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NERC Data Catalogue Service (Natural Environment Research Council)
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Maritime and Coastguard Agency (MCA) Bathymetric Survey HI1221, Cockle Shoal, (17/04/2007 to 19/04/2007)
Samples and associated geological data are held at the British Geological Survey for Maritime Coastguard Agency (MCA), Civil Hydrography Programme (CHP), Bathymetric Survey HI1221; Cockle Shoal, Area in SqKm: 5, (17/04/2007 to 19/04/2007), Standard: IHO S44ed4 Order 1. Contract: RRS (2006 LT). FY 2006/07. Contractor: MMT.
The copyright of materials derived from the British Geological Survey's work is vested in the Natural Environment Research Council [NERC]. No part of this work may be reproduced or transmitted in any form or by any means, or stored in a retrieval system of any nature, without the prior permission of the copyright holder, via the BGS Intellectual Property Rights Manager. Use by customers of information provided by the BGS, is at the customer's own risk. In view of the disparate sources of information at BGS's disposal, including such material donated to BGS, that BGS accepts in good faith as being accurate, the Natural Environment Research Council (NERC) gives no warranty, expressed or implied, as to the quality or accuracy of the information supplied, or to the information's suitability for any use. NERC/BGS accepts no liability whatever in respect of loss, damage, injury or other occurence however caused.
MMT was contracted to undertake the survey on behalf of Maritime and Coastguard Agency. For more detailed information on the acquisition equipment and data collection techniques, operational standards, data processing methods and quality control procedures used on this survey see the Report of Survey/Cruise Report and associated documentation where available. The information available may vary depending on the age of the survey. Data are checked and loaded to the BGS Coastal and Marine data management system following BGS marine data management procedures.
Airborne gravity data over Marguerite Bay collected with a Windracers Ultra UAV (2023/24 season)
Airborne gravity data provides insight into the regional subsurface geology and tectonic history. This dataset includes processed airborne data collected over Marguerite Bay using an iCorous strapdown gravity sensor. The gravity sensor was mounted in a Windracers Ultra UAV, serial TD-02. Gravity data was collected at a mean altitude of 500 m on nine flights between 120 and 260 km long, originating from Rothera Research Station. The flight pattern covered an area of 24 km by 75 km, with lines spaced 2 km apart. Data has an along line resolution of ~2 km. The survey targeted a tectonic break between different sectors of the Antarctic Peninsula identified in existing magnetic data. The survey was flown as part of the Innovate UK SWARM project demonstrating the utility of the Windracers Ultra as a platform for environmental science. This study was funded by Innovate UK through their Future flight challenge support for the "Protecting environments with unmanned aerial vehicle swarms" project (reference: 10023377). We thank BAS operations for their support and specifically the BAS air unit and ground support staff whose close cooperation and engagement with the UAV deployment made the project successful. We also thank staff at Windracers and Distributed avionics who provided remote support for UAV operations across the field season.
This data is covered by a UK Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/) Further by downloading this data the user acknowledges that they agree with the NERC data policy (http://www.nerc.ac.uk/research/sites/data/policy.asp), and the following conditions: 1. To cite the data in any publication as follows: Jordan, T., Robinson, C., Reed, T., & Toomey, R. (2024). Airborne gravity data over Marguerite Bay collected with a Windracers Ultra UAV (2023/24 season) (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/3a9c8604-2bca-48c1-a40c-48a873076581 2. The user recognizes the limitations of data. Use of the data is at the users'' own risk, and there is no warranty as to the quality or accuracy of any data, or the fitness of the data for your intended use. The data are not necessarily fully quality assured and cannot be expected to be free from measurement uncertainty, systematic biases, or errors of interpretation or analysis, and may include inaccuracies in error margins quoted with the data.
The processed gravity data was created using a Kalman filter with a spatial corelation coefficient of 2 km, and an assumed standard deviation for the gravity data of 10 mGal. The assumed minimum along track resolution is therefore 2 km. Comparison of repeat lines shows differences with a standard deviation of 1.66 mGal. This is taken to represent the accuracy of the dataset after levelling.
Photosynthesis data for the plant species Calluna vulgaris, Vaccinium myrtillus and Empetrum nigrum at the Climoor field site in Clocaenog Forest
[THIS DATASET HAS BEEN WITHDRAWN]. This dataset includes measurements of photosynthesis for the dominant higher plant species in the experimental plots at the Climoor field site in Clocaenog Forest. Plant species included are Calluna vulgaris, Vaccinium myrtillus and Empetrum nigrum. Ambient light measurements are included as well as light response curve measurements. Data was collected infrequently between 2001-2003 for Calluna and Vaccinium, and just in 2001 for Empetrum. Full details about this dataset can be found at https://doi.org/10.5285/f5e7e03c-ecf3-4455-8567-e1ad8daa66ee
If you reuse this data, you should cite: Sowerby, A., Emmett, B.A. (2014). Photosynthesis data for the plant species Calluna vulgaris, Vaccinium myrtillus and Empetrum nigrum at the Climoor field site in Clocaenog Forest. NERC Environmental Information Data Centre https://doi.org/10.5285/f5e7e03c-ecf3-4455-8567-e1ad8daa66ee
This resource is made available under the terms of the Open Government Licence
Photosynthesis was measured infrequently between 2001 and 2003 for Calluna vulgaris and Vaccinium myrtillus, and in 2001 for Empetrum nigrum. A standard leaf cuvette with light source was used in addition to a CIRAS-2 infra-red gas analyser from PP Systems (UK). Measurements were taken with the light source (to standardise between variability across treatments, as well as to determine light response curves). Measurements were also recorded in ambient light. Two of the 3 plant species have three dimensional leaves, and so data on leaf mass is included to standardise between different sized leaves (determining leaf area is not possible currently for three dimensional leaves). Data is recorded in the CIRAS in the field, and downloaded into excel files which were stored in CEH Bangor's shared file area.
Compilation of Surface Currents of the equatorial Indian Ocean (1856 -1974)
The data set comprises of measurements of surface currents collected across the Indian Ocean in the region 50 E (the Gulf of Aden) to 100 E and 25 S to 10 N. The data were collected between 1854 and 1974. The surface currents, measured from ships' drift, have been compiled into 10 day periods and 1 degree latitude-longitude squares. For each of these the vector mean of all of the observations from all years has been calculated. With this amount of subdivision, coverage is often sparse and sometimes non-existent. The source material for this atlas was obtained from the UK Meteorological Office archive of historical surface currents and this data set was compiled by the Institute of Oceanographic Sciences Deacon Laboratory (IOSDL).
Lagrangian currents and transport rates in the water column
Marine Environmental Data and Information Network
Natural Environment Research Council Designated Data Centres
Data are freely available to all following agreement to the terms and conditions of a Data Licence
Instrument(s) used to collect data: unknown.
CMIP6 HighResMIP: Tropical storm tracks as calculated by the TempestExtremes algorithm
These data are the tropical storm tracks calculated using the "TempestExtremes" storm tracking algorithm. The storm tracks are from experiments run as part of HighResMIP (High Resolution Model Intercomparison Project; Haarsma, R. J. and co-authors) a component of the Coupled Model Intercomparison Project Phase 6 (CMIP6). The raw HighResMIP data are available from the Earth System Grid Federation (ESGF), here the calculated storm tracks are available. The storm tracks are provided as Climate Model Output Rewriter (CMOR)-like NetCDF files with one file per hemisphere for all years in the simulated period of HighResMIP experiments: 1950-2014 - highresSST-present, atmosphere-only; 2015-2050 - highresSST-future experiment, atmosphere-only; 1950-2050 – control-1950, coupled atmosphere-ocean; 1950-2014 – hist-1950, coupled atmosphere-ocean; 2015-2050 – highres-future, coupled atmosphere-ocean using SSP585 scenario. There is one tracked variable in each file with time, latitude and longitude coordinates associated at each six-hour interval. Other variables associated with each track are also provided, e.g. the minimum or maximum value adjacent to the track of the variable of interest and these variables have their own latitude and longitude coordinate variables. If a maximum/minimum value is not found, then a missing data value is used for the respective latitude-longitude values.
Public data: access to these data is available to both registered and non-registered users.
Under the following licence http://creativecommons.org/licenses/by/4.0/, appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
The data were passed from the project team to the Centre for Environmental Data Analysis for archival and distribution in July 2019.
Coastal Biodiversity and Ecosystem Service Sustainability (CBESS) projected area of vegetation in saltmarsh habitats
The dataset contains estimates of the projected area of vegetation derived from the analysis of side-on photographs through the vegetation canopy and recorded for survey quadrats at six UK saltmarsh sites. Three of the sites were in Morecambe Bay, North West England and three of the sites were in Essex, South East England, each of these sites consisted of a saltmarsh area and adjacent mudflat area. Each site comprised 22 quadrats in the vegetated area of salt marsh. A calibrated camera was used to photograph through a 600 x 200mm section of vegetation against a red background. Calibrated images were then classified into vegetation and background classes and parameters of vegetation density in the horizontal were computed. This data was collected as part of Coastal Biodiversity and Ecosystem Service Sustainability (CBESS): NE/J015644/1. The project was funded with support from the Biodiversity and Ecosystem Service Sustainability (BESS) programme - is a six-year programme (2011-2017) funded by the UK Natural Environment Research Council (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme. Full details about this dataset can be found at https://doi.org/10.5285/936e04d0-c8ae-47ec-a858-518a77667c70
If you reuse this data, you should cite: Evans, B.R., Möller, I., Spencer, T. (2016). Coastal Biodiversity and Ecosystem Service Sustainability (CBESS) projected area of vegetation in saltmarsh habitats. NERC Environmental Information Data Centre https://doi.org/10.5285/936e04d0-c8ae-47ec-a858-518a77667c70
The method followed that of Möller (2006). Side-on photography was undertaken in the field using a frame to ensure consistent geometry and a calibrated Fuji Finepix XP30 camera. Photographs were rectified using Matlab and exported in TIFF format to Erdas Imagine for classification. A 20-class unsupervised classification was performed followed by manual attribution of classes into "background" and vegetation". The binary image files were then analysed in Matlab based on pixel sizes derived from the camera calibration procedure against a chequerboard background. Further methodological details are contained in the supporting document.
Planktonic foraminifer occurrence data from IODP Expedition 395C, Reykjanes Ridge (NERC Grant NE/W007002/1)
Qualitative abundance data from micropalaeontological residues from International Ocean Discovery Program Sites U1554, U1555, U1562, U1563 and U1564. Data represents abundance and preservation state of planktonic foraminifera and other sedimentary components from washed residues sieved at > 63 microns. Relative abundances and counts of left and right coiling ratios of selected species of planktonic foraminifera are recorded.
Either: (i) the dataset is made freely available, e.g. via the Internet, for a restricted category of use (e.g. educational use only); or (ii) the dataset has not been formally approved by BGS for access and use by external clients under licence, but its use may be permitted under alternative formal arrangements; or (iii) the dataset contains 3rd party data or information obtained by BGS under terms and conditions that must be consulted in order to determine the permitted usage of the dataset. Refer to the BGS staff member responsible for the creation of the dataset if further advice is required. He / she should be familiar with the composition of the dataset, particularly with regard to 3rd party IPR contained in it, and any resultant use restrictions. This staff member should revert to the IPR Section (ipr@bgs.ac.uk) for advice, should the position not be clear.
The dataset has been formally approved by BGS for access by external clients under a BGS Digital Data Licence, issued via BGS's IPR Section. The dataset must not be provided to, or be accessible by, an external client until the IPR Section confirms that signed licence documentation is in place. Refer to the IPR Section (DigitalLE@bgs.ac.) if further advice is required.. Constraint applies until 2025-08-31
Planktonic foraminifers were examined from core catcher (CC) samples and selected samples taken from within split cores. Planktonic foraminifers were also examined from mudline samples from the top of selected holes. Mudline samples were stained with Rose Bengal to highlight living cells. Sample volumes of approximately 10 or 20 cm3 were washed over 63 ?m sieves. Harder samples were dried at ~40oC overnight before washing in a sediment shaker. Very hard samples were treated with dilute peroxide and/or detergent and some were disaggregated with mortar and pestle. Empty sieves were cleaned in an ultrasonic bath to minimize cross-contamination between samples. Dried residues (>63 ?m) were transferred to labelled glass vials, from which subsamples were examined on metal trays using a binocular stereomicroscope.
Aerial survey of St Andrews Bay, South Georgia, elephant seal colony during the 2024/2025 season, flight DLPUS_214_26
Aerial survey of St Andrews Bay elephant seal colony, Mirounga leonina, during the 2023/24 season conducted using a remotely piloted aerial system (RPAS). The aerial survey was conducted as part of the Darwin Plus (DPLUS) 214 project: Southwest Atlantic Elephant Seal Population Assessment (SAESPA). Dataset includes the original images and log files, the original RINEX GNSS (global navigation satellite system) base station files, the post-processed global navigation satellite system and imagery data, along with the resulting georeferenced DSM (digital surface model) and an orthorectified mosaic of the imagery. This dataset is from flight number DPLUS_214_26 which was carried out on 2024-10-30. This work was supported by the Overseas Territories Environment and Climate Fund under Grant Darwin Plus ref: DPLUS214: Southwest Atlantic Elephant Seal Population Assessment (SAESPA).
Data supplied under Open Government Licence v3.0 http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/.
Coordinate reference system for outputs: Projection: UTM Zone 23S Horizontal datum: WGS84 Vertical datum: MSL (mean sea level), EGM2008 geoid Resolution of final outputs: DSM (2.1 cm) Orthorectified mosaic (2.1 cm) Calibration accounted for in processing.
Borehole electric log from the southern sector of Larsen C Ice Shelf, Antarctic Peninsula, December 2022
This is an electric log of a borehole drilled by hot water to 120 m (Site 1) on Larsen C Ice Shelf, Antarctic Peninsula. The borehole was drilled in December 2022 to investigate the internal properties of a suture zone (Site 1) and a meteoric ice band (Site 2) of an ice shelf, as part of the NERC-funded RiPIce (Rift Propagation for Ice sheet models) research project. NERC standard grant NE/T008016/1.
Data are unaltered from those logged in the field. Due to the field site location on an ice shelf, the voltage reference fish was submerged in the ice surface around 5 m from the winch and 15 m from the borehole. Missing data are presented as -999.5.
https://catalogue.ceda.ac.uk/uuid/76cad0b4f6f141ada1c44a4ce9e7d4bd 76cad0b4f6f141ada1c44a4ce9e7d4bd 10.5285/76cad0b4f6f141ada1c44a4ce9e7d4bd
Summary for Policymakers of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure SPM.1 (v20210809)
Data for Figure SPM.1 from the Summary for Policymakers (SPM) of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure SPM.1 shows global temperature history and causes of recent warming. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu and B. Zhou (eds.)]. Cambridge University Press. In Press. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has two panels, with data provided for all panels in subdirectories named panel_a and panel_b. --------------------------------------------------- List of data provided --------------------------------------------------- Panel a The dataset contains: - Estimated temperature during the warmest multi-century period in at least the last 100,000 years, which occurred around 6500 years ago (4500 BCE), multi-centennial average, from AR6 WGI Chapter 2 - Global surface temperature change time series relative to 1850-1900 for 1-2020 from: • 1-2000 CE reconstruction from paleoclimate archives, decadal smoothed, from PAGES2k Consortium (2019, DOI: 10.1038/s41561-019-0400-0) • 1850-2020 CE, observations, decadal smoothed, from AR6 WGI Chapter 2 assessed mean Panel b: The dataset contains global surface temperature change time series relative to 1850-1900 for 1850-2020 from simulations from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and observations: - CMIP6 historical+ssp245 simulations (simulations with human and natural forcing, 1850-2019) - CMIP6 hist-nat simulations (simulations with natural forcing, 1850-2019) - Global Surface Temperature Anomalies (GSTA) relative to 1850-1900 from observations assessed in IPCC AR6 WG1 Chapter 2 (1850-2020) --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - panel_a/SPM1_1-2000_recon.txt, 1-2000 time series, decadal smoothed, for years centered on 5-1996 CE [column 1 grey line, columns 2 and 3 grey shading] - panel_a/SPM1_1850-2020_obs.txt, 1850-2020 time series, decadal smoothed, for years centered on 1855-2016 CE [black line] - panel_a/SPM1_6500_recon.txt, bar for the warmest multi-century period in more than 100,000 years (around 6500 years ago: 4500 BCE) [grey bar] Panel b: - panel_b/gmst_changes_model_and_obs.csv. Global surface temperature change time series relative to 1850-1900 for 1850-2020 from: • CMIP6 historical+ssp245 simulations (1850-2019) [mean, brown line] • CMIP6 historical+ssp245 simulations (1850-2019) [5% range, brown shading, bottom] • CMIP6 historical+ssp245 simulations (1850-2019) [95% range, brown shading, top] • CMIP6 hist-nat simulations (1850-2019) [mean, green line] • CMIP6 hist-nat simulations (1850-2019) [5% range, green shading, bottom] • CMIP6 hist-nat simulations (1850-2019) [95% range, green shading, top] • Global Surface Temperature Anomalies (GSTA) relative to 1850-1900 from observations assessed in IPCC AR6 WG1 Chapter 2 (1850-2020) [black line] --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report webpage, which includes the report component containing the figure (Summary for Policymakers), the Technical Summary (Cross-Section Box TS.1, Figure 1a) and the Supplementary Material for Chapters 2 and 3, which contains details on the input data used in Tables 2.SM.1 (Figure 2.11a) and 3.SM.1 (Figure 3.2c; FAQ 3.1, Figure 1). - Link to related publication for input data
Data produced by Intergovernmental Panel on Climate Change (IPCC) authors and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by the Technical Support Unit (TSU) for IPCC Working Group I (WGI). Data curated on behalf of the IPCC Data Distribution Centre (IPCC-DDC).
EARTH SCIENCE > Solid Earth > Geodetics/Gravity
EARTH SCIENCE > Solid Earth > Geodetics/Gravity > Gravity
EARTH SCIENCE > Biosphere > Animal Taxonomy > Mammals
EARTH SCIENCE > Biosphere > Ecological Dynamics > Biodiversity
EARTH SCIENCE > Biosphere > Ecological Dynamics > Population Dynamics
EARTH SCIENCE > Biosphere > Terrestrial Ecosystems
EARTH SCIENCE > Oceans > Marine Biology > Marine Mammals
EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Glacier Mass Balance/Ice Sheet Mass Balance
EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Glacier Motion/Ice Sheet Motion
EARTH SCIENCE > Hydrosphere > Glaciers/Ice Sheets > Glacier Mass Balance/Ice Sheet Mass Balance
EARTH SCIENCE > Hydrosphere > Glaciers/Ice Sheets > Glacier Motion/Ice Sheet Motion
EARTH SCIENCE > Oceans > Coastal Processes > Sea Level Rise
Github site with documentation and python code to read and understand the storm track files.
Ullrich, P. A., & Zarzycki, C. M. (2017). TempestExtremes: A framework for scale-insensitive pointwise feature tracking on unstructured grids. Geoscientific Model Development, 10(3), 1069-1090.
Zarzycki, C. M., & Ullrich, P. A. (2017). Assessing sensitivities in algorithmic detection of tropical cyclones in climate data. Geophysical Research Letters, 44(2), 1141-1149.
Webpage for the Working Group I Contribution to the IPCC Sixth Assessment Report
RELATED PUBLICATION: PAGES 2k Consortium (2019): Consistent multidecadal variability in global temperature reconstructions and simulations over the Common Era, 12(8), 643-649, doi:10.1038/s41561-019-0400-0
ORIGIN OF FIGURE (IPCC REPORT SPM): IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
Polar Data Centre - British Antarctic Survey
NERC EDS Environmental Information Data Centre
Institute of Oceanographic Sciences Wormley Laboratory
Centre for Environmental Data Analysis (CEDA)
NERC EDS Centre for Environmental Data Analysis
2001 Strategic Environmental Assessment SEA2 Environmental Sampling Survey, North Sea, May 2001 Data Report ERTSL 637 - Sediment hydrocarbons and metals analyses
Sediment samples were collected from selected areas of the southern North Sea as part of the ongoing Department of Trade and Industry's (now Department of Energy and Climate Change) Strategic Environmental Assessment (SEA2). The aim of the survey was to describe the physical, chemical and biological characteristics of a range of offshore sandbanks and pockmarks (more than 12 km from the coast). The survey focused on three main study areas in the southern North Sea: the Dogger Bank study area; the South Fladen Pockmark study area and a major sand bank area off the coasts of Norfolk and Lincolnshire. This report presents the following sediment data: Total hydrocarbon and n-alkane concentrations; 2 to 6 ring polynuclear aromatic hydrocarbons (PAH) content; selected metals concentrations.
Concentration of alkanes in sediment samples
Concentration of other organic contaminants in sediment samples
Concentration of polycyclic aromatic hydrocarbons (PAHs) in sediment samples
Inorganic chemical composition of sediment or rocks
The sampling strategy of the identified sandbanks was developed by Hartley Anderson Ltd (HAL - contracted as principal scientists). Sampling operations were conducted from the R/V Kommandor Jack with overall direction of field operations undertaken by HAL as part of the UK Department of Energy and Climate Change's Offshore Energy Strategic Environmental Assessment programme. ERT (Scotland) Ltd (ERTSL) was contracted by the Department of Trade and Industry (DTI) via Geotek Ltd/HAL to retrieve the seabed samples as well as processing, storage and chain-of-custody of the samples prior to initiation of the analysis programme by ERTSL. The analyses were: Total hydrocarbon and n-alkane concentrations by gas chromatography (GC); 2 to 6 ring polynuclear aromatic hydrocarbons (P AH) content by gas chromatography-mass spectrometry (GC-MS); Selected metals concentrations. This resulted in the publication of this report in 2001.
Digital Terrain Model (DTM) at 5 metre resolution (GB-wide) derived from photogrammetry (2008-2012).
The Digital Terrain Model (DTM) is a bare earth model, posted at 5m with a vertical accuracy of less than 60cm RMSE (root mean square error). The model represents the bare ground surface without any objects like trees and buildings. The dataset covers Great Britain. The first surface model, the Digital Surface Model (DSM), which represents the earth’s surface including all objects on the surface, is produced using the digital stereo aerial photography acquired by Getmapping. The DSM is edited to produce a 5m DTM product. A suite of algorithms have been applied to semi-automatically edit the DSM and remove unwanted surface features such as buildings and vegetation. These algorithms include a routine which reduces the woodland canopy areas based on a bounding polygon. This requires some manual intervention to create bounding polygons for woodland extents and identify true ground level. In addition, break lines are captured where required to ensure true terrain features are not removed and that bodies of water, such as lakes, remain flat. The PGA Elevation data offers improved spatial resolution compared to the NEXTMap data. The data is from the Pan Government Agreement (PGA) and an in-perpetuity license has been granted to BGS. The data is being managed by the Earth and Planetary Observation and Monitoring (EPOM) Team in support of the wider BGS Programme.
The data is for BGS internal use. Detailed copyright and licensing information can be found at S:\PGA_Elevation\licensing_and_copyright
The first surface model, the Digital Surface Model (DSM), is produced using the digital stereo aerial photography acquired by Getmapping. The DSM is edited to produce a 5m DTM product. A suite of algorithms have been applied to semi-automatically edit the DSM and remove unwanted surface features such as buildings and vegetation. These algorithms include a routine which reduces the woodland canopy areas based on a bounding polygon. This requires some manual intervention to create bounding polygons for woodland extents and identify true ground level. In addition, break lines are captured where required to ensure true terrain features are not removed and that bodies of water, such as lakes, remain flat. The result is a 5m posted DTM with a vertical accuracy of less than 60cm RMSE.
Strategic Environmental Assessment (SEA) data portal
Department for Energy and Climate Change (DECC)