[From The Landmap Project: Introduction, "http://www.landmap.ac.uk/background/intro.html"]

 A joint project to provide orthorectified satellite image mosaics of Landsat,
 SPOT and ERS radar data and a high resolution Digital Elevation Model for the
 whole of the UK. These data will be in a form which can easily be merged with
 other data, such as road networks, so that any user can quickly produce a
 precise map of their area of interest.

 Predominately aimed at the UK academic and educational sectors these data and
 software are held online at the Manchester University super computer facility
 where users can either process the data remotely or download it to their local
 network.

 Please follow the links to the left for more information about the project or
 how to obtain data or access to the radar processing system at MIMAS. Please
 also refer to the MIMAS spatial-side website,
 "http://www.mimas.ac.uk/spatial/", for related remote sensing materials.

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.

The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

Welcome to the Ordnance Survey Data Download in ArcGIS Online! This is a feature service that enables ArcGIS users to download OS Open Datasets via the ArcGIS Platform. These downloads come from the OS Open Data Hub.OS Terrain® 50: Visualise simple landscapes in 3D and bring your geographic analysis to life.This dataset comes as a Shapefile (.shp), an ASCII Grid and a Geopackage.Download ShapefileDownload ASCII GridDownload GeopackagePlease see here for the Terms Currency: This dataset points to the OS datahub so will be the most current dataset that they have available.

World Elevation layers are compiled from many authoritative data providers, and are updated quarterly. 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 Vantor's Precision3D covering parts of the globe.Note: ArcGIS Elevation service, Terrain 3D (for Export) and TopoBathy 3D (for Export) does not include Vantor Precision3D and Airbus WorldDEM4Ortho.To view the all the sources in a table format, check out World Elevation Data Sources Table.Topography sources listed in the table 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.Disclaimer: Data sources are not to be used for navigation/safety at sea and in air.

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.

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/

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.

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.

This dataset is published as Open Data.OS Terrain® 50 is an open height dataset of contours with spot heights, breaklines, coastline, lakes, ridges and formlines for Great Britain.What OS Terrain 50 provides you withModel wind direction and lines of sightMake better decisions about where to locate wind turbines and mobile phone masts. OS Terrain 50 lets you model wind direction and lines of sight at your desk, meaning fewer site visits.Plan landscape defencesGet the bigger picture about flood risk, soil erosion and pollution. By showing steep hillside gradients, OS Terrain 50 helps you plan flood defences and safeguard the landscape.More engaging mapsWith the contours version of OS Terrain 50, you can shade in hills to show their height. This extra sense of depth is ideal for walking maps and apps.Surface model entire landscapesGet an accurate, uncluttered view of the terrain with the grid version of OS Terrain 50. Its 50 metre post spacing gives you a surface model of the entire landscape, including major roads, large lakes and estuaries.Take account of tidesThe contours dataset also includes mean high and low water boundaries.

Ordnance Survey’s OS Terrain 50 DTM is a dataset representing the physical shape of the real world. The dataset includes 50metre GRID. The DTM data is captured from Ordnance Survey’s large scale aerial imagery. The product is updated and maintained annually. A free to use topology GIS dataset, to help you visualise simple landscapes in 3D and bring your geographic analysis to life.

These data are digital elevation models which describe landscape topography. The data were created to support analysis of landscape change following the 7th February 2021 avalanche-debris flow in Chamoli District, Uttarakhand, India. The data were used as standalone datasets to support this analysis, but also supported numerical modelling using CAESAR-Lisflood (see data collection). The DEMs were created from CNES/Airbus Pléiades-HR stereo satellite imagery captured in along-track mode. They are a geospatial dataset created in raster (.tif) format. They are most commonly imported into GIS software, where they can be analysed or support other forms of geospatial analysis.

This record is for Approval for Access product AfA439. A habitat map derived from airborne data, specifically CASI (Compact Airborne Spectrographic Imager) and LIDAR (Light Detection and Ranging) data.

The habitat map is a polygon shapefile showing site relevant habitat classes. Geographical coverage is incomplete because of limits in data available. It includes those areas where the Environment Agency, Natural England and the Regional Coastal Monitoring Programme have carried out sufficient aerial and ground surveys in England.

The habitat map is derived from CASI multispectral data, LIDAR elevation data and other GIS products. The classification uses ground data from sites collected near to the time of CASI capture. We use ground data to identify the characteristics of the different habitats in the CASI and LIDAR data. These characteristics are then used to classify the remaining areas into one of the different habitats.

Habitat maps generated by Geomatics are often derived using multiple data sources (e.g. CASI, LIDAR and OS-base mapping data), which may or may not have been captured coincidentally. In instances where datasets are not coincidentally captured there may be some errors brought about by seasonal, developmental or anthropological change in the habitat.

The collection of ground data used in the classification has some limitations. It has not been collected at the same time as CASI or LIDAR capture; it is normally within a couple of months of CASI capture. Some variations between the CASI data and situation on site at the time of ground data collection are possible. A good spatial coverage of ground data around the site is recommended, although not always practically achievable. For a class to be mapped on site there must have been samples collected for it on site. If the class is not seen on site or samples are not collected for a class, it cannot be mapped.

No quantitative accuracy assessment has been carried out on the habitat map, although the classification was trained using ground data and the final habitat map has been critically evaluated using Aerial Photography captured simultaneously with the CASI data by the processors and independently by habitat specialists. Please note that this content contains Ordnance Survey data © Crown copyright and database right [2014] and you must ensure that a similar attribution statement is contained in any sub-licences of the Information that you grant, together with a requirement that any further sub-licences do the same.

This record consists of 5 different datasets covering the Alexander Island region of Antarctica: coastline (including grounding line and ice shelf fronts), contours, spot heights, rock outcrop and lakes. The data have been produced for a new topographic map of Alexander Island at 1:500,000 scale, produced by the Mapping and Geographic Information Centre, British Antarctic Survey. The data are suitable for a 1:500,000 scale map but may be suitable for larger scales in certain areas. They have been created from source data ranging from 2022 - 2025. The data primarily cover Alexander Island, and also cover Rothschild, Charcot and Latady islands, as well as Wilkins and George VI ice shelves, and the Rymill Coast section of Palmer Land on the Antarctic Peninsula. The datasets were created using a mixture of GIS software, primarily digitised from Sentinel-2 satellite imagery or extracted from high resolution, published elevation models. Exact details of each dataset can be found in the lineage statements.

These data are digital elevation models (DEMs) of difference (DoD). They are a geospatial dataset created in raster (.tif) format and quantify vertical (z) topographic change between two dates. The data were created to support analysis of landscape change following the 7th February 2021 avalanche-debris flow in Chamoli District, Uttarakhand, India. The data also supported numerical modelling using CAESAR-Lisflood (see related data https://catalogue.ceh.ac.uk/documents/7023cb77-c797-475e-872c-6f1e2b63dcc1). They are most commonly imported into GIS software, where they can be analysed or support other forms of geospatial analysis.

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.

The LIDAR Composite DSM (Digital Surface Model) is a raster elevation model covering ~99% of England at 1m spatial resolution. The DSM (Digital Surface Model) is produced from the last or only laser pulse returned to the sensor and includes heights of objects, such as vehicles, buildings and vegetation, as well as the terrain surface

Produced by the Environment Agency in 2022, the DSM 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 catalogue which show for any location which survey was used in the production of the LIDAR composite.

The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

A National Nature Reserve (NNR) is the land declared under the National Parks and Access to the Countryside Act 1949 or Wildlife and Countryside Act (1981) as amended. The data does not include "proposed" sites. Boundaries are mapped against Ordnance Survey MasterMap Topography Layer.Full metadata can be viewed on data.gov.uk.

The LIDAR derived Vegetation Object Model (VOM) is a raster product produced as part of the Environment Agency’s “Keeping Rivers Cool” project. It is an attempt to identify riparian tree cover and the opportunities for tree planting to increase future shading of streams & rivers.

The dataset has been produced by complex GIS modelling of the Environment Agency national LIDAR programme 1m elevation data into discrete objects, with spatial proximity queries against features in Ordnance Survey mapping and Sentinel 2 imagery aiding in the classification of vegetation and non-vegetation objects.

The result is a raster product where each pixel represents the height of top of canopy above ground, for all classified vegetation objects above a threshold of 2.5 metres. The data production is fully automated, with no manual QC and editing of the output, other than visual checks. Because of the process to classify objects based on proximity to features within OS mapping there could be some mis-classifications of objects not included in the OS mapping (especially static caravans, shipping containers, large tents / marquees, coastal cliffs and new buildings constructed directly under tree cover). This is a first release of this dataset, the quality of the production methods will be reviewed over the next year, improvements will be made where possible.

As there are many potential environmental applications for an open data, national coverage, high resolution Vegetation Object Model the product will be released for all national LIDAR programme survey data captured by the Environment Agency.

The Vegetation Object Model is available to download as 5km GeoTiff tiles in the same structure as the other derived products from the national LIDAR programme. Contained within each 5km zip file is the Vegetation Object Model and a hillshade raster produced by adding the VOM onto the Digital Terrain Model.

Please refer to the metadata record: https://environment.data.gov.uk/dataset/2e8d0733-4f43-48b4-9e51-631c25d1b0a9 for downloading all other products derived from the national LIDAR programme, including the digital surface and terrain models, intensity rasters or point cloud.

Forest Ecosystem Dynamics (FED) Project Spatial Data Archive: Elevation Contours for the Northern Experimental Forest

The Biospheric Sciences Branch (formerly Earth Resources Branch) within the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center and associated University investigators are involved in a research program entitled Forest Ecosystem Dynamics (FED) which is fundamentally concerned with vegetation change of forest ecosystems at local to regional spatial scales (100 to 10,000 meters) and temporal scales ranging from monthly to decadal periods (10 to 100 years). The nature and extent of the impacts of these changes, as well as the feedbacks to global climate, may be addressed through modeling the interactions of the vegetation, soil, and energy components of the boreal ecosystem.

The Howland Forest research site lies within the Northern Experimental Forest of International Paper. The natural stands in this boreal-northern hardwood transitional forest consist of spruce-hemlock-fir, aspen-birch, and hemlock-hardwood mixtures. The topography of the region varies from flat to gently rolling, with a maximum elevation change of less than 68 m within 10 km. Due to the region's glacial history, soil drainage classes within a small area may vary widely, from well drained to poorly drained. Consequently, an elaborate patchwork of forest communities has developed, supporting exceptional local species diversity.

This data layer contains elevation contours for the 10 X 10 km area located within the Northern Experimental Forest. Contours and elevation benchmarks from the United States Geological Survey 7.5" Maine quadsheets for Howland and Lagrange were digitized, and elevation data in feet were added.

The data was revised by projecting it into NAD83 datum by L. Prihodko at NASA Goddard Space Flight Center. Although the data was received at GSFC with an undeclared datum, it was assumed to be in North American Datum of 1927 (NAD27) because the original map from which the data were digitized was in NAD27. Also, the data fit exactly within the bounds of the FED site grid (even Universal Transverse Mercator projections) in NAD27. After projecting the data into NAD83 it was checked to insure that the change was a linear translation of the coordinates.

This SRTM Slope Map was created from level 1 SRTM NASA data which was cleaned and had holes patched. The slope map was created in ArcMap (presumably using the simple 3x3 nearest neighbour method). The data does not include the Shetland Islands as SRTM data becomes unreliable at 60N. The cell size is close to 90m. Data was acquired between the 11th - 20th Feb 2000. SRTM Slope Map was created from level 1 SRTM NASA data, slope map generated in ArcGIS using a basic nearest neighbour approach. Digital Terrain Model. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2010-06-30 and migrated to Edinburgh DataShare on 2017-02-20.