[This dataset is embargoed until December 1, 2023]. This data contains values of bare sand area, modelled wind speed, aspect and slope at a 2.5 m spatial resolution for four UK coastal dune fields, Abberfraw (Wales), Ainsdale (England), Morfa Dyffryn (Wales), Penhale (England). Data is stored as a .csv file. Data is available for 620,756.25 m2 of dune at Abberfraw, 550,962.5 m2 of dune at Ainsdale, 1,797,756.25 m2 of dune at Morfa Dyffryn and 2,275,056.25 m2 of dune at Penhale. All values were calculated from aerial imagery and digital terrain models collected between 2014 and 2016. For each location, areas of bare sand were mapped in QGIS using the semi-automatic classification plugin (SCP) and the minimum distance algorithm on true-colour RGB images. The slope and aspect of the dune surface at each site was calculated in QGIS from digital terrain models. Wind speed at 0.4 m above the surface of the digital terrain model at each site was calculated using a steady state computational fluid dynamics (CFD). Data was collected to statistically test the relationship between bare sand and three abiotic physical factors on coastal dunes (wind speed, dune slope and dune slope aspect). Vertical aerial imagery was sourced from EDINA Aerial Digimap Service and digital terrain models from EDINA LIDAR Digimap Service. Wind speed data was generated and interpreted by Dr Thomas Smyth (University of Huddersfield). Full details about this dataset can be found at https://doi.org/10.5285/972599af-0cc3-4e0e-a4dc-2fab7a6dfc85

This view shows a 1km resolution raster version of the Land Cover Map 2007 for Great Britain. The data consists of 23 bands. Each band represents a target class, broadly representing a Broad Habitat, and within the band each 1km pixel represents a percentage cover value of that class. The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2007. LCM2007 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 and LCM2000. Like the earlier 1990 and 2000 products, LCM2007 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. LCM2007 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 LCM2007 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions.

This dataset shows potential carbon storage as modelled for the urban areas of Milton Keynes/Newport Pagnell, Bedford, and Luton/Dunstable, UK. The modelling approach used the ‘InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) 3.1.0’ ecosystem service model suite, raster land cover maps at two spatial resolutions (5 m and 25 m) and published literature values for carbon storage by land cover. The resulting data are presented in the form of two ‘GeoTIFF’ raster map files (and associated metadata and spatial information files required by software) that can be viewed and manipulated in Geographic Information Software. The units are kg C per square meter. The purpose of the modelling was to help assess and visualise the value that urban green space represents to urban residents and natural systems in just one of many ecosystem services. This research was conducted as part of the larger 'Fragments, Functions, Flows and Urban Ecosystem Services' (F3UES) programme. Detailed methods and results of this analysis are published in: Grafius DR, Corstanje R, Warren PH, et al (2016) The impact of land use/land cover scale on modelling urban ecosystem services. Landsc Ecol 31:1509–1522. doi: 10.1007/s10980-015-0337-7. Full details about this dataset can be found at https://doi.org/10.5285/9209af2c-24f6-4e37-98fe-550032e97a2c

Estimates of annual volumes of manure produced by six broad farm livestock types for England and Wales at 10 km resolution, modelled with MANURES-GIS [1]. The farm livestock classes are: dairy cattle; beef cattle; pigs; sheep and other livestock; laying hens; broilers and other poultry. The quantities produced by each type are subsequently apportioned into managed and field-deposited manure. The managed manure sources are categorised as beef farmyard manure, beef slurry, dairy farmyard manure, dairy slurry, broiler litter, layer manure, pig farmyard manure, pig slurry and sheep farmyard manure. The destinations are recorded as grass, winter arable, spring arable and direct excreta when grazing. For each 10 km square, the quantity of manure going from each source to each destination is estimated. The values specify amount of excreta, in kilograms for solid manure and in litres for liquid manure. [1] ADAS (2008) The National Inventory and Map of Livestock Manure Loadings to Agricultural Land: MANURES-GIS. Final Report for Defra Project WQ0103 Full details about this dataset can be found at https://doi.org/10.5285/517717f7-d044-42cf-a332-a257e0e80b5c

Data on resilience of wheat yields in England, derived from the annual Defra Cereals and Oilseeds production survey of commercial farms. The data presented here are summarised over a ten-year time-series (2008-2017) at 10km x10km grid cell (hectad) resolution. The data give the mean yield, relative yield, yield stability and resistance to an extreme event (the poor weather of 2012), for all hectads with at least one sampled farm holding in each year of the time-series (i.e. the minimum data required to calculate the resilience metrics). These metrics were calculated to explore the impact of landscape structure on yield resilience. The data also give the number of samples per year per hectad, so that sampling biases can be explored and filtering applied. No hectads are included that contain data from <9 holdings across the time series (the minimum level required by Defra to maintain anonymity is <5). The data were created under the ASSIST (Achieving Sustainable Agricultural Systems) project by staff at the UK Centre for Ecology & Hydrology to enable exploration of the impacts of agriculture on the environment and vice versa, enabling farmers and policymakers to implement better, more sustainable agricultural practices. Full details about this dataset can be found at https://doi.org/10.5285/7dbcee0c-00ca-4fb2-93cf-90f2a5ca37ea

This dataset for the UK, Jersey and Guernsey contains the Corine Land Cover (CLC) changes between 2006 and 2012. This shapefile has been created by combining the land cover change layers from the individual CLC database files for the UK, Jersey and Guernsey. CLC is a dataset produced within the frame of the Initial Operations of the Copernicus programme (the European Earth monitoring programme previously known as GMES) on land monitoring. CLC provides consistent information on land cover and land cover changes across Europe. This inventory was initiated in 1985 (initial reference year 1990) and then established a time series of land cover information with updates in 2000 and 2006 with the last one being for the 2012 reference year. CLC products are based on the analysis of satellite images by national teams of participating countries - the EEA member and cooperating countries - following a standard methodology and nomenclature with the following base parameters: - 44 classes in the hierarchical three level Corine nomenclature - Minimum mapping unit (MMU) for Land Cover Changes (LCC) for the change layers is 5 hectares. The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important information supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. Full details about this dataset can be found at https://doi.org/10.5285/35fecd0f-b466-448b-94d1-0bba90be450e

This dataset for the UK, Jersey and Guernsey contains the Corine Land Cover (CLC) revised for 2006. This shapefile has been created from combining the 2006 land cover layers from the individual CLC database files for the UK, Jersey and Guernsey. CLC is a dataset produced within the frame of the Initial Operations of the Copernicus programme (the European Earth monitoring programme previously known as GMES) on land monitoring. CLC provides consistent information on land cover and land cover changes across Europe. This inventory was initiated in 1985 (initial year 1990) and then established a time series of land cover information with updates in 2000 and 2006 the last one being the 2012 reference year. CLC products are based on the analysis of satellite images by national teams of participating countries - the EEA member and cooperating countries - following a standard methodology and nomenclature with the following base parameters: * 44 classes in the hierarchical three level Corine nomenclature; * Minimum mapping unit (MMU) for status layers is 25 hectares; * Minimum width of linear elements is 100 metres; The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important datasets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. Full details about this dataset can be found at https://doi.org/10.5285/2d0cf17f-aabd-4be6-859b-55c3403bbd9a

This dataset consists of palaeoecological measurements taken at sites in the Peak District and NW Sutherland during the NERC Rural Economy and Land Use (RELU) programme. This data collection includes the results from four interlinked projects combining quantitative and qualitative evidence to assess long-term ecological data at local to national levels: Project 1 synthesises existing information on historical environmental changes in the uplands with relevance to current management and policy Project 2 used high resolution palaeoenvironmental analyses to reconstruct ecological changes and land-use histories of four contrasting moorland systems in the Peak District (England) over the last c.200-1300 yrs. Sites were selected in consultation with stakeholders and the results provide the basis for comparison with ecological survey results and knowledge of current managers. Project 3 used similar methods to reconstruct ecological and land-use changes in NW Sutherland (Scotland) over the last c.400 yrs. Site selection was based on discussion with stakeholders and results were compared with stakeholder knowledge and preferences for landscape change. Project 4 used three choice experiments to assess the response of different communities to long-term evidence as a potential source of information to inform preferences for upland management. Project 4a used a choice experiment to assess the influence of long-term evidence on management preferences of residents of the Peak District. Project 4b used choice experiments to present long-term evidence to ecologists from government, NGO, research and practitioner communities in conjunction with established sources of ecological evidence used in upland management (ecological monitoring and ecological research) and with stakeholder preferences for upland management, since this is increasingly becoming embedded in decision-making. The upland woods and peatlands were used as the contexts for two choice experiments. This dataset consists of palaeoecological measurements taken at sites in the Peak District and NW Sutherland, as part of projects 2 and 3 as listed above. The choice experiment data from this study are available at the UK Data Archive under study number 6791 (see online resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

This is the land parcels (polygon) dataset for the UKCEH Land Cover Map of 2019 (LCM2019) representing Northern Ireland. It describes Northern Ireland's land cover in 2019 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived from the corresponding LCM2019 20m classified pixels dataset. All further LCM2019 datasets for Northern Ireland are derived from this land parcel product. A range of land parcel attributes are provided. These include the dominant UKCEH Land Cover Class given as an integer value and a range of per-parcel pixel statistics to help assess classification confidence and accuracy; for a full explanation please refer to the dataset documentation. LCM2019 represents a suite of geospatial land cover datasets (raster and polygon) describing the UK land surface in 2019. These were produced at the UK Centre for Ecology & Hydrology by classifying satellite images from 2019. LCM2019 was simultaneously released with LCM2017 and LCM2018. These are the latest in a series of UKCEH land cover maps, which began with the 1990 Land Cover Map of Great Britain (now usually referred to as LCM1990) followed by UK-wide land cover maps LCM2000, LCM2007 and LCM2015. 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/10.5285/6e67cba0-c872-4146-bc09-d6c98731f3b3

The dataset contains model output from an agricultural land use model at kilometre scale resolution over Great Britain (GB) for four different climate and policy scenarios. Specifically, arable area is modelled for with or without a climate tipping point (standard (medium emissions scenario SRES-A1B) climate change vs Atlantic Meridional Overturning Circulation (AMOC) collapse) and with or without widespread irrigation use for farmers from 2000 to 2089. Full details about this dataset can be found at https://doi.org/10.5285/e1c1dbcf-2f37-429b-af19-a730f98600f6