This is a 25m pixel data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a three-band raster in GeoTiff format, produced by rasterising three properties of the classified land parcels dataset. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover, the third band is a measure of parcel purity. The probability and purity bands (scaled 0 to 100) combine to give an indication of uncertainty. A full description of this and all UKCEH LCM2020 products are available from the LCM2020 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/c1d73bd3-33aa-4a5f-aac5-47c403c2a0e6

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

This is the 25m rasterised land parcels dataset for the UKCEH Land Cover Map of 2017 (LCM2017) representing Great Britain. It describes Great Britain's land cover in 2017 using UKCEH Land Cover Classes, which are based on UK Biodiversity Action Plan broad habitats. This dataset was derived by rasterising the corresponding LCM2017 land parcels dataset into 25m pixels. It is provided as a 3-band, 8-bit integer raster. The first band is the UKCEH Land Cover Class identifier. Bands 2 and 3 are indicators of classification confidence. For a fuller description please refer to the product documentation. 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/10.5285/499212cd-d64a-43ba-b801-95402e4d4098

This is a 25m pixel data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a three-band raster in GeoTiff format, produced by rasterising three properties of the classified land parcels dataset. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover, the third band is a measure of parcel purity. The probability and purity bands (scaled 0 to 100) combine to give an indication of uncertainty. A full description of this and all UKCEH LCM2023 products are available from the LCM2023 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/becb5f16-948f-407b-8fa3-f7762ba6efb6

This is a 25m pixel data set representing the land surface of Great Britain, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a three-band raster in GeoTiff format, produced by rasterising three properties of the classified land parcels dataset. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover, the third band is a measure of parcel purity. The probability and purity bands (scaled 0 to 100) combine to give an indication of uncertainty. A full description of this and all UKCEH LCM2021 products are available from the LCM2021 product documentation accompanying this dataset. Full details about this dataset can be found at https://doi.org/10.5285/a1f85307-cad7-4e32-a445-84410efdfa70

The data contains bird species records from the Vale do Paraíba and Serra do Mar regions in the state of São Paulo, Brazil. Bird species were surveyed using point counts between December 2015 and February 2017, with four temporal replicates per point for which the number of replicates in which each bird species was detected is recorded. A total of thirty-four fragmented and fifteen near continuous land-use landscapes were surveyed using a nine-point grid system with each point separated by 75m. For fragmented landscapes three of the points were situated within a native forest fragment, three at the fragment edge and three in the surrounding matrix habitat. Fifteen fragments had a Eucalyptus plantation matrix and nineteen had a pasture matrix. Continuous land-use landscapes were split equally between native forest, plantation forest and pasture. A total of 267 bird species were detected across the different land-use types. Full details about this dataset can be found at https://doi.org/10.5285/45f5c9eb-7bd3-435f-97f3-ce149f3b381c

This data resource contains soil physico-chemical data from eight agricultural sites across the UK sampled during September 2022 and October 2022. For all sites, the data resource presents results for a range of soil characteristics including, pH, soil moisture, stone content, bulk density, organic matter content, soil texture, and total carbon and nitrogen content. Thermo-Gravimetric Analyses (TGA) was performed at one site due to atypically high values for total carbon content. The soil samples were collected using a Split tube sampler. The soil samples were processed at UKCEH laboratories from September 2022 through to August 2023. Sample collection and analysis was performed by project staff. The samples were taken to provide soil baseline data at the eight sites before the planting of perennial biomass crops. The project was funded by the Department for Energy Security & Net Zero (formally the Department for Business, Energy & Industrial Strategy (BEIS)) (Client reference - CEH-303). Full details about this dataset can be found at https://doi.org/10.5285/8c87a397-a010-48a4-8ca5-0f3742c2d857

This dataset consists of the 25m raster version of the Land Cover Map 2015 (LCM2015) for Northern Ireland. This is the most detailed of the LCM2015 raster products both thematically and spatially, and it is used to derive the 1km products. The 25m raster product consists of two bands: Band 1 - raster representation of the majority (dominant) class per polygon for 21 target habitat classes; Band 2 - mean per polygon probability as reported by the Random Forest classifier (see supporting information). 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/10.5285/47f053a0-e34f-4534-a843-76f0a0998a2f

This is a 25m pixel data set representing the land surface, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a three-band dataset in GeoTiff format, produced by rasterising three properties of the classified land parcels dataset. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover, the third band is a measure of parcel purity. The probability and purity bands (scaled 0 to 100) combine to give an indication of uncertainty. A full description of this and all UKCEH LCM2020 products are available from the LCM2020 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/6c22cf6e-b224-414e-aa85-900325baedbd

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. It also covers Northern Ireland and incorporates information derived from other ancillary datasets. LCM2007 was classified using a hierarchical 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, incorporating land cover classes sought by other users. LCM2007 is produced in both vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. This dataset consists of the 25m raster version, Northern Ireland only. Full details about this dataset can be found at https://doi.org/10.5285/08b78c4b-cd3f-4eeb-a9eb-9c3e88812f16