a "friction surface"; a map where every pixel is allocated a nominal overall speed of travel based on the types occurring within that pixel. Least-cost-path algorithms (running in Google Earth Engine and, for high-latitude areas, in R) were used in conjunction with this friction surface to calculate the time of travel from all locations to the nearest (in time) city. The cities dataset used is the high-density-cover product created by the Global Human Settlement Project. Each pixel in the resultant accessibility map thus represents the modelled shortest time from that location to a city. Authors: D.J. Weiss, A. Nelson, H.S. Gibson, W. Temperley, S. Peedell, A. Lieber, M. Hancher, E. Poyart, S. Belchior, N. Fullman, B. Mappin, U. Dalrymple, J. Rozier, T.C.D. Lucas, R.E. Howes, L.S. Tusting, S.Y. Kang, E. Cameron, D. Bisanzio, K.E. Battle, S. Bhatt, and P.W. Gething. A global map of travel time to cities to assess inequalities in accessibility in 2015. (2018). Nature. doi:10.1038/nature25181

Processing notes: Data were processed from numerous sources including OpenStreetMap, Google Maps, Land Cover mapping, and others, to generate a global friction surface of average land-based travel speed. This accessibility surface was then derived from that friction surface via a least-cost-path algorithm finding at each location the closest point from global databases of population centres and densely-populated areas. Please see the associated publication for full details of the processing.

Source: https://map.ox.ac.uk/research-project/accessibility_to_cities/

OSNI Street Maps showing detailed information, including road names and one-way systems, railway lines, car parking, public buildings, churches and schools, for Northern Ireland’s cities and towns. Dataset derived from OSNI large and smallscale data.Please Note for Open Data NI Users: Esri Rest API is not Broken, it will not open on its own in a Web Browser but can be copied and used in Desktop and Webmaps

Data from North Yorkshire Police http://data.police.uk/data/

This dataset contains centreline information regarding roads in Northern Ireland that are adopted and maintained by DfI Roads. Use the ADOPTION_STATUS_NAME column to filter the data and to show current adopted road sections. Note this is a 'live' link and is updated each evening to include any new road sections. A map displaying the adopted roads can be accessed via: https://dfi-ni.maps.arcgis.com/apps/webappviewer/index.html?id=f8a42fc35a3d48788e651a1d47865ce1

The most detailed street-level open data vector mapping product available, OS Open Map – Local is a great backdrop over which to display and analyse your data.

This dataset is refreshed on a weekly basis from the datasets the team works on daily.Last update date: 18 July 2025.National Highways Operational Highway Boundary (RedLine) maps out the land belonging to the highway for the whole Strategic Road Network (SRN). It comprises two layers; one being the an outline and another showing the registration status / category of land of land that makes up the boundary. Due to the process involved in creating junctions with local highway authority (LHA) roads, land in this dataset may represent LHA highway (owned by National Highways but the responsibility of the LHA to maintain). Surplus land or land held for future projects does not form part of this dataset.The highway boundary is derived from:Ordnance Survey Mastermap Topography,HM Land Registry National Polygon Service (National Highway titles only), andplots researched and digitised during the course of the RedLine Boundary Project.The boundary is split into categories describing the decisions made for particular plots of land. These categories are as follows:Auto-RedLine category is for plots created from an automated process using Ordnance Survey MasterMap Topography as a base. Land is not registered under National Highways' name. For example, but not limited to, unregistered ‘ancient’ highway vested in Highways England, or bridge carrying highways over a rail line.NH Title within RedLine category is for plots created from Land Registry Cadastral parcels whose proprietor is National Highways or a predecessor. Land in this category is within the highway boundary (audited) or meets a certain threshold by the algorithm.NH Title outside RedLine category is for plots created in the same way as above but these areas are thought to be outside the highway boundary. Where the Confidence is Low, land in this category is yet to be audited. Where the Confidence is High, land in this category has been reviewed and audited as outside our operational boundary.National Highways (Technician) Data category is for plots created by National Highways, digitised land parcels relating to highway land that is not registered, not yet registered or un-registerable.Road in Tunnel category, created using tunnel outlines from Ordnance Survey MasterMap Topography data. These represent tunnels on Highways England’s network. Land is not registered under National Highways' name, but land above the tunnel may be in National Highways’ title. Please refer to the definitive land ownership records held at HM Land Registry.The process attribute details how the decision was made for the particular plot of land. These are as follows:Automated category denotes data produced by an automated process. These areas are yet to be audited by the company.Audited category denotes data that has been audited by the company.Technician Data (Awaiting Audit) category denotes data that was created by National Highways but is yet to be audited and confirmed as final.The confidence attribute details how confident you can be in the decision. This attribute is derived from both the decisions made during the building of the underlying automated dataset as well as whether the section has been researched and/or audited by National Highways staff. These are as follows:High category denotes land that has a high probability of being within the RedLine boundary. These areas typically are audited or are features that are close to or on the highway.Moderate category denotes land that is likely to be within the highway boundary but is subject to change once the area has been audited.Low category denotes land that is less likely to be within the highway boundary. These plots typically represent Highways England registered land that the automated process has marked as outside the highway boundary.Please note that this dataset is indicative only. For queries about this dataset please contact the GIS and Research Team.

This layer is a georeferenced raster image of the historic paper map entitled: A new mapp of the city of London c. : with the many additionall buildings and new streets anno 1723 in a playne. It was printed and sold by Thomas Taylor at the Golden Lyon in Fleet Street, 1723. All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, or other information associated with the principal map. This map was georeferenced as part of the Authorial London project, an application which allows users to visualize the spatial overlap of varios authors who lived in and traveled through London over the last 600 years.