This map shows the extent of the various datasets comprising the World Elevation dynamic (Terrain, TopoBathy) and tiled (Terrain 3D, TopoBathy 3D, World Hillshade, World Hillshade (Dark)) services.The tiled services (Terrain 3D, TopoBathy 3D, World Hillshade, World Hillshade (Dark)) also include an additional data source from Maxar's Precision3D covering parts of the globe.Topography sources listed in the table below are part of Terrain, TopoBathy, Terrain 3D, TopoBathy 3D, World Hillshade and World Hillshade (Dark), while bathymetry sources are part of TopoBathy and TopoBathy 3D only. Data Source Native Pixel Size Approximate Pixel Size (meters) Coverage Primary Source Country/Region

Topography

Australia 1m 1 meter 1 Partial areas of Australia Geoscience Australia Australia

Moreton Bay, Australia 1m 1 meter 1 Moreton Bay region, Australia Moreton Bay Regional Council Australia

New South Wales, Australia 5m 5 meters 5 New South Wales State, Australia DFSI Australia

SRTM 1 arc second DEM-S 0.0002777777777779 degrees 31 Australia Geoscience Australia Australia

Burgenland 50cm 0.5 meters 0.5 Burgenland State, Austria Land Burgenland Austria

Upper Austria 50cm 0.5 meters 0.5 Upper Austria State, Austria Land Oberosterreich Austria

Austria 1m 1 meter 1 Austria BEV Austria

Austria 10m 10 meters 10 Austria BEV Austria

Wallonie 50cm 0.5 meters 0.5 Wallonie state, Belgium Service public de Wallonie (SPW) Belgium

Vlaanderen 1m 1 meter 1 Vlaanderen state, Belgium agentschap Digitaal Vlaanderen Belgium

Canada HRDEM 1m 1 meter 1 Partial areas of Canada Natural Resources Canada Canada

Canada HRDEM 2m 2 meter 2 Partial areas of the southern part of Canada Natural Resources Canada Canada

Denmark 40cm 0.4 meters 0.4 Denmark KDS Denmark

Denmark 10m 10 meters 10 Denmark KDS Denmark

England 1m 1 meter 1 England Environment Agency England

Estonia 1m 1 meter 1 Estonia Estonian Land Board Estonia

Estonia 5m 5 meters 5 Estonia Estonian Land Board Estonia

Estonia 10m 10 meters 10 Estonia Estonian Land Board Estonia

Finland 2m 2 meters 2 Finland NLS Finland

Finland 10m 10 meters 10 Finland NLS Finland

France 1m 1 meter 1 France IGN-F France

Bavaria 1m 1 meter 1 Bavaria State, Germany Bayerische Vermessungsverwaltung Germany

Berlin 1m 1 meter 1 Berlin State, Germany Geoportal Berlin Germany

Brandenburg 1m 1 meter 1 Brandenburg State, Germany GeoBasis-DE/LGB Germany

Hamburg 1m 1 meter 1 Hamburg State, Germany LGV Hamburg Germany

Hesse 1m 1 meter 1 Hesse State, Germany HVBG Germany

Nordrhein-Westfalen 1m 1 meter 1 Nordrhein-Westfalen State, Germany Land NRW Germany

Saxony 1m 1 meter 1 Saxony State, Germany Landesamt für Geobasisinformation Sachsen (GeoSN) Germany

Sachsen-Anhalt 2m 2 meters 2 Sachsen-Anhalt State, Germany LVermGeo LSA Germany

Hong Kong 50cm 0.5 meters 0.5 Hong Kong CEDD Hong Kong SAR

Italy TINITALY 10m 10 meters 10 Italy INGV Italy

Japan DEM5A *, DEM5B * 0.000055555555 degrees 5 Partial areas of Japan GSI Japan

Japan DEM10B * 0.00011111111 degrees 10 Japan GSI Japan

Latvia 1m 1 meters 1 Latvia Latvian Geospatial Information Agency Latvia

Latvia 10m 10 meters 10 Latvia Latvian Geospatial Information Agency Latvia

Latvia 20m 20 meters 20 Latvia Latvian Geospatial Information Agency Latvia

Lithuania 1m 1 meters 1 Lithuania NZT Lithuania

Lithuania 10m 10 meters 10 Lithuania NZT Lithuania

Netherlands (AHN3/AHN4) 50cm 0.5 meters 0.5 Netherlands AHN Netherlands

Netherlands (AHN3/AHN4) 10m 10 meters 10 Netherlands AHN Netherlands

New Zealand 1m 1 meters 1 Partial areas of New Zealand Land Information New Zealand (Sourced from LINZ. CC BY 4.0) New Zealand

Northern Ireland 10m 10 meters 10 Northern Ireland OSNI Northern Ireland

Norway 10m 10 meters 10 Norway NMA Norway

Poland 1m 1 meter 1 Partial areas of Poland GUGIK Poland

Poland 5m 5 meters 5 Partial areas of Poland GUGIK Poland

Scotland 1m 1 meter 1 Partial areas of Scotland Scottish Government et.al Scotland

Slovakia 1m 1 meter 1 Slovakia ÚGKK SR Slovakia

Slovakia 10m 10 meters 10 Slovakia GKÚ Slovakia

Slovenia 1m 1 meter 1 Slovenia ARSO Slovenia

Madrid City 1m 1 meter 1 Madrid city, Spain Ayuntamiento de Madrid Spain

Spain 2m (MDT02 2019 CC-BY 4.0 scne.es) 2 meters 2 Partial areas of Spain IGN Spain

Spain 5m 5 meters 5 Spain IGN Spain

Spain 10m 10 meters 10 Spain IGN Spain

Varnamo 50cm 0.5 meters 0.5 Varnamo municipality, Sweden Värnamo Kommun Sweden

Canton of Basel-Landschaft 25cm 0.25 meters 0.25 Canton of Basel-Landschaft, Switzerland Geoinformation Kanton Basel-Landschaft Switzerland

Grand Geneva 50cm 0.5 meters 0.5 Grand Geneva metropolitan, France/Switzerland SITG Switzerland and France

Switzerland swissALTI3D 50cm 0.5 meters 0.5 Switzerland and Liechtenstein swisstopo Switzerland and Liechtenstein

Switzerland swissALTI3D 10m 10 meters 10 Switzerland and Liechtenstein swisstopo Switzerland and Liechtenstein

OS Terrain 50 50 meters 50 United Kingdom Ordnance Survey United Kingdom

Douglas County 1ft 1 foot 0.3048 Douglas County, Nebraska, USA Douglas County NE United States

Lancaster County 1ft 1 foot 0.3048 Lancaster County, Nebraska, USA Lancaster County NE United States

Sarpy County 1ft 1 foot 0.3048 Sarpy County, Nebraska, USA Sarpy County NE United States

Cook County 1.5 ft 1.5 foot 0.46 Cook County, Illinois, USA ISGS United States

3DEP 1m 1 meter 1 Partial areas of the conterminous United States, Puerto Rico USGS United States

NRCS 1m 1 meter 1 Partial areas of the conterminous United States NRCS USDA United States

San Mateo County 1m 1 meter 1 San Mateo County, California, USA San Mateo County CA United States

FEMA LiDAR DTM 3 meters 3 Partial areas of the conterminous United States FEMA United States

NED 1/9 arc second 0.000030864197530866 degrees 3 Partial areas of the conterminous United States USGS United States

3DEP 5m 5 meter 5 Alaska, United States USGS United States

NED 1/3 arc second 0.000092592592593 degrees 10 conterminous United States, Hawaii, Alaska, Puerto Rico, and Territorial Islands of the United States USGS United States

NED 1 arc second 0.0002777777777779 degrees 31 conterminous United States, Hawaii, Alaska, Puerto Rico, Territorial Islands of the United States; Canada and Mexico USGS United States

NED 2 arc second 0.000555555555556 degrees 62 Alaska, United States USGS United States

Wales 1m 1 meter 1 Wales Welsh Government Wales

WorldDEM4Ortho 0.00022222222 degrees 24 Global (excluding the countries of Azerbaijan, DR Congo and Ukraine) Airbus Defense and Space GmbH World

SRTM 1 arc second 0.0002777777777779 degrees 31 all land areas between 60 degrees north and 56 degrees south except Australia NASA World

EarthEnv-DEM90 0.00083333333333333 degrees 93 Global N Robinson,NCEAS World

SRTM v4.1 0.00083333333333333 degrees 93 all land areas between 60 degrees north and 56 degrees south except Australia CGIAR-CSI World

GMTED2010 7.5 arc second 0.00208333333333333 degrees 232 Global USGS World

GMTED2010 15 arc second 0.00416666666666666 degrees 464 Global USGS World

GMTED2010 30 arc second 0.0083333333333333 degrees 928 Global USGS World

Bathymetry

Canada west coast 10 meters 10 Canada west coast Natural Resources Canada Canada

Gulf of Mexico 40 feet 12 Northern Gulf of Mexico BOEM Gulf of Mexico

MH370 150 meters 150 MH370 flight search area (Phase 1) of Indian Ocean Geoscience Australia Indian Ocean

Switzerland swissBATHY3D 1 - 3 meters 1, 2, 3 Lakes of Switzerland swisstopo Switzerland

NCEI 1/9 arc second 0.000030864197530866 degrees 3 Puerto Rico, U.S Virgin Islands and partial areas of eastern and western United States coast NOAA NCEI United States

NCEI 1/3 arc second 0.000092592592593 degrees 10 Partial areas of eastern and western United States coast NOAA NCEI United States

CRM 1 arc second (Version 2) 0.0002777777777779 degrees 31 Southern California coast of United States NOAA United States

NCEI 1 arc second 0.0002777777777779 degrees 31 Partial areas of northeastern United States coast NOAA NCEI United States

CRM 3 arc second 0.00083333333333333 degrees 93 United States Coast NOAA United States

NCEI 3 arc second 0.00083333333333333 degrees 93 Partial areas of northeastern United States coast NOAA NCEI United States

Abstract copyright UK Data Service and data collection copyright owner.

This research project aimed to fill a major lacuna militating against the effective exploitation of many post-medieval to mid-Victorian historical sources collected by local administrative areas: the lack of information on the boundaries of those administrative areas, the so-called 'historic' or 'ancient' parishes of England and Wales. It is known that these districts came into being during the Middle Ages, that the map of these ecclesiastical parishes was essentially complete by the fifteenth century, that these ecclesiastical boundaries were adopted during the early modern period for secular and judicial purposes, and that boundaries remained essentially unchanged until a number of reforms from the mid-nineteenth century onwards reorganised the local administrative geography of the country. The project aimed to reconstruct those boundaries as they were before the post-nineteenth century changes.
Main Topics:

The digitised maps cover the whole of England and Wales, and are organised by Ordnance Survey Sheet number. The maps contain a scanned bitmap image of the Ordnance Survey one inch to one mile (1:63,360) New Popular Edition maps (1945-8) with National Grid. They contain the boundaries of some 18,233 places, and are arranged as three electronic 'layers'. The first is a scan of the Ordnance Survey maps stored as grey tone sheet images. This enables Ordnance Survey physical, cultural and place-name content to be readily visible in the background for orientation and general location purposes, while not obscuring the added boundary and reference number material. The second layer consists of the boundaries, stored as solid red lines; and the third layer contains the reference numbers that link places on the map to the gazetteer/metadata dataset that accompanies the maps.

The maps are available on CD-ROM in Adobe Illustrator (ISBN:0-9540032-2-5) or Adobe Acrobat (ISBN:0-9540032-1-7) PDF formats. We recommend using the Adobe Illustrator format if you already have the software (as it enables you to edit the maps and select the layers to view). However, the Adobe Acrobat PDF format is perfectly suitable for viewing the maps, and we will supply the necessary reader software.

An accompanying book Historic Parishes of England and Wales: An Electronic Map of Boundaries before 1850 with a Gazetteer and Metadata by Roger Kain and Richard Oliver (ISBN:0-9540032-0-9) provides an introduction to the provenance of the maps. It also includes an abbreviated version of the gazetteer/metadata dataset, and a discussion of historical boundaries.

This unique combination publication is set to become a standard reference resource and is an invaluable tool for all those interested in plotting local area-based data from the past (population, agricultural, statistics, tax data etc.) from the fourteenth to the nineteenth centuries.

Please note: this study does not include information on named individuals and would therefore not be useful for personal family history research.

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.

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

This low-resolution image has been produced from BGS land and marine gravity data. The colour was generated using the BGS COLMAP software package. Colour levels are defined by histogram equalisation. Combining this image with the grey shaded relief image produces a similar image to the colour shaded relief image. The measured gravity values have been corrected in order to show the anomalies attributable to variations in crustal density. In broad terms the blues are attributable to large volumes of low density rocks, the reds to high density rocks. Significant lows occur, for instance, over areas of thick, low density sedimentary rocks(e.g. Cheshire Basin, Wessex Basin), or large granites (eg Cornwall). For marine data, free-air anomalies have been calculated from observed gravity values along marine survey lines. Line intersection errors between crossing lines and overlapping surveys have been used using network adjustment techniques. Free air anomalies have been calculated for sea-bottom stations. For land data, bouguer anomalies have been calculated from gravity observations at points of known height. In order to minimise the effect of topography, Bouguer corrections for the British Mainland have been applied using a density estimated for each station. Elsewhere a correction density of 2.67 Mg/m3 has been used. Corrections for the gravitational effect of terrain have been made where significant, and in a general extent to a radius of 48.6km. The data have been interpolated onto a 1km x 1km grid using a variable tension technique, and smoothed.

This low-resolution image has been produced from BGS airborne and marine magnetic data. The colour was generated using the BGS COLMAP software package. Colour levels are defined by histogram equalisation. Combining this image with the grey shaded relief image produces a similar image to the colour shaded relief image. A published coloured shaded relief map, using the full resolution of the data and produced at a scale of 1: 1500 000, is available. The map covers a larger area than this image, and includes additional data from other sources. The data used to compile this image are available in various forms for academic and commercial licensing. The data from surveys covering the UK mainland have been digitised from their original analogue form. Elsewhere data were acquired digitally. Standard methods of processing were used to remove diurnal and secular variations and to minimise line intersection errors. While efforts have been made to remove artefacts from the data, some may remain between adjacent datasets. Generally anomalies over man-made structures have not been removed. The data have been interpolated onto a 1km x 1km grid using a variable tension technique, and smoothed.

This low-resolution image has been produced from BGS airborne and marine magnetic data. The colour was generated using the BGS COLMAP software package. Colour levels are defined by histogram equalisation. Combining this image with the grey shaded relief image produces a similar image to the colour shaded relief image. A published coloured shaded relief map, using the full resolution of the data and produced at a scale of 1: 1500 000, is available. The map covers a larger area than this image, and includes additional data from other sources. The data used to compile this image are available in various forms for academic and commercial licensing. The data from surveys covering the UK mainland have been digitised from their original analogue form. Elsewhere data were acquired digitally. Standard methods of processing were used to remove diurnal and secular variations and to minimise line intersection errors. While efforts have been made to remove artefacts from the data, some may remain between adjacent datasets. Generally anomalies over man-made structures have not been removed. The data have been interpolated onto a 1km x 1km grid using a variable tension technique, and smoothed. This layer is only available at specific zoom levels. Please zoom to a larger scale to interrogate the map.

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. The first complete coverage of Great Britain at the half-inch scale was achieved by 1903, and this is the layer shown here.The half-inch maps were distinctive for using different layers of colour to represent landscape relief. A subtle and innovative gradation of colour bands were employed for land at different heights. Lighter greens were used for low ground closest to sea-level, darker greens and browns for higher ground, with white used for mountain tops. Whilst layer colouring had been developed in Germany from the 1860s, Bartholomew's development of it was both innovative and influential. John Bartholomew junior (1831-1893) first used the firm's trademark layer colouring in Baddeley’s Thorough Guide to the English Lake District (1880). His son, John George Bartholomew (1860-1920), later went on to refine the style. You can see Bartholomew’s continued experimentation with layer colour palettes in the Cairngorms layer colour explorer ( http://geo.nls.uk/maps/bartholomew/layers/ )

Bartholomew based their half-inch maps on more detailed Ordnance Survey mapping at one-inch to the mile (1:63,360). The firm had published 'Reduced Ordnance Maps' of Scotland, England and Wales at this scale from the 1890s. These maps were progressively revised and updated with new information. 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:

● Scotland: https://maps.nls.uk/series/bart_half_scotland.html

● England and Wales: https://maps.nls.uk/series/bart_half_england.html

Spatial coverage index compiled by East View Geospatial of set "United Kingdom OS MasterMap - Sites Layer (part of topography layer)". Source data from OSI (publisher). Type: Topographic. Scale: Varies. Region: Europe.

Satellite-derived data and data used for satellite data validation from the SWOT-UK project. Validation sea level elevation data are from tide gauges re-referenced to ETRS89 (WGS84) This data covers the Bristol Channel, Severn estuary and river Severn. The bulk of the data spans the period from the beginning of 2022 to the end of July 2023, but the data used for the validation of the Cryosat2 satellite goes back to 2012. These data came from the Environment Agency and National Network of Regional Coastal Monitoring Programmes (Channel Coastal Observatory) APIs, with three addition Global Navigation Satellite Systems Interferometric Reflectometry (GNSS-IR) systems installed by the project team. The data were transformed to ETRS89 (WGS84) Ellipsoid using a software utility provided by the Ordnance Survey, for comparison to satellite altimetry data. Stations measuring relative to chart or stage datum were corrected to ordnance datum before transformation to ETRS89 (WGS84). The data are supplied as water surface elevation (altitude) in metres, relative to ETRS89 (WGS84) Ellipsoid. These real-time in situ data have not been corrected for atmospheric pressure, to match the total water level measurements of the satellite.

This map shows the extents of the various datasets comprising the World Elevation dynamic (Terrain, TopoBathy) and tiled (Terrain 3D, TopoBathy 3D, World Hillshade, World Hillshade (Dark)) services.The map has pop-ups defined. Click anywhere on the map to reveal details about the data sources.Topography sources listed in the table below are part of Terrain, TopoBathy, Terrain 3D, TopoBathy 3D, World Hillshade and World Hillshade (Dark), while bathymetry sources are part of TopoBathy and TopoBathy 3D only. Data Source Native Pixel Size Approximate Pixel Size (meters) Coverage Primary Source Country/Region

Topography

Australia 1m 1 meter 1 Partial areas of Australia Geoscience Australia Australia

Moreton Bay, Australia 1m 1 meter 1 Moreton Bay region, Australia Moreton Bay Regional Council Australia

New South Wales, Australia 5m 5 meters 5 New South Wales State, Australia DFSI Australia

SRTM 1 arc second DEM-S 0.0002777777777779 degrees 31 Australia Geoscience Australia Australia

Burgenland 50cm 0.5 meter 0.5 Burgenland State, Austria Land Burgenland Austria

Upper Austria 50cm 0.5 meter 0.5 Upper Austria State, Austria Land Oberosterreich Austria

Austria 1m 1 meter 1 Austria BEV Austria

Austria 10m 10 meters 10 Austria Geoland Austria

Canada HRDEM 1m 1 meter 1 Partial areas of the southern part of Canada Natural Resources Canada Canada

Canada HRDEM 2m 2 meters 2 Partial areas of the southern part of Canada Natural Resources Canada Canada

Denmark 40cm 0.4 meter 0.4 Denmark SDFE Denmark

Denmark 10m 10 meters 10 Denmark SDFE Denmark

England 2m 2 meters 2 70 % of England Environment Agency England

Estonia 1m 1 meter 1 Estonia Estonian Land Board Estonia

Estonia 5m 5 meters 5 Estonia Estonian Land Board Estonia

Estonia 10m 10 meters 10 Estonia Estonian Land Board Estonia

Finland 2m 2 meters 2 Finland NLS Finland

Finland 10m 10 meters 10 Finland NLS Finland

Berlin 1m 1 meter 1 Berlin State, Germany Geoportal Berlin Germany

Hamburg 1m 1 meter 1 Hamburg State, Germany LGV Hamburg Germany

Nordrhein-Westfalen 1m 1 meter 1 Nordrhein-Westfalen State, Germany Land NRW Germany

Sachsen-Anhalt 2m 2 meters 2 Sachsen-Anhalt State, Germany LVermGeo LSA Germany

Hong Kong 50cm 0.5 meter 0.5 Hong Kong CEDD Hong Kong SAR

Italy TINITALY 10m 10 meters 10 Italy INGV Italy

Japan DEM5A *, DEM5B * 0.000055555555 degrees 5 Partial areas of Japan GSI Japan

Japan DEM10B * 0.00011111111 degrees 10 Japan GSI Japan

Latvia 1m 1 meter 1 Latvia Latvian Geospatial Information Agency Latvia

Latvia 10m 10 meters 10 Latvia Latvian Geospatial Information Agency Latvia

Latvia 20m 20 meters 20 Latvia Latvian Geospatial Information Agency Latvia

Lithuania 1m 1 meter 1 Lithuania NZT Lithuania

Lithuania 10m 10 meters 10 Lithuania NZT Lithuania

Netherlands (AHN3/AHN4) 50cm 0.5 meter 0.5 Netherlands AHN Netherlands

Netherlands (AHN3/AHN4) 10m 10 meters 10 Netherlands AHN Netherlands

New Zealand 1m 1 meter 1 Partial areas of New Zealand Land Infromation New Zealand (Sourced from LINZ. CC BY 4.0) New Zealand

Northern Ireland 10m 10 meters 10 Northern Ireland OSNI Northern Ireland

Norway 10m 10 meters 10 Norway NMA Norway

Poland 1m 1 meter 1 Partial areas of Poland GUGIK Poland

Poland 5m 5 meters 5 Partial areas of Poland GUGIK Poland

Scotland 1m 1 meter 1 Partial areas of Scotland Scottish Government et.al Scotland

Slovakia 10m 10 meters 10 Slovakia GKÚ Slovakia

Slovenia 1m 1 meter 1 Slovenia ARSO Slovenia

Madrid City 1m 1 meter 1 Madrid city, Spain Ayuntamiento de Madrid Spain

Spain 2m (MDT02 2019 CC-BY 4.0 scne.es) 2 meters 2 Partial areas of Spain IGN Spain

Spain 5m 5 meters 5 Spain IGN Spain

Spain 10m 10 meters 10 Spain IGN Spain

Varnamo 50cm 0.5 meter 0.5 Varnamo municipality, Sweden Värnamo Kommun Sweden

Canton of Basel-Landschaft 25cm 0.25 meter 0.25 Canton of Basel-Landschaft, Switzerland Geoinformation Kanton Basel-Landschaft Switzerland

Grand Geneva 50cm 0.5 meter 0.5 Grand Geneva metropolitan, France/Switzerland SITG Switzerland and France

Switzerland swissALTI3D 50cm 0.5 meter 0.5 Switzerland and Liechtenstein swisstopo Switzerland and Liechtenstein

Switzerland swissALTI3D 10m 10 meters 10 Switzerland and Liechtenstein swisstopo Switzerland and Liechtenstein

OS Terrain 50 50 meters 50 United Kingdom Ordnance Survey United Kingdom

3DEP 1m 1 meter 1 Partial areas of the conterminous United States, Puerto Rico USGS United States

NRCS 1m 1 meter 1 Partial areas of the conterminous United States NRCS USDA United States

FEMA LiDAR DTM 3 meters 3 Partial areas of the conterminous United States FEMA United States

NED 1/9 arc second 0.000030864197530866 degrees 3 Partial areas of the conterminous United States USGS United States

3DEP 5m 5 meters 5 Alaska, United States USGS United States

NED 1/3 arc second 0.000092592592593 degrees 10 conterminous United States, Hawaii, Alaska, Puerto Rico, and Territorial Islands of the United States USGS United States

NED 1 arc second 0.0002777777777779 degrees 31 conterminous United States, Hawaii, Alaska, Puerto Rico, Territorial Islands of the United States; Canada and Mexico USGS United States

NED 2 arc second 0.000555555555556 degrees 62 Alaska, United States USGS United States

Wales 2m 2 meters 2 70 % of Wales Natural Resources Wales Wales

WorldDEM4Ortho 0.00022222222 degrees 24 Global (excluding the countries of Azerbaijan, DR Congo and Ukraine) Airbus Defense and Space GmbH World

SRTM 1 arc second 0.0002777777777779 degrees 31 all land areas between 60 degrees north and 56 degrees south except Australia NASA World

EarthEnv-DEM90 0.00083333333333333 degrees 93 Global N Robinson,NCEAS World

SRTM v4.1 0.00083333333333333 degrees 93 all land areas between 60 degrees north and 56 degrees south except Australia CGIAR-CSI World

GMTED2010 7.5 arc second 0.00208333333333333 degrees 232 Global USGS World

GMTED2010 15 arc second 0.00416666666666666 degrees 464 Global USGS World

GMTED2010 30 arc second 0.0083333333333333 degrees 928 Global USGS World

Bathymetry

Canada west coast 10 meters 10 Canada west coast Natural Resources Canada Canada

Gulf of Mexico 40 feet 12 Northern Gulf of Mexico BOEM Gulf of Mexico

MH370 150 meters 150 MH370 flight search area (Phase 1) of Indian Ocean Geoscience Australia Indian Ocean

Switzerland swissBATHY3D 1 - 3 meters 1, 2, 3 Lakes of Switzerland swisstopo Switzerland

NCEI 1/9 arc second 0.000030864197530866 degrees 3 Puerto Rico, U.S Virgin Islands and partial areas of eastern and western United States coast NOAA NCEI United States

NCEI 1/3 arc second 0.000092592592593 degrees 10 Partial areas of eastern and western United States coast NOAA NCEI United States

CRM 1 arc second (Version 2) 0.0002777777777779 degrees 31 Southern California coast of United States NOAA United States

NCEI 1 arc second 0.0002777777777779 degrees 31 Partial areas of northeastern United States coast NOAA NCEI United States

CRM 3 arc second 0.00083333333333333 degrees 93 United States Coast NOAA United States

NCEI 3 arc second 0.00083333333333333 degrees 93 Partial areas of northeastern United States coast NOAA NCEI United States

USGS CoNED 1 - 3 meters 1, 2, 3 Partial coastal areas of eastern and western United States USGS United States

GEBCO 2021 ** 0.00416666666666666 degrees 464 Global GEBCO World

GEBCO 2014 0.0083333333333333 degrees 928 Global GEBCO World * Fundamental Geospatial Data provided by GSI with Approval Number JYOU-SHI No.1239 2016. ** GEBCO Compilation Group (2021) GEBCO 2021 Grid (doi:10.5285/c6612cbe-50b3-0cff-e053-6c86abc09f8f) *** Bathymetry datasets are part of TopoBathy and TopoBathy3D services only.Disclaimer: Data sources are not to be used for navigation/safety at sea and in air.

River elevation and catchment area data for major rivers in Calabria, Italy (one river profile in each file). Data were extracted from 1 arc second SRTM (Shuttle Radar Topography Mission) Digital Elevation Models using the Arc GIS hydrology toolbox between October 2015 and October 2019. These river profiles were acquired for fluvial inversion to calculate rock uplift in Calabria.

OS MasterMap Topography Layer is the most detailed and accurate view of Great Britain's landscape. It includes features representing the manmade and natural environment, including: roads, tracks and paths; land cover; buildings; water; rail; height;heritage; structures and; administrative boundaries. All features are assigned a unique Topographic Identifier (TOID).

The Fluxes Across Sloping Topography of the North East Atlantic (FASTNEt) data set comprises a diverse collection of oceanographic (largely physical and chemical) observations, together with model simulation output. FASTNEt data were collected from three principal localities in close proximity to the UK’s Shelf Edge – the Celtic Sea, the Malin Shelf and the North Scotland Shelf. Each of these were chosen for contrasting bathymetric properties and associated slope current characteristics. There were two main research cruises associated with FASTNEt. These took place in the summers of 2012 and 2013. The core observations include measurements of temperature, salinity, nutrients, currents and shear harvested from a suite of instrumentation including CTDs, ocean gliders (as well as other Autonomous Underwater Vehicles), drifter buoys and moored sensors. The FASTNEt data set aims to develop new parameterisations of shelf edge exchange processes, which will benefit future ocean modelling and forecasting exercises. Additional observations were made from moored instrumentation and autonomous platforms (including ocean gliders, AUVs and drifter buoys) adding to the temporal and spatial coverage of the core cruise data sets. The FASTNEt data set was compiled in order to improve understanding of the processes of physical and biogeochemical exchange at shelf edge margins. These margins are important gateways for the supply of nutrients to our shallow shelf seas, with implications for biodiversity and fishery resources. The NERC FASTNEt Consortium brings together scientists from various UK research centres including the Scottish Association for Marine Science (SAMS), National Oceanography Centre (NOC) and the Universities of Bangor, Liverpool and Plymouth.

Living England is a multi-year project which delivers a broad habitat map for the whole of England, created using satellite imagery, field data records and other geospatial data in a machine learning framework. The Living England habitat map shows the extent and distribution of broad habitats across England aligned to the UKBAP classification, providing a valuable insight into our natural capital assets and helping to inform land management decisions. Living England is a project within Natural England, funded by and supports the Defra Natural Capital and Ecosystem Assessment (NCEA) Programme and Environmental Land Management (ELM) Schemes to provide an openly available national map of broad habitats across England.This dataset includes very complex geometry with a large number of features so it has a default viewing distance set to 1:80,000 (City in the map viewer).Process Description:A number of data layers are used to develop a ground dataset of habitat reference data, which are then used to inform a machine-learning model and spatial analyses to generate a map of the likely locations and distributions of habitats across England. The main source data layers underpinning the spatial framework and models are Sentinel-2 and Sentinel-1 satellite data from the ESA Copernicus programme, Lidar from the EA's national Lidar Programme and collected data through the project's national survey programme. Additional datasets informing the approach as detailed below and outlined in the accompanying technical user guide.Datasets used:OS MasterMap® Topography Layer; Geology aka BGS Bedrock Mapping 1:50k; Long Term Monitoring Network; Uplands Inventory; Coastal Dune Geomatics Mapping Ground Truthing; Crop Map of England (RPA) CROME; Lowland Heathland Survey; National Grassland Survey; National Plant Monitoring Scheme; NE field Unit Surveys; Northumberland Border Mires Survey; Sentinel-2 multispectral imagery; Sentinel-1 backscatter imagery; Sentinel-1 single look complex (SLC) imagery; National forest inventory (NFI); Cranfield NATMAP; Agri-Environment HLS Monitoring; Living England desktop validation; Priority Habitat Inventory; Space2 Eye Lens: Ainsdale NNR, State of the Bog Bowland Survey, State of the Bog Dark Peak Condition Survey, State of the Bog Manchester Metropolitan University (MMU) Mountain Hare Habitat Survey Dark Peak, State of the Bog; Moors for the Future Dark Peak Survey; West Pennines Designation NVC Survey; Wetland Annex 1 inventory; Soils-BGS Soil Parent Material; Met Office HadUK gridded climate product; Saltmarsh Extent and Zonation; EA LiDAR DSM & DTM; New Forest Mires Wetland Survey; New Forest Mires Wetland Survey; West Cumbria Mires Survey; England Peat Map Vegetation Surveys; NE protected sites monitoring; ERA5; OS Open Built-up Areas; OS Boundaries dataset; EA IHM (Integrated height model) DTM; OS VectorMap District; EA Coastal Flood Boundary: Extreme Sea Levels; AIMS Spatial Sea Defences; LIDAR Sand Dunes 2022; EA Coastal saltmarsh species surveys; Aerial Photography GB (APGB); NASA SRT (Shuttle Radar Topography Mission) M30; Provisional Agricultural Land Classification; Renewable Energy Planning Database (REPD); Open Street Map 2024.Attribute descriptions: Column Heading Full Name Format Description

SegID SegID Character (100) Unique Living England segment identifier. Format is LEZZZZ_BGZXX_YYYYYYY where Z = release year (2223 for this version), X = BGZ and Y = Unique 7-digit number

Prmry_H Primary_Habitat Date Primary Living England Habitat

Relblty Reliability
Character (12) Reliability Metric Score

Mdl_Hbs Model_Habs Interger List of likely habitats output by the Random Forest model.

Mdl_Prb Model_Probs Double (6,2) List of probabilities for habitats listed in ‘Model_Habs’, calculated by the Random Forest model.

Mixd_Sg Mixed_Segment Character (50) Indication of the likelihood a segment contains a mixture of dominant habitats. Either Unlikely or Probable.

Source Source

Description of how the habitat classification was derived. Options are: Random Forest; Vector OSMM Urban; Vector Classified OS Water; Vector EA saltmarsh; LE saltmarsh & QA; Vector RPA Crome, ALC grades 1-4; Vector LE Bare Ground Analysis; LE QA Adjusted

SorcRsn Source_Reason

Reasoning for habitat class adjustment if ‘Source’ equals ‘LE QA Adjusted’

Shap_Ar Shape_Area

Segment area (m2) Full metadata can be viewed on data.gov.uk.

ESYS plc and the Department of Geomatic Engineering at University College London (UCL) have been funded by the British National Space Centre (BNSC) to develop a web GIS service to serve geographic data derived from remote sensing datasets. Funding was provided as part of the BNSC International Co-operation Programme 2 (ICP-2).

Particular aims of the project were to:

1. use Open Geospatial Consortium (OGC, recently renamed from the OpenGIS Consortium) technologies for map and data serving;

2. serve datasets for Europe and Africa, particularly Landsat TM and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data;

3. provide a website giving access to the served data;

4. provide software scripts, etc., and a document reporting the data processing and software set-up methods developed during the project.

ICEDS was inspired in particular by the Committee on Earth Observing Satellites (CEOS) CEOS Landsat and SRTM Project (CLASP) proposal. An express intention of ICEDS (aim 4 in the list above) was therefore that the solution developed by ESYS and UCL should be redistributable, for example, to other CEOS members. This was taken to mean not only software scripts but also the methods developed by the project team to prepare the data and set up the server. In order to be compatible with aim 4, it was also felt that the use of Open Source, or at least 'free-of-cost' software for the Web GIS serving was an essential component. After an initial survey of the Web GIS packages available at the time , the ICEDS team decided to use the Deegree package, a free software initiative founded by the GIS and Remote Sensing unit of the Department of Geography, University of Bonn , and lat/lon . However the Red Spider web mapping software suite was also provided by IONIC Software - this is a commercial web mapping package but was provided pro bono by IONIC for this project and has been used in parallel to investigate the possibilities and limitations opened up by using a commercial package.

http://iceds.ge.ucl.ac.uk/

ASCII XYZ point cloud data for a portion of the environs of Anegada, British Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected March 19-20, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 55 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 0.5-1.6 meters. The nominal vertical elevation accuracy expressed as the root mean square error (RMSE) is 20 centimeters. A peak sampling rate of 15-30 kilohertz results in an extremely dense spatial elevation dataset. More than 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

Dataset contains Terrestrial laser scanner (TLS) and CT scan data collected during fieldwork on a small gravel-bed river. TLS data show the river bed surface topography collected at five intervals between September 2014 and October 2018. CT scan data show the 3D structure of sections of the river bed. CT data has been processed to segment the images into gravel grains and fine-grained matrix.

ග න ව ග න ඉත හ සය ග න භ ව තය ග ල ය ග න භ ව තයම ම ප රදස න හ ව ශ ලත වය 388 600 ප ක සල අන ක ත ව භ දනයන 155 240 ප ක සල 310 4

description: ASCII XYZ point cloud data for a portion of the environs of Anegada, British Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected March 19-20, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 55 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 0.5-1.6 meters. The nominal vertical elevation accuracy expressed as the root mean square error (RMSE) is 20 centimeters. A peak sampling rate of 15-30 kilohertz results in an extremely dense spatial elevation dataset. More than 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.; abstract: ASCII XYZ point cloud data for a portion of the environs of Anegada, British Virgin Islands, was produced from remotely sensed, geographically referenced elevation measurements collected March 19-20, 2014 by the U.S. Geological Survey. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 55 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 0.5-1.6 meters. The nominal vertical elevation accuracy expressed as the root mean square error (RMSE) is 20 centimeters. A peak sampling rate of 15-30 kilohertz results in an extremely dense spatial elevation dataset. More than 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.