Important Note: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This map is designed to be used as a general reference map for informational and educational purposes as well as a basemap by GIS professionals and other users for creating web maps and web mapping applications.The map was developed by National Geographic and Esri and reflects the distinctive National Geographic cartographic style in a multi-scale reference map of the world. The map was authored using data from a variety of leading data providers, including Garmin, HERE, UNEP-WCMC, NASA, ESA, USGS, and others.This reference map includes administrative boundaries, cities, protected areas, highways, roads, railways, water features, buildings and landmarks, overlaid on shaded relief and land cover imagery for added context. The map includes global coverage down to ~1:144k scale and more detailed coverage for North America down to ~1:9k scale.Map Note: Although small-scale boundaries, place names and map notes were provided and edited by National Geographic, boundaries and names shown do not necessarily reflect the map policy of the National Geographic Society, particularly at larger scales where content has not been thoroughly reviewed or edited by National Geographic.Data Notes: The credits below include a list of data providers used to develop the map. Below are a few additional notes:Reference Data: National Geographic, Esri, Garmin, HERE, iPC, NRCAN, METILand Cover Imagery: NASA Blue Marble, ESA GlobCover 2009 (Copyright notice: © ESA 2010 and UCLouvain)Protected Areas: IUCN and UNEP-WCMC (2011), The World Database on Protected Areas (WDPA) Annual Release. Cambridge, UK: UNEP-WCMC. Available at:www.protectedplanet.net.Ocean Data: GEBCO, NOAA
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
This dataset is part of the Geographical repository maintained by Opendatasoft. This dataset contains data for countries in the United Kingdom.Processors and tools are using this data.EnhancementsAdd ISO 3166-3 codes.Simplify geometries to provide better performance across the services.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
This is a collection of simple maps in PDF format that are designed to be printed off and used in the classroom. The include maps of Great Britain that show the location of major rivers, cities and mountains as well as maps of continents and the World. There is very little information on the maps to allow teachers to download them and add their own content to fit with their lesson plans. Customise one print out then photocopy them for your lesson. data not available yet, holding data set (7th August). Other. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2012-08-07 and migrated to Edinburgh DataShare on 2017-02-22.
More than 400 Country Parks exist. They are public green spaces often at the edge of urban areas which provide places to enjoy the outdoors and experience nature in an informal semi-rural park setting. Country Parks normally have some facilities such as a car park, toilets, perhaps a cafe or kiosk, paths and trails, and visitor information. There is not necessarily a public right of access, although most are publicly accessible; some charge entry others do not. Most are owned and managed by Local Authorities. Many Country Parks were designated in the 1970s by the then Countryside Commission, under the Countryside Act 1968. More recently Country Parks have been created under a less formal arrangement and Natural England is working with partners to encourage a renaissance and accreditation of parks which meet certain criteria. The dataset contains boundaries of each Country Park, digitised against Ordnance Survey MasterMap using source maps supplied by Local Authorities.Full metadata can be viewed on data.gov.uk.
http://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/INSPIRE_Directive_Article13_1dhttp://inspire.ec.europa.eu/metadata-codelist/LimitationsOnPublicAccess/INSPIRE_Directive_Article13_1d
This dataset comprises 2 collections of maps. The facsmile collection contains all the marginalia information from the original map as well as the map itself, while the georectified collection contains just the map with an associated index for locating them. Each collection comprises approximately 101 000 monochrome images at 6-inch (1:10560) scale. Each image is supplied in .tiff format with appropriate ArcView and MapInfo world files, and shows the topography for all areas of England, Wales and Scotland as either quarter or, in some cases, full sheets. The images will cover the approximate epochs 1880's, 1900's, 1910's, 1920's and 1930's, but note that coverage is not countrywide for each epoch. The data was purchased by BGS from Sitescope, who obtained it from three sources - Royal Geographical Society, Trinity College Dublin and the Ordnance Survey. The data is for internal use by BGS staff on projects, and is available via a customised application created for the network GDI enabling users to search for and load the maps of their choice. The dataset will have many uses across all the geoscientific disciplines across which BGS operates, and should be viewed as a valuable addition to the BGS archive. There has been a considerable amount of work done during 2005, 2006 and 2007 to improve the accuracy of the OS Historic Map Collection. All maps should now be located to +- 50m or better. This is the best that can be achieved cost effectively. There are a number of reasons why the maps are inaccurate. Firstly, the original maps are paper and many are over 100 years old. They have not been stored in perfect condition. The paper has become distorted to varying degrees over time. The maps were therefore not accurate before scanning. Secondly, different generations of maps will have used different surveying methods and different spatial referencing systems. The same geographical object will not necessarily be in the same spatial location on subsequent editions. Thirdly, we are discussing maps, not plans. There will be cartographic generalisations which will affect the spatial representation and location of geographic objects. Finally, the georectification was not done in BGS but by the company from whom we purchased the maps. The company no longer exists. We do not know the methodology used for georectification.
In the century between Napoleon's defeat and the outbreak of the First World War (known as the "Pax Britannica"), the British Empire grew to become the largest and most powerful empire in the world. At its peak in the 1910s and 1920s, it encompassed almost one quarter of both the world's population and its land surface, and was known as "the empire on which the sun never sets". The empire's influence could be felt across the globe, as Britain could use its position to affect trade and economies in all areas of the world, including many regions that were not part of the formal empire (for example, Britain was able to affect trading policy in China for over a century, due to its control of Hong Kong and the neighboring colonies of India and Burma). Some historians argue that because of its economic, military, political and cultural influence, nineteenth century Britain was the closest thing to a hegemonic superpower that the world ever had, and possibly ever will have. "Rule Britannia" Due to the technological and logistical restrictions of the past, we will never know the exact borders of the British Empire each year, nor the full extent of its power. However, by using historical sources in conjunction with modern political borders, we can gain new perspectives and insights on just how large and influential the British Empire actually was. If we transpose a map of all former British colonies, dominions, mandates, protectorates and territories, as well as secure territories of the East India Trading Company (EIC) (who acted as the precursor to the British Empire) onto a current map of the world, we can see that Britain had a significant presence in at least 94 present-day countries (approximately 48 percent). This included large territories such as Australia, the Indian subcontinent, most of North America and roughly one third of the African continent, as well as a strategic network of small enclaves (such as Gibraltar and Hong Kong) and islands around the globe that helped Britain to maintain and protect its trade routes. The sun sets... Although the data in this graph does not show the annual population or size of the British Empire, it does give some context to how Britain has impacted and controlled the development of the world over the past four centuries. From 1600 until 1920, Britain's Empire expanded from a small colony in Newfoundland, a failing conquest in Ireland, and early ventures by the EIC in India, to Britain having some level of formal control in almost half of all present-day countries. The English language is an official language in all inhabited continents, its political and bureaucratic systems are used all over the globe, and empirical expansion helped Christianity to become the most practiced major religion worldwide. In the second half of the twentieth century, imperial and colonial empires were eventually replaced by global enterprises. The United States and Soviet Union emerged from the Second World War as the new global superpowers, and the independence movements in longstanding colonies, particularly Britain, France and Portugal, gradually succeeded. The British Empire finally ended in 1997 when it seceded control of Hong Kong to China, after more than 150 years in charge. Today, the United Kingdom consists of four constituent countries, and it is responsible for three crown dependencies and fourteen overseas territories, although the legacy of the British Empire can still be seen, and it's impact will be felt for centuries to come.
Digital Map Market Size 2025-2029
The digital map market size is forecast to increase by USD 31.95 billion at a CAGR of 31.3% between 2024 and 2029.
The market is driven by the increasing adoption of intelligent Personal Digital Assistants (PDAs) and the availability of location-based services. PDAs, such as smartphones and smartwatches, are becoming increasingly integrated with digital map technologies, enabling users to navigate and access real-time information on-the-go. The integration of Internet of Things (IoT) enables remote monitoring of cars and theft recovery. Location-based services, including mapping and navigation apps, are a crucial component of this trend, offering users personalized and convenient solutions for travel and exploration. However, the market also faces significant challenges.
Ensuring the protection of sensitive user information is essential for companies operating in this market, as trust and data security are key factors in driving user adoption and retention. Additionally, the competition in the market is intense, with numerous players vying for market share. Companies must differentiate themselves through innovative features, user experience, and strong branding to stand out in this competitive landscape. Security and privacy concerns continue to be a major obstacle, as the collection and use of location data raises valid concerns among consumers.
What will be the Size of the Digital Map Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the market, cartographic generalization and thematic mapping techniques are utilized to convey complex spatial information, transforming raw data into insightful visualizations. Choropleth maps and dot density maps illustrate distribution patterns of environmental data, economic data, and demographic data, while spatial interpolation and predictive modeling enable the estimation of hydrographic data and terrain data in areas with limited information. Urban planning and land use planning benefit from these tools, facilitating network modeling and location intelligence for public safety and emergency management.
Spatial regression and spatial autocorrelation analyses provide valuable insights into urban development trends and patterns. Network analysis and shortest path algorithms optimize transportation planning and logistics management, enhancing marketing analytics and sales territory optimization. Decision support systems and fleet management incorporate 3D building models and real-time data from street view imagery, enabling effective resource management and disaster response. The market in the US is experiencing robust growth, driven by the integration of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and advanced computer technology into various industries.
How is this Digital Map Industry segmented?
The digital map industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Application
Navigation
Geocoders
Others
Type
Outdoor
Indoor
Solution
Software
Services
Deployment
On-premises
Cloud
Geography
North America
US
Canada
Europe
France
Germany
UK
APAC
China
India
Indonesia
Japan
South Korea
Rest of World (ROW)
By Application Insights
The navigation segment is estimated to witness significant growth during the forecast period. Digital maps play a pivotal role in various industries, particularly in automotive applications for driver assistance systems. These maps encompass raster data, aerial photography, government data, and commercial data, among others. Open-source data and proprietary data are integrated to ensure map accuracy and up-to-date information. Map production involves the use of GPS technology, map projections, and GIS software, while map maintenance and quality control ensure map accuracy. Location-based services (LBS) and route optimization are integral parts of digital maps, enabling real-time navigation and traffic data.
Data validation and map tiles ensure data security. Cloud computing facilitates map distribution and map customization, allowing users to access maps on various devices, including mobile mapping and indoor mapping. Map design, map printing, and reverse geocoding further enhance the user experience. Spatial analysis and data modeling are essential for data warehousing and real-time navigation. The automotive industry's increasing adoption of connected cars and long-term evolution (LTE) technologies have fueled the demand for digital maps. These maps enable driver assistance app
The maps below show the population of the UK in 2022, at country, region, county and postcode sector level. The maps also provide information about the relative wealth, education and employment of people living in different areas.This map shows different countries of the UK.
Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
License information was derived automatically
This dataset shows the global distribution of coral reefs in tropical and subtropical regions. It is the most comprehensive global dataset of warm-water coral reefs to date, acting as a foundation baseline map for future, more detailed, work. This dataset was compiled from a number of sources by UNEP World Conservation Monitoring Centre (UNEP-WCMC) and the WorldFish Centre, in collaboration with WRI (World Resources Institute) and TNC (The Nature Conservancy). Data sources include the Millennium Coral Reef Mapping Project (IMaRS-USF and IRD 2005, IMaRS-USF 2005) and the World Atlas of Coral Reefs (Spalding et al. 2001).
Citation: UNEP-WCMC, WorldFish Centre, WRI, TNC (2018). Global distribution of warm-water coral reefs, compiled from multiple sources including the Millennium Coral Reef Mapping Project. Version 4.0. Includes contributions from IMaRS-USF and IRD (2005), IMaRS-USF (2005) and Spalding et al. (2001). Cambridge (UK): UN Environment World Conservation Monitoring Centre. URL: http://data.unep-wcmc.org/datasets/1
Citations for the separate entities: IMaRS-USF (Institute for Marine Remote Sensing-University of South Florida) (2005). Millennium Coral Reef Mapping Project. Unvalidated maps. These maps are unendorsed by IRD, but were further interpreted by UNEP World Conservation Monitoring Centre. Cambridge (UK): UNEP World Conservation Monitoring Centre
IMaRS-USF, IRD (Institut de Recherche pour le Developpement) (2005). Millennium Coral Reef Mapping Project. Validated maps. Cambridge (UK): UNEP World Conservation Monitoring Centre
Spalding MD, Ravilious C, Green EP (2001). World Atlas of Coral Reefs. Berkeley (California, USA): The University of California Press. 436 pp.
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/
Data from the British Geological Survey's GeoIndex Map products theme are made available for viewing here. GeoIndex is a website that allows users to search for information about BGS data collections covering the UK and other areas world wide. Access is free, the interface is easy to use, and it has been developed to enable users to check coverage of different types of data and find out some background information about the data. More detailed information can be obtained by further enquiry via the web site: www.bgs.ac.uk/geoindex.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
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)
This dataset summarises information from WWT's wetland potential mapping at the WFD waterbody catchment (catchment) level. Data from multiple layers are pulled together to allow visualisation of the relative potential for wetlands across catchments of Great Britain. Specifically, it includes data from the WWT 'wetlands for water quality', 'wetlands for carbon storage', 'wetlands for flood resilience' and 'wetlands for urban wellbeing' indicative wetland potential maps, and from the Combined 'multi-benefit' wetland potential map, which amalgamates these four layers. It is recommended that users view these layers alongside the layers created from this dataset.The absence of mapped wetland potential in a catchment does not necessarily mean there is no potential to create wetlands, nor a lack of issues that wetland solutions could be used to address. Wetland potential was only mapped within 'demand' areas where there is a greater need for wetland solutions.This dataset includes the following information:UK Water Framework Directive (WFD) status and waterbody identifiers (for waterbodies in England, Wales and Scotland).Summary information on the total indicative wetland potential (from the four wetland potential maps) per catchment, including the total area (in hectares) and percentage cover of wetland potential across the catchment area.Total area and percentage cover of 'wetlands for flood resilience' and 'wetlands for water quality' potential per catchment. Number of potential 'wetlands for flood resilience' and 'wetlands for water quality' parcels per catchment (figures may be arbitrary due to intersects used to summarise wetland potential).Priority 'demand' catchments for potential 'wetlands for water quality'. Priority 'demand' catchments for potential 'wetlands for flood resilience'. Percentage change in household projections for 2018-2041, per catchment (averaged across Local Authorities and Higher Administrative areas (England & Wales) and Council areas (Scotland)).Average number of new builds (averaged across Local Authorities) built in 2021-2022, per catchment.WWT are calling for the creation of 100,000 hectares of new and restored wetlands in the UK by 2050. This dataset is a part of WWT’s Roadmap to 100,000 hectares project, which aims to assess both the spatial and economic potential for large-scale wetland restoration targeted at tackling some of the key issues faced by UK society. The work has a particular focus on four themes where wetlands can provide solutions, namely (1) wetlands for carbon storage (specifically saltmarsh for blue carbon), (2) wetlands for urban wellbeing, (3) wetlands for flood resilience, and (4) wetlands for water quality. Wetland potential for water quality, carbon storage, flood resilience and urban wellbeing has been mapped.Full methodology can be found here. Attributes:
Heading
Description
wb_id
ID number of the WFD waterbody
wb_name
Name of the WFD waterbody
country
UK country in which the WFD waterbody is located
WFD_class
WFD status classification of the waterbody
ovl_p_ha
Total area of wetland potential (from all four WWT wetland potential layers) in the catchment, in hectares
percnt_ovl
Total area of wetland potential (from all four WWT wetland potential layers) in the waterbody, as a percentage of the catchment area
count_ovl
Number of wetland potential parcels located in the catchment (arbitrary value)
nfm_p_ha
Total area of 'wetlands for flood resilience' potential in the catchment, in hectares
percnt_nfm
Total area of 'wetlands for flood resilience' potential in the catchment, as a percentage of the catchment area
count_nfm
Number of 'wetlands for flood resilience' parcels located in the catchment
wq_p_ha
Total area of 'wetlands for water quality' potential in the catchment
percnt_wq
Total area of 'wetlands for water quality' potential in the catchment, as a percentage of the catchment area
count_wq
Number 'wetlands for water quality' parcels located in the catchment
priorit_wq
Priority 'demand' catchments for 'wetlands for water quality' (1 = 'demand' catchment')
prior_nfm
Priority 'demand' catchments for 'wetlands for flood resilience' (1 = 'demand' catchment')
Av_percent
Percentage change in household predictions from 2018 - 2041 averaged across Local Authorities within the catchment
Av_nb_2122
Number of new builds (2021-22) per catchment (average across Local Authorities within the catchment)
WorldMap shows single species plant distributions and cumulative map distributions for the following plant groups in sub Saharan Africa: Gymnosperms, Dicotyledons, Monocotyledons, Kenyan Trees, Shrubs, and Lianas, Northeastern Tropical African forest trees, and Southern Africa trees.
There are thousands of single species plant distribution maps currently in distribution, documenting plant distributions over the vast majority of sub-Saharan Africa. The maps display species distributions on a per-species basis, and date back over the last 100+ years documenting what for many was a life's work.
Current conservation initiatives call for the understanding of the total species composition, or the levels of diversity, of areas under analysis. The raw data for this is available in The single species distribution maps. However, cumulative maps of species distributions displaying broader distributions at higher taxonomic scales have historically not been available due to technological limitations.
The advent of faster computers with large amounts of digital storage space, and the development of the software application 'WORLDMAP,' makes constructing these cumulative plant species databases a possibility.
It is predicted that there are around 40,000 sub-Saharan African plant species. It is the aim of CELP to compile 10-15% of these from available distribution maps. To date, over 3500 available species have been mapped at the 1-degree resolution here at CELP.
Information was obtained from "http://www.york.ac.uk/res/celp/webpages/projects/worldmap/worldmap.htm"
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
DescriptionThe railway key is a label from OpenStreetMap which aims to map and document all types of railways including light rail, mainline railways, metros, monorails and trams. 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 identifierrailway: Type or status of railway facility (platform, subway, rail)electrified: Source of electricity (contact_line: a power line over the train head, rail: a third rail near the track supplying the train with power, yes: electrified track, but no details available, no: track with no power supply)Gauge: Voltage used for the railway facility operation (W)
The Historic Environment Opportunity Map for New Woodland dataset identifies areas in England that may be suitable for new woodland, based solely on available Historic Environment data. The dataset categorises land by different opportunity ratings to reflect the potential suitability of land for woodland creation while acknowledging areas of uncertainty due to data availability.The purpose of this dataset is to guide landowners, planners, and decision-makers in considering woodland creation from a historic environment perspective. It should be noted that this dataset only considers the Historic Environment and therefore the opportunity ratings do not guarantee or preclude approval for woodland creation proposals.As any forestry proposal could have the potential to affect the Historic Environment you should contact your local historic environment service. The local historic environment service can provide further data to support woodland creation proposals.NHLE is the official, up to date register of all nationally protected historic buildings and sites in England.SHINE is a single, nationally consistent dataset of non-designated historic and archaeological features from across England that could benefit from land management schemes.The opportunity ratings are as defined:· Favourable - Areas deemed suitable for new woodland on consideration of available Historic Environment data.· Neutral - Areas deemed neither favourable nor unfavourable for new woodland on consideration of available Historic Environment data. Proposals in these areas will require additional consideration of the Historic Environment on a case-by-case basis.· Unclassified - Areas, where SHINE data has been supplied, with no assigned opportunity rating. This illustrates a current absence of recorded data from a Historic Environment perspective. However, as SHINE data is included in the dataset for this area, a degree of confidence may be inferred when considering the absence of historic environment features.· Unclassified (No SHINE supplied) - Areas, where SHINE data has not been supplied, with no assigned opportunity rating. This illustrates a current absence of recorded data from a Historic Environment perspective.· Unsuitable - Areas deemed unsuitable for new woodland on consideration of available Historic Environment data.Unclassified areas may be suitable or unsuitable for new woodland. To better understand these areas, contact the local historic environment service in accordance with the UKFS and Historic Environment Guidance for Forestry in England - GOV.UKThe datasets included in each opportunity rating are as follows:Favourable· Lost Historic Woodlands (ArchAI/Forestry Commission) – An A.I. dataset that identifies areas of woodland depicted on early 20th Century Ordnance Survey mapping which have since been lost.Neutral· Historic Parklands (Zulu Ecosystems) – an A.I. dataset that identifies areas of parkland depicted on early 20th Century Ordnance Survey mapping.· World Heritage Site Core data (Historic England) – Core areas of World Heritage Sites, as designated by UNESCO.· World Heritage Site Buffer (Historic England) – Buffer zones surrounding World Heritage Sites, as designated by UNESCO.· Ridge and Furrow (Low) (ArchAI) – an A.I. dataset that identifies areas of less well-preserved historic ridge and furrow derived from LiDAR data.Unclassified· HER Boundaries (SHINE supplied) – Geographic areas covered by local historic environment services, where SHINE data has been supplied to the Forestry Commission.· HER Boundaries (No SHINE supplied) - Geographic areas covered by local historic environment services where SHINE data has not been supplied to the Forestry Commission.Unsuitable· Historic Landscape Characterisation (HLC) (local historic environment services) – regional datasets that provide information on the historic character of the landscape.· Scheduled Monuments (Historic England) – Protected archaeological sites of national importance.· Scheduled Monuments Buffer – A 20 metre buffer surrounding Scheduled Monuments in-line with UKFS.· Selected Heritage Inventory for Natural England (SHINE)(local historic environment services) – National dataset of non-designated heritage assets.· Registered Parks and Gardens (Historic England) – Parks and Gardens designated as being of national significance.· Registered Battlefields (Historic England) – Battlefields designated as being of national significance.· Ridge and Furrow (High) (ArchAI) – an A.I. dataset that identifies areas of well-preserved historic ridge and furrow derived from LiDAR data.
The map is designed to be used as a basemap by marine GIS professionals and as a reference map by anyone interested in ocean data. The basemap focuses on bathymetry. It also includes inland waters and roads, overlaid on land cover and shaded relief imagery.The Ocean Base map currently provides coverage for the world down to a scale of ~1:577k; coverage down to ~1:72k in United States coastal areas and various other areas; and coverage down to ~1:9k in limited regional areas.The World Ocean Reference is designed to be drawn on top of this map and provides selected city labels throughout the world. This web map lets you view the World Ocean Base with the Reference service drawn on top. Article in the Fall 2011 ArcUser about this basemap: "A Foundation for Ocean GIS".The map was compiled from a variety of best available sources from several data providers, including General Bathymetric Chart of the Oceans GEBCO_08 Grid version 20100927 and IHO-IOC GEBCO Gazetteer of Undersea Feature Names August 2010 version (https://www.gebco.net), National Oceanic and Atmospheric Administration (NOAA) and National Geographic for the oceans; and Garmin, and Esri for topographic content. You can contribute your bathymetric data to this service and have it served by Esri for the benefit of the Ocean GIS community. For details on the users who contributed bathymetric data for this map via the Community Maps Program, view the list of Contributors for the Ocean Basemap. The basemap was designed and developed by Esri. The GEBCO_08 Grid is largely based on a database of ship-track soundings with interpolation between soundings guided by satellite-derived gravity data. In some areas, data from existing grids are included. The GEBCO_08 Grid does not contain detailed information in shallower water areas, information concerning the generation of the grid can be found on GEBCO's website: https://www.gebco.net/data_and_products/gridded_bathymetry_data/. The GEBCO_08 Grid is accompanied by a Source Identifier (SID) Grid which indicates which cells in the GEBCO_08 Grid are based on soundings or existing grids and which have been interpolated. The latest version of both grids and accompanying documentation is available to download, on behalf of GEBCO, from the British Oceanographic Data Centre (BODC) https://www.bodc.ac.uk/data/online_delivery/gebco/.The names of the IHO (International Hydrographic Organization), IOC (intergovernmental Oceanographic Commission), GEBCO (General Bathymetric Chart of the Oceans), NERC (Natural Environment Research Council) or BODC (British Oceanographic Data Centre) may not be used in any way to imply, directly or otherwise, endorsement or support of either the Licensee or their mapping system.Tip: Here are some famous oceanic locations as they appear this map. Each URL launches this map at a particular location via parameters specified in the URL: Challenger Deep, Galapagos Islands, Hawaiian Islands, Maldive Islands, Mariana Trench, Tahiti, Queen Charlotte Sound, Notre Dame Bay, Labrador Trough, New York Bight, Massachusetts Bay, Mississippi Sound
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
(:unav)...........................................
https://vocab.nerc.ac.uk/collection/L08/current/CC/https://vocab.nerc.ac.uk/collection/L08/current/CC/
A series of approximately 3250 navigational charts covering the world. The series is maintained by Admiralty Notices to Mariners issued every week. New editions or new charts are published as required. Two thirds of the series are now available in metric units.
In areas where the United Kingdom is, or until recently has been, the responsible hydrographic authority - i.e. Home Waters, some Commonwealth countries, British colonies, and certain areas like the Gulf, Red Sea and parts of the eastern Mediterranean - the Admiralty charts afford detailed cover of all waters, ports and harbours. These make up about 30 per cent of the total series. Modern charts in these areas usually have a source data diagram showing the sources from which the chart was compiled. The quantity and quality of the sources vary due to age and the part of the world the chart depicts. The other 70 per cent are derived from information on foreign charts, and the Admiralty versions are designed to provide charts for ocean passage and landfall, and approach and entry to the major ports.
The series contains charts on many different scales, but can be divided very broadly as follows:
Route planning 1:10 million Ocean planning 1:3.5 million Coast approach or landfall identification 1:1 million Coasting 1:300,000 to 1:200,000 Intricate or congested coastal waters 1:150,000 to 1:75,000 Port approach 1:50,000 or larger Terminal installation 1:12,500 or larger
Charts on scales smaller than 1:50,000, except in polar regions, are on Mercator projection. Since 1978 all charts on 1:50,000 and larger have been produced on Transverse Mercator projection. Prior to 1978 larger scale charts were on a modified polyconic projection referred to as 'gnomonic', not to be confused with the true Gnomonic projection.
Most of the detail shown on a chart consists of hydrographic information - soundings (selected spot depths) in metres (on older charts in fathoms or feet) reduced to a stated vertical datum; depth contours; dredged channels; and the nature of the seabed and foreshore. Features which present hazards to navigation, fishing and other marine operations are also shown. These include underwater rocks and reefs; wrecks and obstructions; submarine cables and pipelines and offshore installations. Shallow water areas are usually highlighted with pale blue tint(s). Also shown are aids established to assist the navigator - buoys, beacons, lights, fog signals and radio position finding and reporting services; and information about traffic separation schemes, anchorages, tides, tidal streams and magnetic variation. Outline coastal topography is shown especially objects of use as fixing marks. As a base for navigation the chart carries compass roses, scales, horizontal datum information, graduation (and sometimes land map grids), conversion tables and tables of tidal and tidal stream rates.
Important Note: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This map is designed to be used as a general reference map for informational and educational purposes as well as a basemap by GIS professionals and other users for creating web maps and web mapping applications.The map was developed by National Geographic and Esri and reflects the distinctive National Geographic cartographic style in a multi-scale reference map of the world. The map was authored using data from a variety of leading data providers, including Garmin, HERE, UNEP-WCMC, NASA, ESA, USGS, and others.This reference map includes administrative boundaries, cities, protected areas, highways, roads, railways, water features, buildings and landmarks, overlaid on shaded relief and land cover imagery for added context. The map includes global coverage down to ~1:144k scale and more detailed coverage for North America down to ~1:9k scale.Map Note: Although small-scale boundaries, place names and map notes were provided and edited by National Geographic, boundaries and names shown do not necessarily reflect the map policy of the National Geographic Society, particularly at larger scales where content has not been thoroughly reviewed or edited by National Geographic.Data Notes: The credits below include a list of data providers used to develop the map. Below are a few additional notes:Reference Data: National Geographic, Esri, Garmin, HERE, iPC, NRCAN, METILand Cover Imagery: NASA Blue Marble, ESA GlobCover 2009 (Copyright notice: © ESA 2010 and UCLouvain)Protected Areas: IUCN and UNEP-WCMC (2011), The World Database on Protected Areas (WDPA) Annual Release. Cambridge, UK: UNEP-WCMC. Available at:www.protectedplanet.net.Ocean Data: GEBCO, NOAA