This is a 10m pixel data set representing the land surface, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. The pixel product is given as a two-band raster in geoTiff format. The first band gives the most likely land cover type; the second band gives the probability associated with this land cover. The probability layer is an indicator of uncertainty (rescaled 0 to 100). Low values correspond to low certainty (higher 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/10.5285/78d3824b-2612-4707-ae2e-26f82bdd5dad

The data contains Aerial imagery of Ynyslas Dunes, Wales saved in a GeoTiff format. The imagery covers 8000 m2 of a discrete coastal sand dune at northern distal end of a spit in Dyfi National Nature Reserve. Data was collected during a six-minute flight on 5th February 2020 made by a DJI Mavic Pro 2 uncrewed aerial vehicle (UAV). The flight was planned with Pix4DCapture based on a ground pixel resolution of 0.01 m. Lateral and longitudinal overlap was set to 80%. Prior to flying, eight (5.8 per 100 photos) Ground Control Points (GCPs) were evenly distributed throughout the dune and their location surveyed using a differential global positioning system (DGPS). Orthorectification and mosaicking of the aerial imagery collected was performed using Pix4Dmapper utilising a fully automated workflow based on Structure-from-Motion (SFM) digital photogrammetry algorithms. The data was collected to test the accuracy and repeatability of bare sand and vegetation cover in dunes mapped from aerial imagery. Data was collected and processed by Dr Ryan Wilson (University of Huddersfield) and interpreted by Dr Thomas Smyth (University of Huddersfield). The work was supported by the Natural Environment Research Council NE/T00410X/1. Full details about this dataset can be found at https://doi.org/10.5285/ac7071cb-79a3-400d-9f17-13dc4a657083

This dataset is a fine resolution 2018 land cover map of the headwaters region of the Welland River Catchment, UK, projected in British national grid. It has a spatial resolution of 10m and thematic resolution of 10 classes. The map covers a 340km2 region across the English counties of Leicestershire, Rutland and Northamptonshire with predominantly agricultural land use. Full details about this dataset can be found at https://doi.org/10.5285/63b748ee-22a4-42ca-8a34-20321f6ab8af

This dataset consists of a 1km resolution raster version of the Land Cover Map 2000 for Northern Ireland. Each 1km pixel represents the dominant aggregate class across the 1km area. The aggregate classes are aggregations of the target classes, broadly representing Broad Habitats (see below). 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. 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/f6fc7bd4-6525-4850-b832-24b6c05b8074

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

This dataset consists of the vector version of the Land Cover Map 2000 for Northern Ireland, 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. 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/10.5285/9f043047-d1c7-4852-b513-aa00204022a8

[THIS DATASET HAS BEEN WITHDRAWN]. The Land Cover Map of Great Britain 1990 (1km percentage target class, GB), is a raster digital dataset, providing a classification of land cover types into 25 classes, at a 1km resolution. The dataset consists of a set of 1km bands, each containing one of 25 target classes (or 'sub' classes). Each band of the dataset contains the percentage of the specified habitat class per 1km, derived from a higher resolution (25m) dataset. The map was produced using supervised maximum likelihood classifications of Landsat 5 Thematic Mapper satellite data. The 25 mapped classes include sea and inland waters, bare, suburban and urban areas, arable farmland, pastures and meadows, rough grass, grass heaths and moors, bracken, dwarf shrub heaths and moorland, scrub, deciduous and evergreen woodland, and upland and lowland bogs. It can potentially be used to plan, manage or monitor agriculture, ecology, conservation, forestry, environmental assessment, water supplies, urban spread, transport, telecommunications, recreation and mineral extraction. The map was produced in the early 1990s by a forerunner of the Centre for Ecology & Hydrology, the Institute of Terrestrial Ecology, at Monks Wood. Note: The bands in the dataset run from 1-26, not 0-25 as stated in the documentation. Hence '1' is unclassifed (not '0'), '2' is sea/estuary and so on. Full details about this dataset can be found at https://doi.org/10.5285/0172cc8c-8b5c-46cf-b08a-785ab832e88c

This is a 10-metre pixel data set representing the land surface, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. The pixel product is given as a two-band raster in geoTiff format. The first band gives the most likely land cover type; the second band gives the probability associated with this land cover. The probability layer is an indicator of uncertainty (0 to 100). Low values correspond to low certainty (higher uncertainty). This is the first 10m resolution land cover map produced by UKCEH. It succeeds 20m resolution classified pixel products from 2017, 2018 and 2019. A full description of this and all UKCEH LCM2020 products are available from the product documentation accompanying this data. Full details about this dataset can be found at https://doi.org/10.5285/35c7d0e5-1121-4381-9940-75f7673c98f7

The data comprise Sentinel-2 derived burn severity rasters covering restored and unrestored reaches of the South Fork McKenzie river, Oregon USA. The data were collected in order to quantify differences in burn severity in restored and unrestored river reaches following the Holiday Farm wildfire in 2020. Raw satellite imagery acquired in June 2020 and June 2021 was processed to calculate Normalised Burn Ratio (NBR), giving pre- and post-fire burn severity information. Data consist of 10 m .TIF raster imagery where a digital number gives a measure of burn severity; high NBR values indicate healthy vegetation, whereas lower values indicate burnt areas or bare ground. The study was conducted by the University of Nottingham, in partnership with the US Forest Service, Portland State University, Washington State University and Colorado State University. Funding for the work was received from the Natural Environment Research Council. Full details about this dataset can be found at https://doi.org/10.5285/8162887a-5481-440f-a7f2-427eee793efd

3D digital elevation models of Tsho Rolpa glacier lake, Nepal, generated from unmanned aerial vehicle (UAV) imagery, with a spatial resolution of 10 centimetres. It is combined with bathymetry data so that both the lakebed elevation (DTM) and the lake surface elevation (DSM) are obtained. Full details about this dataset can be found at https://doi.org/10.5285/8e483692-3b65-41d2-a7fd-5a3cd589a71c