NERC Data Catalogue Service
NERC Data Catalogue Service (Natural Environment Research Council)
Continents, countries, sea regions of the world.
Daily automatic weather station (AWS) data from Climoor fieldsite in Clocaenog Forest, UK, 2024
This dataset holds daily data from one automated weather station (AWS) located at the Climoor field site in Clocaenog forest, North East Wales. The data are on relative humidity (percent), air temperature (degrees Celsius), rainfall (millimetres), air pressure (millibars), net radiation (millivolts), solar radiation (kilowatts per square metre per second), photosynthetic active radiation (PAR), (micromol per square metre per second), wind speed (metres per second) and wind direction (degrees). Data is an extension for the AWS datasets 1999-2015, 2015-2016, 2016-2021, 2022-2023 and covering the time period January 2024 to December 2024. Data are logged in minute intervals, averaged to half-hourly. Data are sent from the field site to a UKCEH server. A working copy is created, quality assurance checks carried out and daily averages calculated from half-hourly records. Data which were not recorded are marked with “NA”, faulty data were replaced by “-9999”. Note, the rainfall sensor was broken during this time period, but the column is kept in the datafile for consistency with previous data records. Data collection, processing and quality checking was carried out by members of CEH and UKCEH staff. The following measures were taken with sensors from Campbell Scientific: Rainfall sums are measured with an ARG100 Tipping bucket, air pressure is measured with a CS100 Barometer. Further, Solar radiation and PAR are measured using a Skye SP1110 pyranometer and a SKP215 quantum sensor from Skye Instruments. Wind direction and speed were recorded using a windsonic 2D Ultrasonic Anemometer from Windsonic. The Climoor field experiment intends to answer questions regarding the effects of warming and drought on ecosystem processes. The reported data are collected to monitor site specific environmental conditions and their development over time. These data are important to interpret results that are collected from the climate change manipulations imposed in the field. Full details about this dataset can be found at https://doi.org/10.5285/6b3b766f-4d04-4a41-b2a4-6ca2dd1ea23a
If you reuse this data, you should cite: Reinsch, S., Hatton, J. (2025). Daily automatic weather station (AWS) data from Climoor fieldsite in Clocaenog Forest, UK, 2024. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/6b3b766f-4d04-4a41-b2a4-6ca2dd1ea23a
This resource is available under the terms of the Open Government Licence
Data were recorded every minute, then automatically averaged to half-hourly data by the data-logger. The half-hourly data were transferred from loggers at the field site onto UKCEH Bangor servers via remote telemetry. Each morning, the previous day’s data was transferred to the server. Data were then averaged to daily values. An automated script transferred the data into the project shared area of the shared network drive. Data quality checking was performed at the end of each calendar year. Telemetered data were processed using R. Data were averaged to daily values and inspected visually. Erroneous values were removed taken into account the annual cycle. A .csv file was produced from the quality assessed data. The following measures were taken with sensors from Campbell Scientific: relative humidity and air temperature are recorded with an HMP45C sensor. Rainfall sums are measured with an ARG100 Tipping bucket, air pressure is measured with a CS100 Barometer and net radiation is measured with an NR-Lites sensor. Further, Solar radiation and PAR are measured using a Skye SP1110 pyranometer and a SKP215 quantum sensor from Skye Instruments. Wind direction and speed are recorded using a windsonic 2D Ultrasonic Anemometer from Windsonic.
This dataset consists of the vector version of the Land Cover Map 2000 for Great Britain, containing individual parcels of land cover (the highest available resolution). Level 2 & Level 3 attributes are available. Level 2, the standard level of detail, provides 26 LCM2000 target or ('sub') classes. This is the most widely used version of the dataset. Level 3 gives higher class detail. However, the quality of this level of detail may vary in different areas of the country, requiring expert interpretation. The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2000. LCM2000 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990. Like the earlier 1990 products, LCM2000 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2000 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2000 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. Full details about this dataset can be found at https://doi.org/10.5285/b79e887e-a2a7-4224-8fd7-e78066b950b3
Bespoke licensing terms apply to these data. If you choose to download the data, the CEH Data Licensing team will contact you to negotiate a licence
If you reuse this data, you should cite: Fuller, R.M., Smith, G.M., Sanderson, J.M., Hill, R.A., Thomson, A.G., Cox, R., Brown, N.J., Clarke, R.T., Rothery, P., Gerard, F.F. (2002). Land Cover Map 2000 (vector, GB). NERC Environmental Information Data Centre https://doi.org/10.5285/b79e887e-a2a7-4224-8fd7-e78066b950b3
In a major development of earlier methods, LCM2000 used image segmentation to identify land parcels in the pixel-based images. An automated procedure grouped the image pixels into spectrally 'uniform' segments. These were built around 'seedpoints' selected to avoid parcel boundaries. The segmentation recorded a field-by-field pattern, also separating land use zones within urban and suburban areas, and subdividing mosaics of semi-natural vegetation. Generalisation gave minimum mappable units of a half hectare. A 'vector' version was then created in the geographical information system (GIS), where the boundaries between the pixel-based segments were represented by digital linework. The resultant land parcels were treated as GIS objects to which attribute data could then be attached covering such topics as land cover class, parcel area, length of boundary, processing history, knowledge-based correction and identification of the original satellite scene. The raster products have been derived from the vector dataset. LCM2000 was produced at CEH Monks Wood. For further information on the methodology developed and used to create Land Cover Map 2000, see on-line supporting documentation.
Future Flows Climate (FF-HadRM3-PPE) is an eleven-member ensemble climate projection for Great Britain at a 1-km resolution spanning from 1950 to 2098. It was specifically developed for hydrological application and contain daily time series of Available Precipitation, which is the precipiated water available to hydrological processes after delays due to snow and ice storage are accounted for; and monthly reference Potential Evapotranspiration calculated using the FAO56 method. Future Flows Climate is derived from the Hadley Centre's Regional climate projection ensemble HadRM3-PPE based on 11 different variants of the regional climate model run under the SRES A1B emission scenario. HadRM3-PPE is underpinning the UKCP09 products. Bias correction and spatial downscaling were applied to the total precpitation and air temperature variables before Future Flows Climate APr and PE were generated. The development of Future Flows Climate was made during the partnership project 'Future Flows and Groundwater Levels' funded by the Environment Agency for England and Wales, Defra, UK Water Research Industry, NERC (Centre for Ecology & Hydrology and British Geological Survey) and Wallingford HydroSolutions. Full details about this dataset can be found at https://doi.org/10.5285/bad1514f-119e-44a4-8e1e-442735bb9797
If you reuse this data, you should cite: Prudhomme, C., Dadson, S., Morris, D., Williamson, J., Goodsell, G., Crooks, S., Boolee, L., Davies, H., Buys, G., Lafon, T. (2012). Future flows climate data. NERC Environmental Information Data Centre https://doi.org/10.5285/bad1514f-119e-44a4-8e1e-442735bb9797
Registration is required to access this data
A modified version of the 11-member HadRM3-PPE ensemble projection assuming SRES-A1B emissions scenario developed for hydrological application in March 2012. It cover land areas of Great Britain at a 1-km resolution and contains 11 sets of 1951-2098 equally likely time series for two data types daily Available Precipitation (incorporating delays due to water storage as snow and ice) and monthly Potential Evapotranspiritation time series. Future Flows Climate used a monthly bias-correction and downscaling procedure based on the Gamma distribution (precipitation) and linear model (temperature). Potential Evapotranspiration is calculated using the FAO56 formulation with monthly bias-corrected downscaled temperature and HadRM3-PPE original time series for the other variables. As Future Flows Climate datasets are derived from climate model outputs they do not replicate the historical weather but are possible realisations of the climate. Despite the use of bias-correction and downscaling procedures Future Flows Climate might still contain some differences with observed climate and cannot be compared directly with gauged values. SC090016/PN2, SC090016/PN3 SC090016/PN5 project technical notes provide details on the methods used and results.
Eddy covariance measurements of carbon dioxide, energy and water fluxes at an organically managed grassland, Berkshire, UK, 2017 to 2019
This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at an area of organically managed grassland located on the Berkshire Downs, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 1st January 2017 and 31st July 2019. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/5a93161f-0124-4650-a2c9-7e8aaea7e6bb
If you reuse this data, you should cite: Morrison, R., Cooper, H., Cumming, A., Scarlett, P., Thornton, J., Winterbourn, J.B. (2019). Eddy covariance measurements of carbon dioxide, energy and water fluxes at an organically managed grassland, Berkshire, UK, 2017 to 2019. NERC Environmental Information Data Centre https://doi.org/10.5285/5a93161f-0124-4650-a2c9-7e8aaea7e6bb
Eddy covariance (EC) and micrometeorological observations were made using an open-path eddy covariance system. Ancillary meteorological and soil physics observations were obtained from a co-located COSMOS-UK station. Turbulent flux densities were calculated from the raw EC data using the EddyPRO® Flux Calculation Software Version 6.1. Quality Control of EC data involved removal of statistical outliers and tests that theoretical requirements for the successful application of the EC technique were not violated significantly. Data gaps in EC data (NEE, LE, H) and the partitioning of NEE into gross ecosystem production and total ecosystem production were performed using the REddyProc Package for R (Reichstein et al., 2019). Further details are available in the supporting documentation.
Experimental data on herbivorous pest insects, predatory insect occurrence and population growth rates of artificially established aphids from three crops
This dataset contains percentage cover of plants, mean numbers of aphids, mean counts of predators and mean counts of herbivores on three crops (field bean, wheat and oilseed rape) within different grassland types (improved, restored and species rich). Data were collected in 2013 on five farms in the Salisbury Plain area of the UK as part of the Wessex Biodiversity and Ecosystem Services Sustainability (BESS) project within the UK Natural Environment Research Council (NERC) BESS programme. This data set was used to provide an assessment of the potential for different grassland types to provide natural pest control ecosystem services. The study uses sentinel plants of the three crops established in the grasslands to monitor herbivorous pest insects, predatory insect occurrence and the population growth rates of artificially established aphids. Full details about this dataset can be found at https://doi.org/10.5285/4c02ae08-5703-46f4-947e-80e5d0a34a28
If you reuse this data, you should cite: Woodcock, B.A., Bullock, J.M., Pywell, R.F. (2018). Experimental data on herbivorous pest insects, predatory insect occurrence and population growth rates of artificially established aphids from three crops. NERC Environmental Information Data Centre https://doi.org/10.5285/4c02ae08-5703-46f4-947e-80e5d0a34a28
This resource is made available under the terms of the Open Government Licence
Data has been checked for anomalous values following its entry from hand written sheets to electronic spreadsheet. Invertebrate identification was verified by comparison to museum held material at the Oxford University Museums of Natural History.
Behavioural experiments in the laboratory with stickleback fish - Fish personality data
The data consist of eight datasets on stickleback fish personality data. Data are on catch order, mean time spent out of cover, proportion of time fish spent out of cover, sex differences for the catch order, sex differences for the catch order on two occasions and sex differences in the proportion of time spent out of cover. A laboratory population of three-spined sticklebacks (Gasterosteus aculeatus) were filmed and timed using a high definition camera. The work was carried out between March 2012 and February 2013 at The Structure and Motion Laboratory, Royal Veterinary College.The work was funded by a BBSRC studentship and NERC (grant NE/H016600/2 Does diversity deliver? How variation in individual knowledge and behavioural traits impact on the performance of animal groups) All animal care and experimental procedures described here were approved as non-regulatory procedures by the Ethics and Welfare Committee of the Royal Veterinary College, London (URN 2011 1084). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/9c7fe956-0ae6-46b6-bca2-2be5778e46bd
If you reuse this data, you should cite: Furtbaer, I., Mamuneas, D., James, C., Manica, A., King, A. (2015). Behavioural experiments in the laboratory with stickleback fish - Fish personality data. NERC Environmental Information Data Centre https://doi.org/10.5285/9c7fe956-0ae6-46b6-bca2-2be5778e46bd
Tests of exploratory behaviour were undertaken in isolation in test tanks, and a Panasonic HDC-SD60 high-definition video camera, mounted directly above the tanks were used to record fish movements. Times were recorded of time taken for fish to locate reward. Each fish net-caught from their aquarium was assigned a catch number. 1 was allocated to the fish that was caught first, 2 allocated to the fish that was caught second and so on and tests of exploratory behaviour.
Mapped stream networks for the Mundeni Aru, Maduru Oya and Miyangolla Ela river basins in eastern Sri Lanka
This dataset provides stream networks for three river basins in eastern Sri Lanka (Mundeni Aru, Maduru Oya and Miyangolla Ela). The stream networks were developed for use in hydrologic modelling and are provided as shapefiles. The work was supported by the Natural Environment Research Council (Grant NE/S005838/1). Full details about this dataset can be found at https://doi.org/10.5285/0537af26-5cab-4381-aca0-d997db421111
If you reuse this data, you should cite: Matthews, J.B.R., Jayaratne, R., Raby, A. (2024). Mapped stream networks for the Mundeni Aru, Maduru Oya and Miyangolla Ela river basins in eastern Sri Lanka. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/0537af26-5cab-4381-aca0-d997db421111
Natural and artificial watercourses were manually mapped using satellite imagery from Google Earth and their widths measured. The resulting stream networks have been checked for integrity, including to ensure lines are snapped at vertices and points ordered in the downhill direction.
UK Environmental Change Network (ECN) butterfly data: 1993-2015
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 2015. 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/10.5285/5aeda581-b4f2-4e51-b1a6-890b6b3403a3
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., Flexen, M., Gardiner, A., Hamilton, D., Hargreaves, P., Hatton-Ellis, M., Howe, M., Kahl, J., Lane, M., Langan, S., Lloyd, D., McCarney, B., 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., Wood, C. (2017). UK Environmental Change Network (ECN) butterfly data: 1993-2015. NERC Environmental Information Data Centre https://doi.org/10.5285/5aeda581-b4f2-4e51-b1a6-890b6b3403a3
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.
The Isle of May long-term study (IMLOTS) seabird annual return rate 1988-2016
[THIS DATASET HAS BEEN WITHDRAWN]. This dataset contains calculated return rates for five seabird species from representative colonies on the Isle of May, off the East coast of Scotland. Annual return rates are measured as the number of individually colour marked individuals seen in any one year that were also observed in the previous year for the Atlantic puffin (Fratercula arctica), common guillemot (Uria aalge), razorbill (Alca torda), European shag (Phalacrocorax aristotelis) and black-legged kittiwake (Rissa tridactyla). Not every individual is seen in any one year and the data set does not take into account those missed in any previous years hence these data are not to be treated as survival estimates. The Isle of May long-term study (IMLOTS) aims to identify the impact of environmental change on seabirds and their associated ecosystems. Understanding the mechanisms underlying variation in seabird population size requires a thorough knowledge of demographic parameters, namely birth rates, death rates, immigration and emigration. The effects of environmental change are likely to be different according to which demographic parameter or life history stage is being considered. This complexity means that only long-term monitoring, such as that carried out on the Isle of May, will allow us to understand the functioning of bird populations and their responses to environmental change. Full details about this dataset can be found at https://doi.org/10.5285/53251b3c-6c79-4aeb-a0de-fc63b9350cc1
If you reuse this data, you should cite: Newell, M., Harris, M.P., Wanless, S., Burthe, S., Bogdanova, M., Gunn, C.M., Daunt, F. (2016). The Isle of May long-term study (IMLOTS) seabird annual return rate 1988-2016. NERC Environmental Information Data Centre https://doi.org/10.5285/53251b3c-6c79-4aeb-a0de-fc63b9350cc1
Data collected by CEH staff. All fieldwork, sampling and data handling was carried out by experienced and trained staff to defined protocols agreed to meet the objectives of the work. All data was collected in the field in notebooks and field data sheets. These were transcribed to spreadsheets after each check was made and files backed up to CEH directories. All notebooks and fieldsheets are archived at CEH Edinburgh. The Isle of May is one of four key UK seabird monitoring sites supported by the JNCC (Joint Nature Conservation Committee). CEH has an on-going contract with JNCC to collect data on seabird demography and diet. The data, including that on annual breeding success, feed into the national Seabird Monitoring Programme network.
Land Cover Map 2015 (1km dominant target class, GB)
This dataset consists of the 1km raster, dominant target class version of the Land Cover Map 2015 (LCM2015) for Great Britain. The 1km dominant coverage product is based on the 1km percentage product and reports the habitat class with the highest percentage cover for each 1km pixel. The 21 target classes are based on the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompass the entire range of UK habitats. This dataset is derived from the vector version of the Land Cover Map, which contains individual parcels of land cover and is the highest available spatial resolution. LCM2015 is a land cover map of the UK which was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. LCM2015 consists of a range of raster and vector products and users should familiarise themselves with the full range (see related records, the CEH web site and the LCM2015 Dataset documentation) to select the product most suited to their needs. LCM2015 was produced at the Centre for Ecology & Hydrology by classifying satellite images from 2014 and 2015 into 21 Broad Habitat-based classes. It is one of a series of land cover maps, produced by UKCEH since 1990. They include versions in 1990, 2000, 2007, 2015, 2017, 2018 and 2019. Full details about this dataset can be found at https://doi.org/10.5285/c4035f3d-d93e-4d63-a8f3-b00096f597f5
If you reuse this data, you should cite: Rowland, C.S., Morton, R.D., Carrasco, L., McShane, G., O'Neil, A.W., Wood, C.M. (2017). Land Cover Map 2015 (1km dominant target class, GB). NERC Environmental Information Data Centre https://doi.org/10.5285/c4035f3d-d93e-4d63-a8f3-b00096f597f5
The 1km dominant cover target class is produced from the 1km percentage cover target class product. The 1km percentage cover data is used to identify the highest percentage cover across the 21 bands and a script is used to identify which band the maximum value coincides with.
NERC EDS Environmental Information Data Centre
Invertebrate herbivory data across a natural soil temperature gradient in Iceland from May-July 2017
This is a dataset of environmental data, vegetation cover, and community- and species-level invertebrate herbivory, sampled at 14 experimental soil plots in the Hengill geothermal valley, Iceland, from May to July 2017. The plots span a temperature gradient of 5-35 °C on average over the sampling period, yet they occur within 1 km of each other and have similar soil moisture, pH, nitrate, ammonium, and phosphate. Full details about this dataset can be found at https://doi.org/10.5285/da5d7028-2aec-4da2-96ff-f347a0dfa77e
If you reuse this data, you should cite: O'Gorman, E.J., Warner, E., Marteinsdóttir, B., Helmutsdóttir, V.F., Ehrlén, J., Robinson, S.I. (2021). Invertebrate herbivory data across a natural soil temperature gradient in Iceland from May-July 2017. NERC Environmental Information Data Centre https://doi.org/10.5285/da5d7028-2aec-4da2-96ff-f347a0dfa77e
Herbivory assessments were made at the plant community and species levels. We focused on three plant species with a widespread occurrence across the temperature gradient: cuckooflower (Cardamine pratensis, Linnaeus), common mouse-ear (Cerastium fontanum, Baumgerten), and marsh violet (Viola palustris, Linnaeus). For assessments of invertebrate herbivory at the species level, thirty individuals per species of C. pratensis, C. fontanum, and V. palustris were marked in each of ten plots, using a stratified random sampling method where individuals were randomly selected, but the full range of within-plot soil temperatures was represented. For assessments of invertebrate herbivory at the community level, five 50 × 50 cm quadrats were marked at random points in eight of the plots that best captured the full temperature gradient. The community-level herbivory assessment was conducted on 19th June. The number of damaged plants was recorded out of 100 random individuals, selected using a 10 × 10 grid within each 50 × 50 cm quadrat. For the species-level herbivory assessment, individual marked plants were surveyed for signs of invertebrate herbivory every two weeks from 30th May to 2nd July, generating three time-points per species. At each survey, all marked individuals for each species were assessed within a 48-hour period. Plants were recorded as damaged or not damaged by invertebrate herbivores at each time-point. Further details of how phenological stage of development, vegetation community composition, soil temperature, moisture, pH, nitrate, ammonium, and phosphate were recorded are provided in the supporting documentation.
ITE Land Classification of Great Britain 2007
The Land Classification 2007 is a classification of Great Britain into a set of 45 environmental strata, termed land classes, to be used as a basis for ecological survey, originally developed by the Institute of Terrestrial Ecology (ITE) in the late 1970s and building upon previous 1990 and 1998 versions. The strata were created from the multivariate analysis of 75 environmental variables, including climatic data, topographic data, human geographical features and geology data. The Land Classification can be used to stratify a wide range of ecological and biogeographical surveys to improve the efficiency of collection, analysis and presentation of information derived from a sample. The Land Classification 2007 provided stratification for the Countryside Survey of Great Britain 2007 and was adjusted from the 1998 version as a consequence of needing to provide National Estimates for habitats for Wales from Countryside Survey 2007 in addition to Scotland and GB as a whole. Both the 1990 version and the 1998 versions are also available. Full details about this dataset can be found at https://doi.org/10.5285/5f0605e4-aa2a-48ab-b47c-bf5510823e8f
If you reuse this data, you should cite: Bunce, R.G.H., Barr, C.J., Clarke, R.T., Howard, D.C., Scott, W.A. (2007). ITE Land Classification of Great Britain 2007. NERC Environmental Information Data Centre https://doi.org/10.5285/5f0605e4-aa2a-48ab-b47c-bf5510823e8f
The 2007 version of the ITE Land Classification was developed from earlier classifications from 1990 and 1998 which used environmental data from all 240,000 km squares in GB to create the stratifications. It contains 45 classes or strata, distributed across Great Britain. Each stratum consists of areas with similar environmental characteristics. The classification differs from the 1998 version by splitting classes in England and creating additional classes in Wales. Further information is provided in the supporting documents available in the Online Resources.