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

LIDAR is an airborne terrain mapping system, which uses a laser to measure the distance between the aircraft and the ground. This technique results in the production of cost effective terrain maps with a height accuracy of 10 to 15cm. Typically with spot heights between 1 to 4 metres spatially on the land surface. CASI is used to provide information on the colour of the environment. It is designed to provide a flexible system which is easy to transport and straightforward to install and operate in small aircraft. It can be used for detailed studies of the spectral characteristics of ground or water targets, which are imaged instantaneously in a large number of spectral wavebands (up to 288), covering the visible and near infra-red regions of the spectrum, between 430 nm and 870 nm. Spatial resolution can be varied from one to ten metres, depending on the flying altitude and lens configuration. New LIDAR and CASI data sets are being gathered from parts of England and Wales all the time. For details on coverage and extent contact the National Centre.

How would you define the boundaries of a town or city in England and Wales in 2016?

Maybe your definition would be based on its population size, geographic extent or where the industry and services are located. This was a question the ONS had to consider when creating a new statistical geography called Towns and Cities.

In reality, the ability to delimit the boundaries of a city or town is difficult!

Major Towns and Cities

The new statistical geography, Towns and Cities has been created based on population size and the extent of the built environment. It contains 112 towns and cities in England and Wales, where the residential and/or workday population > 75,000 people at the 2011 Census. It has been constructed using the existing Built-Up Area boundary set produced by Ordnance Survey in 2011.

This swipe map shows where the towns and cities and built-up areas are different. Just swipe the bar from left to right.

The blue polygons are the towns and cities and the purple polygons are the built-up areas.

The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering ~99% of England at 1m spatial resolution.The DTM (Digital Terrain Model) is produced from the last or only laser pulse returned to the sensor. We remove surface objects from the Digital Surface Model (DSM), using bespoke algorithms and manual editing of the data, to produce a terrain model of just the surface. Produced by the Environment Agency in 2022, the DTM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged. The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.DEFRA Data Services Platform Metadata URLDefra Network WMS server provided by the Environment Agency

PLEASE NOTE: This data product is not available in Shapefile format or KML at https://naturalengland-defra.opendata.arcgis.com/datasets/Defra::living-england-habitat-map-phase-4/about, as the data exceeds the limits of these formats. Please select an alternative download format.This data product is also available for download in multiple formats via the Defra Data Services Platform at https://environment.data.gov.uk/explore/4aa716ce-f6af-454c-8ba2-833ebc1bde96?download=true.The Living England project, led by Natural England, is a multi-year programme delivering a satellite-derived national habitat layer in support of the Environmental Land Management (ELM) System and the Natural Capital and Ecosystem Assessment (NCEA) Pilot. The project uses a machine learning approach to image classification, developed under the Defra Living Maps project (SD1705 – Kilcoyne et al., 2017). The method first clusters homogeneous areas of habitat into segments, then assigns each segment to a defined list of habitat classes using Random Forest (a machine learning algorithm). The habitat probability map displays modelled likely broad habitat classifications, trained on field surveys and earth observation data from 2021 as well as historic data layers. This map is an output from Phase IV of the Living England project, with future work in Phase V (2022-23) intending to standardise the methodology and Phase VI (2023-24) to implement the agreed standardised methods.The Living England habitat probability map will provide high-accuracy, spatially consistent data for a range of Defra policy delivery needs (e.g. 25YEP indicators and Environment Bill target reporting Natural capital accounting, Nature Strategy, ELM) as well as external users. As a probability map, it allows the extrapolation of data to areas that we do not have data. These data will also support better local and national decision making, policy development and evaluation, especially in areas where other forms of evidence are unavailable. Process Description: A number of data layers are used to inform the model to provide a habitat probability map of England. The main sources layers are Sentinel-2 and Sentinel-1 satellite data from the ESA Copericus programme. Additional datasets were incorporated into the model (as detailed below) to aid the segmentation and classification of specific habitat classes. Datasets used:Agri-Environment Higher Level Stewardship (HLS) Monitoring, British Geological Survey Bedrock Mapping 1:50k, Coastal Dune Geomatics Mapping Ground Truthing, Crop Map of England (RPA), Dark Peak Bog State Survey, Desktop Validation and Manual Points, EA Integrated Height Model 10m, EA Saltmarsh Zonation and Extent, Field Unit NEFU, Living England Collector App NEFU/EES, Long Term Monitoring Network (LTMN), Lowland Heathland Survey, National Forest Inventory (NFI), National Grassland Survey, National Plant Monitoring Scheme, NEFU Surveys, Northumberland Border Mires, OS Vector Map District , Priority Habitats Inventory (PHI) B Button, European Space Agency (ESA) Sentinel-1 and Sentinel-2 , Space2 Eye Lens: Ainsdale NNR, Space2 Eye Lens: State of the Bog Bowland Survey, Space2 Eye Lens: State of the Bog Dark Peak Condition Survey, Space2 Eye Lens: State of the Bog (MMU) Mountain Hare Habitat Survey Dark Peak, Uplands Inventory, West Pennines Designation NVC Survey, Wetland Inventories, WorldClim - Global Climate DataFull metadata can be viewed on data.gov.uk.

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.

The 1:63 360 / 1:50 000 scale map series are the most useful scale for most purposes. They provide almost complete coverage of onshore Great Britain. The BGS collection of 1:63 360 and 1:50 000 scale maps comprises two map series: - Geological Survey of England and Wales 1:63 360 / 1:50 000 Geological Map Series [New Series]. These maps are based on the Ordnance Survey One-inch New Series topographic basemaps and provide almost complete coverage of England and Wales, with the exception of sheet 180 (Knighton). The quarter-sheets of 1:63 360 Old Series sheets 91 to 110 coincide with sheets 1 to 73 of the New Series maps. These earlier maps often carry two sheet numbers which refer to the Old Series and the New Series. - Geological Survey of Scotland 1:63 360 / 1:50 000 Geological Map Series. These maps are based on the Ordnance Survey First, Second, Third and Fourth editions of the One-inch map of Scotland. The maps used the most recent topographic basemap available at the time. In the Western Isles, one-inch mapping was abandoned and replaced by maps at 1:100 000 scale, which are associated with this series. Sheets were traditionally issued at 1:63 360 scale, with the first 1:50 000 maps appearing in 1972. Sheets at 1:50 000 scale may be either facsimile enlargements of an existing 1:63 360 sheets, or may contain new geology and cartography. The latter bear the additional series designation '1:50 000 series'. Within the Scottish series, new mapping at 1:50 000 scale was split into east and west sheets. For example, the original one-inch sheet 32 became 1:50 000 sheets 32E and 32W. A number of irregular sheets were also introduced with the new 1:50 000 scale mapping. There are a number of irregular special sheets within both series. Geological maps represent a geologist's compiled interpretation of the geology of an area. A geologist will consider the data available at the time, including measurements and observations collected during field campaigns, as well as their knowledge of geological processes and the geological context to create a model of the geology of an area. This model is then fitted to a topographic basemap and drawn up at the appropriate scale, with generalization if necessary, to create a geological map, which is a representation of the geological model. Explanatory notes and vertical and horizontal cross sections may be published with the map. Geological maps may be created to show various aspects of the geology, or themes. The most common map themes held by BGS are solid (later referred to as bedrock) and drift (later referred to as superficial). These maps are, for the most part, hard-copy paper records stored in the National Geoscience Data Centre (NGDC) and are delivered as digital scans through the BGS website.

A Digital Terrain Model (DTM) is a digital file consisting of a grid of regularly spaced points of known height which, when used with other digital data such as maps or orthophotographs, can provide a 3D image of the land surface. 10m and 50m DTM’s are available. This is a large dataset and will take sometime to download. Please be patient. This service is published for OpenData. By download or use of this dataset you agree to abide by the LPS Open Government Data Licence.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

Complete Antarctic contour dataset, split and labelled according to whether the contour represents an ice or rock surface. Data have been prepared from various map and remotely sensed datasets. Due to the differing sources, this dataset has inconsistent intervals between contour lines. Certain regions contain very detailed contours obtained from VHR elevation models and photogrammetry work. Further information regarding source and source data can be found within the attribute table. Certain inconsistencies and errors are currently known and a comprehensive update is planned for version 7.3.

This is a web map service (WMS) of Digital Terrain Model (DTM) data in South West England at a 1m resolution. The DTM covers an area of 9424 km2 that includes all the land west of Exmouth (i.e. west of circa 3 degrees 21 minutes West). The DTM represents the topographic model (height) of the bare earth. The dataset is a part of outcomes from the Centre for Ecology & Hydrology South West (SW) Project.

This webmap combines the GB Topographic style with the GB Hillshade service.The labels are in local language providing Welsh, Scottish Gaelic and local English names where they are available.Customise this MapBecause this is a vector tile layer, you can customise the map to change its content and symbology. You are able to turn on and off layers and change their symbols. You can open this style in the vector tile style editor, make your changes and save a copy of your modified style to use yourself.As the GB Topographic style is designed to be used in conjunction with the GB Hillshade, it is recommended that after creating you own style you combine it in a webmap with Hillshade service.The map is based primarily on OS Zoomstack data (December 2024)Please send any feedback to marketplacedata@esriuk.com.

The Vector Map (VMap) Level 0 database represents the fifth edition of the Digital Chart of the World. The third/fourth edition was published in 199701. The product is dual named to show its lineage to the original DCW, published in 1992, while positioning the revised product within a broader family of VMap products. VMap Level 0 (VMap0) is a comprehensive 1:1,000,000 scale vector basemap of the world. It consists of cartographic, attribute, and textual data stored on compact disc read only memory (CDROM). The primary source for the database is the National Imagery and Mapping Agency's (NIMA) Operational Navigation Chart (ONC) series. This is the largest scale unclassified map series in existence that provides consistent, continuous global coverage of essential basemap features. The database contains more than 1,900 megabytes of vector data and is organized into 10 thematic layers. The data include major road and rail networks, major hydrologic drainage systems, major utility networks (cross-country pipelines and communication lines), all major airports, elevation contours (metric equivalent of 1000 foot (ft), with 500ft and 250ft supplemental contours), coastlines, international and first order boundaries and populated places. This dataset contains data from the eurasia CD and covers north/western Europe incl. UK. Purpose: The VMap0 is a general purpose global database designed to support Geographic Information Systems applications. This dataset was downloaded as VMap Level 0 data from the NGA 'geoengine' website using the NGA Raster Roam tool (http://geoengine.nga.mil/geospatial/SW_TOOLS/NIMAMUSE/webinter/rast_roam.html). The VMap data was loaded into CadCorp MapModeller and exported as Shapefiles using CadCorp. The field names were edited in ArcMap to remove spaces. The specification of the data and other metadata are included in the Zip file in the Metadata folder. The data is in the WGS 84 coordinate system. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-06-30 and migrated to Edinburgh DataShare on 2017-02-21.

Coastline for Antarctica created from various mapping and remote sensing sources, consisting of the following coast types: ice coastline, rock coastline, grounding line, ice shelf and front, ice rumple, and rock against ice shelf. Covering all land and ice shelves south of 60°S. Suitable for topographic mapping and analysis. High resolution versions of ADD data are suitable for scales larger than 1:1,000,000. The largest suitable scale is changeable and dependent on the region.

Major changes in v7.5 include updates to ice shelf fronts in the following regions: Seal Nunataks and Scar Inlet region, the Ronne-Filchner Ice Shelf, between the Brunt Ice Shelf and Riiser-Larsen Peninsula, the Shackleton and Conger ice shelves, and Crosson, Thwaites and Pine Island. Small areas of grounding line and ice coastlines were also updated in some of these regions as needed.

Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research.

Further information and useful links

Map projection: WGS84 Antarctic Polar Stereographic, EPSG 3031. Note: by default, opening this layer in the Map Viewer will display the data in Web Mercator. To display this layer in its native projection use an Antarctic basemap.

The currency of this dataset is May 2022 and will be reviewed every 6 months. This feature layer will always reflect the most recent version.

For more information on, and access to other Antarctic Digital Database (ADD) datasets, refer to the SCAR ADD data catalogue.

A related medium resolution dataset is also published via Living Atlas, as well medium and high resolution polygon datasets.

For background information on the ADD project, please see the British Antarctic Survey ADD project page.

Lineage

Dataset compiled from a variety of Antarctic map and satellite image sources. The dataset was created using ArcGIS and QGIS GIS software programmes and has been checked for basic topography and geometry checks, but does not contain strict topology. Quality varies across the dataset and certain areas where high resolution source data were available are suitable for large scale maps whereas other areas are only suitable for smaller scales. Each line has attributes detailing the source which can give the user further indications of its suitability for specific uses. Attributes also give information including 'surface' (e.g. grounding line, ice coastline, ice shelf front) and revision date. Compiled from sources ranging in time from 1990s-2022 - individual lines contain exact source dates.

The map allows you to pick any location of interest and quickly and simply create an elevation profile.Accurate elevation data from inside ArcGIS Online is used to produce an info-graphic for any area.Use as a front of class tool to explore with students, or as a resource for their own independent investigations.

This collection provides a seamlessly merged, hydrologically robust Digital Elevation Model (DEM) for the Murray Darling Basin (MDB), Australia, at 5 m and 25 m grid cell resolution.

This composite DEM has been created from all the publicly available high resolution DEMs in the Geoscience Australia (GA) elevation data portal Elvis (https://elevation.fsdf.org.au/) as at November 2022. The input DEMs, also sometimes referred to as digital terrain models (DTMs), are bare-earth products which represent the ground surface with buildings and vegetation removed. The DEMs were either from lidar (0.5 to 2 m resolution) or photogrammetry (5 m resolution) and totalled 852 individual DEMs.

The merging process involved ranking the DEMs, pairing the DEMs with overlaps, and adjusting and smoothing the elevations of the lower ranked DEM to make the edge elevations compatible with the higher-ranked DEM. This method is adapted from Gallant 2019 with modifications to work with hundreds of DEMs and have a variable number of gaussian smoothing steps.

Where there were gaps in the high-resolution DEM extents, the Forests and Buildings removed DEM (FABDEM; Hawker et al. 2022), a bare-earth radar-derived, 1 arc-second resolution global elevation model was used as the underlying base DEM. FABDEM is based on the Copernicus global digital surface model.

Additionally, hillshade datasets created from both the 5 m and 25 m DEMs are provided.

Note: the FABDEM dataset is available publicly for non-commercial purposes and consequently the data files available with this Collection are also available with a Creative Commons NonCommercial ShareAlike 4.0 Licence (CC BY-NC-SA 4.0). See https://data.bris.ac.uk/datasets/25wfy0f9ukoge2gs7a5mqpq2j7/license.txt Lineage: For a more detailed lineage see the supporting document Composite_MDB_DEM_Lineage.

DATA SOURCES 1. Geoscience Australia elevation data (https://elevation.fsdf.org.au/) via Amazon Web Service s3 bucket. Of the 852 digital elevation models (DEMs) from the GA elevation data portal, 601 DEMs were from lidar and 251 were from photogrammetry. The latest date of download was Nov 2022. The oldest input DEM was from 2008 and the newest from 2022.

1. FABDEM - Forests and buildings removed DEM based on the 1 arc-second Copernicus global digital surface model. Hawker, L., Uhe, P., Paulo, L., Sosa, J., Savage, J., Sampson, C., Neal, J., 2022. A 30 m global map of elevation with forests and buildings removed. Environ. Res. Lett. 17, 024016. https://doi.org/10.1088/1748-9326/ac4d4f

METHODS Part I. Preprocessing The input DEMs were prepared for merging with the following steps: 1. Metadata for all input DEMs was collated in a single file and the DEMs were ranked from finest resolution/newest to coarsest resolution/oldest 2. Tiled input DEMs were combined into single files 3. Input DEMs were reprojected to GA LCC conformal conic projection (EPSG:7845) and bilinearly resampled to 5 m 4. Input DEMs were shifted vertically to the Australian Vertical Working Surface (AVWS; EPSG:9458) 5. The input DEMs were stacked (without any merging and/or smoothing at DEM edges) based on rank so that higher ranking DEMs preceded the lower ranking DEMs, i.e. the elevation value in a grid cell came from the highest rank DEM which had a value in that cell 6. An index raster dataset was produced, where the value assigned to each grid cell was the rank of the DEM which contributed the elevation value to the stacked DEM (see Collection Files - Index_5m_resolution) 7. A metadata file describing each input dataset was linked to the index dataset via the rank attribute (see Collection Files - Metadata)

Vertical height reference surface https://icsm.gov.au/australian-vertical-working-surface

Part II. DEM Merging The method for seamlessly merging DEMs to create a composite dataset is based on Gallant 2019, with modifications to work with hundreds of input DEMs. Within DEM pairs, the elevations of the lower ranked DEM are adjusted and smoothed to make the edge elevations compatible with the higher-ranked DEM. Processing was on the CSIRO Earth Analytics and Science Innovation (EASI) platform. Code was written in python and dask was used for task scheduling.

Part III. Postprocessing 1. A minor correction was made to the 5 m composite DEM in southern Queensland to replace some erroneous elevation values (-8000 m a.s.l.) with the nearest values from the surrounding grid cells 2. A 25 m version of the composite DEM was created by aggregating the 5m DEM, using a 5 x 5 grid cell window and calculating the mean elevation 3. Hillshade datasets were produced for the 5 m and 25 m DEMs using python code from https://github.com/UP-RS-ESP/DEM-Consistency-Metrics

Part IV. Validation Six validation areas were selected across the MDB for qualitative checking of the output at input dataset boundaries. The hillshade datasets were used to look for linear artefacts. Flow direction and flow accumulation rasters and drainage lines were derived from the stacked DEM (step 5 in preprocessing) and the post-merge composite DEM. These were compared to determine whether the merging process had introduced additional errors.

OUTPUTS 1. seamlessly merged composite DEMs at 5 m and 25 m resolutions (geotiff) 2. hillshade datasets for the 5 m and 25 m DEMs (geotiff) 3. index raster dataset at 5 m resolution (geotiff) 4. metadata file containing input dataset information and rank (the rank column values link to the index raster dataset values) 5. figure showing a map of the index dataset and 5m composite DEM (jpeg)

DATA QUALITY STATEMENT Note that we did not attempt to improve the quality of the input DEMs, they were not corrected prior to merging and any errors will be retained in the composite DEM.

"As of January 1st 2020, new regulations outlined in the Welsh Government Agricultural Pollution Measures document state that risk maps must be created for each field within a holding which, amongst other factors, should identify ""land with an incline greater than 12°"". This specific dataset displays areas where the 12 degree threshold is exceeded based on a 50m resolution elevation dataset. Areas below the threshold are left transparent. As the elevation map on which the slope information has been calculated is relatively coarse. IMPORTANT: the slope angle information provided here must only be used as a preliminary guide – local variations in slope may differ to the values captured here. Contains OS data © Crown copyright and database right 2018" Available to view via the UK Soil OBservatory map viewer: http://mapapps2.bgs.ac.uk/ukso/home.html

A new version of this dataset exists. To see the last version of the Antarctic Digital Database, have a look here: https://data.bas.ac.uk/collections/e74543c0-4c4e-4b41-aa33-5bb2f67df389/

A very incomplete dataset of surface lakes in Antarctica. Data have been prepared from various map and remotely sensed datasets.

An incomplete dataset of moraine in Antarctica. Data have been prepared from various map and remotely sensed datasets.

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 containing a series of soil spatial covariates (e.g. topographic attributes, soil texture, soil organic matter, etc) usable in the creation of soil digital maps for OAL-UK.