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Continents, countries, sea regions of the world.
https://catalogue.ceda.ac.uk/uuid/cc81a77c2cb7af64722bf936a7b6e18c cc81a77c2cb7af64722bf936a7b6e18c
Data from the ATM Instrument on-board the Piper PA31 Navajo Chieftain G-NERC Aircraft during Flight 86/34 over the Skomer Island, West Angle Bay, Freshwater West and Stackpole Quay Areas
The Airborne Research & Survey Facility (ARSF, formerly Airborne Remote Sensing Facility) is managed by NERC Scientific Services and Programme Management. It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in support of research, survey and monitoring programmes. The ARSF is a unique service providing environmental researchers, engineers and surveyors with synoptic analogue and digital imagery of high spatial and spectral resolution.The NEODC holds the entire archive of Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) data acquired by the NERC ARSF. High-resolution scanned digital versions of the entire collection of analogue photographs are now also available as well as selected LiDAR-derived elevation and terrain models for selected sites flown using the sensor.
Access to these data is available to any registered CEDA user. Please Login or Register for a CEDA account to gain access.
Under the following licence http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/, 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.
Data have been provided to NEODC via a number of routes: Most data up to 2005 was provided directly from ARSF flight team (ARSF-Ops) or Andrew Wilson at CEH, on various media. Data since 2008 was mostly transferred to NEODC from ARSF-Data Analysis Node (DAN) in Plymouth via rsync. Data for 2006 - 2008 were provided partly from ARSF-DAN, partly from ARSF-Ops, and some from Andrew Wilson. Data from the ULM LiDAR instrument was provided, via FTP or on media, from ULM Cambridge. Scanned aerial photographs were provided by Bluesky Ltd, who carried out the digitisation, on LaCiE disks. Some data ("user_provided") was sent to NEODC by ARSF data users.
2010, Xcite Energy Resources Ltd, Bentley, Jack-Up Rig, DECC Reference Number 2186
An oil and gas industry site survey for a jack-up rig acquired under licence P1078 between March and April 2010. The block number traversed was 9/3b.
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.
The metadata is freely available for general disclosure. The actual survey data is restricted.
This dataset was collected by Gardline Geosurvey Ltd on behalf of Xcite Energy Resources Ltd and reported by Senergy through the PON 14 regulation. Data was collected using multibeam echo sounder, single beam echo sounder, side scan sonar, sub bottom profiler, high resolution seismic, seabed photography, seabed video and grab samples.
2011, Total E&P UK Ltd, Fettercairn, Semi-Sub Rig, DECC Reference Number 2439
An oil and gas industry site survey for a semi-sub rig acquired under licence P090 between April and May 2011. The block number traversed was 3/15.
This dataset was collected by Fugro Survey Ltd on behalf of Total E&P UK Ltd and reported by the licensee through the PON 14 regulation. Data was collected using high resolution seismic, mini airgun, multibeam echo sounder, hull-mounted pinger, side scan sonar, grab samples, sea water samples, seabed photography and seabed video.
UK Environmental Change Network (ECN) butterfly data: 1993-2012
[THIS DATASET HAS BEEN WITHDRAWN]. Butterfly data from the UK Environmental Change Network (ECN) terrestrial sites. Counts of individual species are recorded. These data are collected while walking a defined transect at all of ECN's terrestrial sites using a standard protocol. They represent continuous weekly records from 1993 to 2012. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/dad68dc4-9e36-457e-aa3a-e7eb816fb508
If you reuse this data, you should cite: Rennie, S., Adamson, J., Anderson, R., Andrews, C., Bater, J., Bayfield, N., Beaton, K., Beaumont, D., Benham, S., Bowmaker, V., Britt, C., Brooker, R., Brooks, D., Brunt, J., Common, G., Cooper, R., Corbett, S., Critchley, N., Dennis, P., Dick, J., Dodd, B., Dodd, N., Donovan, N., Easter, J., Eaton, E., Flexen, M., Gardiner, A., Hamilton, D., Hargreaves, P., Hatton-Ellis, M., Howe, M., Kahl, J., Lane, M., Langan, S., Lloyd, D., McElarney, Y., McKenna, C., McMillan, S., Milne, F., Milne, L., Morecroft, M., Murphy, M., Nelson, A., Nicholson, H., Pallett, D., Parry, D., Pearce, I., Pozsgai, G., Rose, R., Schafer, S., Scott, T., Sherrin, L., Shortall, C., Smith, R., Smith, P., Tait, R., Taylor, C., Taylor, M., Thurlow, M., Tilbury, C., Turner, A., Tyson, K., Watson, H., Whittaker, M. (2015). UK Environmental Change Network (ECN) butterfly data: 1993-2012. NERC Environmental Information Data Centre https://doi.org/10.5285/dad68dc4-9e36-457e-aa3a-e7eb816fb508
Data are collected from the UK Environmental Change Network (ECN) terrestrial sites while walking a defined transect at all of ECN's terrestrial sites using a standard protocol. Prior to deposit of the data in the EIDC, data are managed by the ECN Data Centre at CEH Lancaster according to defined protocols. Verification steps include numeric range checks (i.e. checking if a value falls within a specified range), categorical checks (e.g. checking that a species code appears on the standard code list), formatting (i.e. that the dataset conforms to the specified data format) and logical integrity checks (i.e. checking the data make sense, e.g. that the dates in one dataset match those in a related dataset). Appropriate range settings for ECN variables have been selected following discussion with specialists in each field. Where data fall outside these ranges, a cautious approach has been adopted towards discarding data on the principle that apparent errors may be valid outliers. Such values are discarded only if there is a clear explanation (e.g. an instrumentation error) and corrections are made where possible. If the reason is unclear, the values are stored, but are qualified using pre-defined quality codes or free-text descriptions. Data providers also use these codes or free text to describe factors affecting sampling outside their control, instrument damage or site management effects.
Methane and CO2 gas concentrations and stable isotope data from select core samples from UKGEOS Glasgow GGC01 borehole
IDA267644 Methane and CO2 gas concentrations and stable isotope analyses of select core samples from GGC01 borehole of the Glasgow UKGEOS facility. Core samples were collected approximately every 10m depth in gas tight isojars by the BGS. Geochemical gas analyses was carried out at the Scottish Universities Environmental Research Centre (SUERC) and consisted of bulk concentration analysis using gas chromatography; followed by δ13CCH4, δ13CCO2, and δD stable isotope analyses on a methane combustion line (full methods attached). This data was collected to investigate the variability of gas fingerprints with depth within the Glasgow coal mine workings, and unmined Carboniferous coal measures. Samples and data are derived from the UK Geoenergy Observatories Programme funded by the UKRI Natural Environment Research Council and delivered by the British Geological Survey.
Available under the Open Government Licence subject to the following acknowledgement accompanying the reproduced NERC materials "Contains NERC materials ©NERC [year]"
Rock samples consisting of two 50mm quarter sections of core were obtained approximately every 10m depth during drilling of the GGC01 borehole. Two sample storage methods was used to collect samples; with a core sample from each depth being stored in de-ionised water, and the other being stored in nitrogen gas. All samples were then stored at standard temperature (25 C) and pressure (1atm) for a three-month period, to allow the samples to equilibrate with the headspace prior to gas analysis at the Scottish Universities Environmental Research Centre (SUERC). Gas analyses consisted of establishing methane and CO2 concentrations through gas chromatography (full method attached), with select gas samples being analysed for their stable isotope signature (methane combustion line method attached).
Allometric modelling of plant biomass from drone-acquired photographs: drone images, ground control marker coordinates and biomass data from 36 sites, 2016-2020
This dataset contains RGB photographs acquired from drone surveys. There are 741 harvest plots from 38 surveys at 36 sites around the world. Each site was approximately 1 ha in area. Included with the photographic images are the coordinates of ground control markers, biomass, taxonomic and location data for harvest plots and ancillary metadata. The observations can be used to obtain allometric size-biomass models. This work was supported by the Natural Environment Research Council award number NE/R00062X/1 as part of the project 'Do dryland ecosystems control variability and recent trends in the land CO2 sink?' Full details about this dataset can be found at https://doi.org/10.5285/1ec13364-cbc6-4ab5-a147-45a103853424
If you reuse this data, you should cite: Cunliffe, A., Anderson, K., Boschetti, F., Graham, H., Brazier, R., Myers-Smith, I., Astor, T., Boer, M., Calvo, L., Clark, P., Cramer, M., Encinas-Lara, M., Escarzaga, S., Fernández-Guisuraga, J., Fisher, A., Gdulová, K., Gillespie, B., Griebel, A., Hanan, N., Hanggito, M., Haselberger, S., Havrilla, C., Ji, W., Karl, J., Kirchhoff, M., Kraushaar, S., Lyons, M., Marzolff, I., Mauritz, M., McIntire, C., Metzen, D., Méndez-Barroso, L., Power, S., Prošek, J., Sanz-Ablanedo, E., Sauer, K., Schulze-Brüninghoff, D., Šímová, P., Smit, J., Steele, C., Suárez-Seoane, S., Tweedie, C., Vargas, S., Villarreal, M., Visser, F., Wachendorf, M., Wirnsberger, H., Wojcikiewicz, R. (2020). Allometric modelling of plant biomass from drone-acquired photographs: drone images, ground control marker coordinates and biomass data from 36 sites, 2016-2020. NERC Environmental Information Data Centre https://doi.org/10.5285/1ec13364-cbc6-4ab5-a147-45a103853424
This resource is available under the terms of the Open Government Licence
These datasets were collected using a standardised sampling protocol during peak biomass by multiple teams using different equipment. Datasets have been reviewed and further details are available in the supporting documentation. Further information on the collection and processing of these data are given in Cunliffe et al. ‘Drone photogrammetry-derived canopy height predicts aboveground biomass across non-forest ecosystems’ (In Press) and the accompanying supplementary materials.
2019, Ithaca Energy (UK) Ltd, Fotla Area Geophysical Survey 22/1b, Site Survey, DECC Reference Number GS_1000
An oil and gas industry geophysical site survey acquired between October and November 2019. The block number traversed was 22/1.
This dataset was collected by Fugro GB (North) Marine Ltd on behalf of Ithaca Oil and Gas Ltd and reported by the licensee through the geological consent activity log and close-out report process (formerly PON 14). Data was collected using single beam echo sounder, grab samples, multibeam echo sounder, high resolution seismic, seabed video, seabed photography, single beam echo sounder, sub bottom profiler, magnetometer/gradiometer, side scan sonar, geotechnical equipment gravity core, mini-g gun.
British Geological Survey (BGS) Sampling Survey 2015/7 RD2 Rockdrill Trials: Firth of Lorne/East of Colonsay (19/Aug/2015 to 29/Aug/2015)
This marine sampling survey took place in August 2015 in the area of Firth of Lorne and east of Colonsay on board the NLV Pharos. The survey was carried out by the British Geological Survey (BGS). The aim of the survey was to test the BGS seabed rockdrill RD2. These data are archived by BGS.
Sample equipment types used included: Drill: Multi-barrel. The survey was undertaken by British Geological Survey. Samples were collected using the BGS seabed rockdrill RD2.
UKCCSRC Call 1 Project: Chemical looping for low-cost oxygen production and other applications
While chemical looping (combustion, CLC) is a promising technology for carbon capture, however many questions still remain as to its applicability at an industrial scale. In Chemical looping combustion a metal oxide is shuttled back and forth between a fuel and air reactor, picking up oxygen in the air reactor and transferring it to the fuel reactor. The fuel is never mixed with the nitrogen from the air, so a stream of CO2 and H2O is produced directly from the fuel reactor; this potentially makes the integrated power production and CO2 capture system highly efficient. Most CLC and CLOU schemes envisage using fluidised beds in which the solid fuel is intimately mixed with the oxygen carrier, or mixing of the solid fuel particles. This project aims to push forward chemical looping within the UK and integrates both experimental work and theoretical analysis to result in the first large-scale demonstration of CLC within the UK. Grant number: UKCCSRC-C1-39.
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.
Either : (i) the dataset has not been formally approved by BGS for access and use by external clients under license; and / or (ii) the dataset contains 3rd party data or information obtained by BGS under terms and conditions that must be consulted before the dataset can be provided to, or accessed by, BGS staff or external clients. 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 access restrictions. This staff member should revert to the IPR Section (IPR@bgs.ac.uk) for advice, should the position not be clear.
UKCCSRC Call 1 project, grant number: UKCCSRC-C1-39, Lead institution: Imperial College London
Simulated yields and transmissivities for the weathered basement aquifer of Northern Ghana (ODA grants NE/R000069/1, NE/M008827/1)
This dataset was generated with a novel process-based stochastic modelling approach to investigate the productivity and sustainability of groundwater abstractions in the Precambrian basement aquifer in Ghana. The statistical distribution of the generated synthetic yield data was found in very good agreement with observed yield data from the same Ghanaian aquifer. The dataset includes more than 40,000 simulated values of maximum allowable yield and corresponding transmissivity values for different realisations of aquifer heterogeneity, net recharge values, and borehole depth. Further details about the dataset and the method of generation and collection can be found in the article by Bianchi et al. (2020) "Investigating the productivity and sustainability of weathered basement aquifers in tropical Africa using numerical simulation and global sensitivity analysis" published in the Water Resources Research journal. This research was supported by the UKRI British Geological Survey NC-ODA grant NE/R000069/1 and NE/M008827/1.
A numerical experiment was designed to generate a comprehensive synthetic dataset of maximum allowable yields for the weathered Precambrian basement aquifer of Northern Ghana. Details of the experiment are described in the paper published in Water Resources Research: "Investigating the productivity and sustainability of weathered basement aquifers in tropical Africa using numerical simulation and global sensitivity analysis" by Marco Bianchi, Alan M. MacDonald, David M.J. Macdonald, and Enoch B. Asare
NERC Earth Observation Data Centre (NEODC)
Airborne Research and Survey Facility (ARSF)
NERC EDS Environmental Information Data Centre
https://catalogue.ceda.ac.uk/uuid/326bf808aedd41fd85594fc06678d20a 326bf808aedd41fd85594fc06678d20a esacci.CLOUD.mon.L3C.CLD_PRODUCTS.multi-sensor.multi-platform.ATSR2-AATSR.3-0.r1.v20200422
ESA Cloud Climate Change Initiative (Cloud_cci): ATSR2-AATSR monthly gridded cloud properties, version 3.0
The Cloud_cci ATSR2-AATSRv3 dataset (covering 1995-2012) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on measurements from the ATSR2 and AATSR instruments (onboard the ERS2 and ENVISAT satellites) and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL; Sus et al., 2018; McGarragh et al., 2018) retrieval framework. The core cloud properties contained in the Cloud_cci ATSR2-AATSRv3 dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. The cloud properties are available at different processing levels: This particular dataset contains Level-3C (monthly averages and histograms) data, while Level-3U (globally gridded, unaveraged data fields) is also available as a separate dataset. Pixel-based uncertainty estimates come along with all properties and have been propagated into the Level-3C data. The data in this dataset are a subset of the ATSR2-AATSR L3C / L3U cloud products version 3.0 dataset produced by the ESA Cloud_cci project available from https://dx.doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003. To cite the full dataset, please use the following citation: Poulsen, Caroline; McGarragh, Greg; Thomas, Gareth; Stengel, Martin; Christensen, Matthew; Povey, Adam; Proud, Simon; Carboni, Elisa; Hollmann, Rainer; Grainger, Don (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci ATSR2-AATSR L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD) and Rutherford Appleton Laboratory (Dataset Producer), DOI:10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003
Public data: access to these data is available to both registered and non-registered users.
Under the following licence https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_cloud_terms_and_conditions.pdf, 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 here form a subset of the ATSR2-AATSR v3.0 products produced by the ESA Cloud CCI, a copy of which has been supplied to the Centre for Environmental Data Analysis in the context of the ESA CCI Open Data Portal Project. The full dataset is collectively referenced by the following DOI: Poulsen, Caroline; McGarragh, Greg; Thomas, Gareth; Stengel, Martin; Christensen, Matthew; Povey, Adam; Proud, Simon; Carboni, Elisa; Hollmann, Rainer; Grainger, Don (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci ATSR2-AATSR L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD) and Rutherford Appleton Laboratory (Dataset Producer), DOI:10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003.
ESA Cloud_cci cloud property datasets retrieved from passive satellite sensors: ATSR2-AATSR L3C/L3U cloud products - Version 3.0
Poulsen, C. A., Mcgarragh, G. R., Thomas, G. E., Stengel, M., Christiensen, M. W., Povey, A. C., Proud, S. R., Carboni, E., Hollmann, R., and Grainger, R. G.: Cloud_cci ATSR-2 and AATSR dataset version 3: a 17-yearclimatology of global cloud and radiation properties, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2019-217, in review, 2019.
Sus et al., 2018: The Community Cloud retrieval for CLimate (CC4CL) Part 1: A framework applied to multiple satellite imaging sensors, Atmos. Meas. Tech., 11, 3373-3396, https://doi.org/10.5194/amt-11-3373-2018, 2018
McGarragh et al., 2018: The Community Cloud retrieval for CLimate (CC4CL) Part 2: The optimal estimation approach, Atmos. Meas. Tech., 11, 3397-3431, https://doi.org/10.5194/amt-11-3397-2018, 2018
Previous dataset version (v2.0): Stengel et al., 2017: Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project, Earth Syst. Sci. Data, 9, 881-904, https://doi.org/10.5194/essd-9-881-2017, 2017
Product Validation and Intercomparison Report
Algorithm Theoretical Baseline Document (ATBD)
CC4CL algorithm description (ATBD CC4CL)
Centre for Environmental Data Analysis (CEDA)