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Land Use

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  • 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.

  • 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

  • The dataset contains chemistry data from streambed porewater (10 and 20 cm) and surface water, as well as nitrogen chemistry data at 2.5 cm resolution within the upper 15 cm of the streambed. The dataset includes concentrations of dissolved organic carbon (DOC), carbon dioxide, methane, ammonium, nitrate, nitrite and nitrous oxide, and isotopic ratios of δ13CCO2, δ15NNO3+NO2 and δ18ONO3+NO2. Also included are measurements of dissolved oxygen and temperature. Samples were collected from three reaches within the stream, an upstream sandy reach, a mid-stream sandy reach and a downstream gravel reach. The work was carried out with Natural Environment Research Council (NERC) funding through a PhD (NERC award number 1602135), grant (NE/L004437/1) and Life Sciences Mass Spectrometry Facility grant (CEH_L102_05_2016). Full details about this dataset can be found at https://doi.org/10.5285/00601260-285e-4ffa-b381-340b51a7ec50

  • 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 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

  • 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

  • These data are metrics of landscape configuration and modelled provision of Ecosystem services for a large number of virtual landscapes (c. 7500) superimposed on real topography. The landscapes are made up of patches of woodland interspersed across a grassland, and were generated with the landscapeR package in R. The topography used is from the Conwy catchment, split into 10 sections to enable comparison between topographies. Metrics were generated for each virtual landscape to quantify landscape configuration. An Ecosystem Services model (LUCI) was run to calculate a metric of “area mitigated” as a proxy for the provision of runoff mitigation Ecosystem Services. Simulated landscapes were established to answer two questions: firstly to identify the relative controls of patch area and fragmentation on service provision and secondly to identify catchment feature controls on these relationships. The work was done by Dario Masante and Amy Thomas, with input from Laurence Jones, as part of work under the NERC Biodiversity and Ecosystem Services (BESS) project NERC Grant Ref: NE/K015508/1. Full details about this dataset can be found at https://doi.org/10.5285/67f9fe33-14dd-4676-9a6d-65fdbafe2a46

  • CEH Land Cover plus: Pesticides maps annual average pesticide applications across England, Wales and Scotland. The product provides application estimates for 162 different active ingredients including herbicides, insecticides, molluscicides and fungicides. It is produced at a 1km resolution with units of kg active ingredient applied per year, averaged between 2012 and 2017. Pesticide application rates (kg/km2/yr) are calculated for each of the crops grown in each 1km square, using information from CEH Land Cover® Plus: Crops 2015, 2016 and 2017 to determine where each crop is grown. Pesticide application data is provided by the Pesticide Usage Survey. Uncertainty maps are produced alongside each active ingredient map to quantify the level of confidence in the estimated applications. Uncertainty is quantified using the distribution of each parameter estimate obtained from the modelling method and is expressed relative to the total application. The product builds upon the Centre for Ecology &amp; Hydrology (CEH) Land Cover® Plus: Crops product. These maps were created under the NERC funded ASSIST (Achieving Sustainable Agricultural Systems) project to enable exploration of the impacts of agrochemical usage on the environment, enabling farmers and policymakers to implement better, more sustainable agricultural practices. Full details about this dataset can be found at https://doi.org/10.5285/99a2d3a8-1c7d-421e-ac9f-87a2c37bda62

  • Ecological field data for a variety of biodiversity indicators were collected from commercial fields of both crops. The study is part of the NERC Rural Economy and Land Use (RELU) programme. Future policies are likely to encourage more land use under energy crops: principally willow, grown as short rotation coppice, and a tall exotic grass Miscanthus. These crops will contribute to the UK's commitment to reduce CO2 emissions. However, it is not clear how decisions about appropriate areas for growing the crops, based on climate, soil and water, should be balanced against impacts on the landscape, social acceptance, biodiversity and the rural economy. This project integrated social, economic, hydrological and biodiversity studies in an interdisciplinary approach to assessing the impact of converting land to Miscanthus grass and short-rotation coppice (SRC) willows. Two contrasting farming systems were focused on: the arable-dominated East Midlands; and grassland-dominated South West England. Ecological field data for a variety of biodiversity indicators were collected from commercial fields of both crops. The public attidues questionnaire data from this study are available at the UK Data Archive under study number 6615 (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 DATASET HAS BEEN WITHDRAWN]. This data product maps pesticide applications across England and Wales. It is produced at a 1km resolution with units of kg active ingredient applied per year. Pesticide application rates (kg/km2/yr) are calculated for each of the crops grown in each 1km square, with the total application calculated by multiplying the estimated rates by the area of each crop in the square. The product provides application estimates for 129 different active ingredients including herbicides, insecticides, molluscicides and fungicides. Uncertainty maps are produced alongside each active ingredient map to quantify the level of confidence in the estimated applications. Uncertainty is quantified using the distribution of each parameter estimate obtained from the modelling method and is expressed relative to the total application. The product is a snapshot of average applications between 2012 and 2016. The product builds upon the Centre for Ecology & Hydrology (CEH) Land Cover® Plus: Crops product. An average of CEH Land Cover® Plus: Crops 2015, 2016 and 2017 is used to reflect average crop coverage at the 1km resolution. Temporal variation in pesticide application is not modelled explicitly but is reflected in the uncertainty maps. This data product was funded by the Natural Environment Research Council (NERC) under research programme NE/N018125/1 Achieving Sustainable Agricultural Systems (ASSIST). ASSIST is an initiative jointly supported by NERC and the Biotechnology and Biological Sciences Research Council (BBSRC). Full details about this dataset can be found at https://doi.org/10.5285/a72f8ce8-561f-4f3a-8866-5da620c0c9fe