The dataset provides raster gridded estimates of open water and inundated vegetation for the Barotseland Region in Western Zambia. There are a total of 55 images covering the period 2016-2019 at a spatial resolution of 10m. The images were generated using an automatic classification routine applied to Sentinel-1 radar imagery, with classification refinements made using ancillary datasets such as the Global Urban Footprint, and the Height Above Nearest Drainage terrain derivative generated using SRTM digital elevation data. These data are valuable for a range of applications including public health and water resources. Full details about this dataset can be found at https://doi.org/10.5285/4ef558d2-05d4-4ae2-988e-a5c2450b95dd

This dataset contains a map of ground movements covering the Afar Rift Zone in Ethiopia, Eritrea, and Djibouti for the time period between October 2014 and August 2019. The Afar region is located where three tectonic plates are pulling apart, creating rift segments which are 50-100 km long. Surface deformation on these segments is not constant in time, with episodes of rifting occurring periodically and magma intrusions causing sudden ground movements. We use frequent Sentinel-1 satellite Interferometric Synthetic Aperture Radar (InSAR) observations to measure surface displacements through time across the whole region. We relate these to ground based Global Navigation Satellite Systems (GNSS) observations and combine data from different satellite tracks to produce maps of the average surface velocity in three directions (perpendicular to the rift zone, parallel to the rift zone, and vertical). The continued observation of these time-varying ground movements is important for understanding how continents break up, with data here providing evidence of how tightly focussed extension is around the rift segments and of the subsurface magma movement at several volcanic centres.

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains a map of a ecosystem. This map depicts the 825 terrestrial ecoregions of the globe. Ecoregions are relatively large units of land contain ing distinct assemblages of natural communities and species, with boundaries that approximate the original extent of natural communities prior to major land-use change. This comprehensive, global map provides a useful framework for conducting biogeographical or macroecological research, for identifying areas of outstanding biodiversity and conse rvation priority, for assessing the representation and gaps in conservation efforts worldwide, and for communicating the global distribution of natural communities on earth.

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

This is a web map service (WMS) for the Land Cover Map 2024 at 1 kilometre resolution The target data comprise 21 UKCEH land cover classes based upon Biodiversity Action Plan broad habitats. The aggregate data ,groups some of the more specialised target classes into more general classes and comprises 10 classes. For example, the five coastal classes in the target class are grouped into a single aggregate class.

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 LCM2023 products are available from the LCM2023 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/ab10ea4a-1788-4d25-a6df-f1aff829dfff

This 1 km summary pixel data set represents the land surface of Great Britain and Northern Ireland, classified using two classification schemas, target and aggregate classes. The target class schema comprise 21 UKCEH land cover classes based upon Biodiversity Action Plan broad habitats. The aggregate class schema comprises 10 aggregate classes that are groupings of the 21 target classes. The aggregate classes group some of the more specialised target classes into more general classes. For example, the five coastal classes in the target class are grouped into a single aggregate class. The 1km percentage product provides the percentage cover for each of the 21 land cover classes for 1km x 1km pixels. This product contains one band per habitat class, producing 21 and 10 band images for the target and aggregate class products respectively. The 1km dominant coverage product is based on the 1km percentage product, and reports the land cover class with the highest percentage cover for each 1km pixel. A full description of this and all UKCEH LCM2021 products are available from the LCM2021 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/a3ff9411-3a7a-47e1-9b3e-79f21648237d

The dataset contains three modelled estimates of global ammonia emissions from seabird colonies, at a spatial resolution of 0.1 degrees latitude/longitude. The model estimates were derived with a) detailed global seabird population data collated from a large number of sources (data sources date from 1980-2010 for different parts of the world) b) climate data (source: High-resolution Gridded Datasets, Climatic Research Unit, University of East Anglia, UK. http://www.cru.uea.ac.uk/cru/data/hrg/ last updated by Harris, I. (2007), date: 1995) c) emission model derived by Riddick et al. (2012) with funding for the project from the CEH Integrating Fund (NERC). A detailed description and discussion of the datasets, including methodology and uncertainties, can be found in the following peer-reviewed article: S. N. Riddick, U. Dragosits, T. D. Blackall, F. Daunt, S. Wanless and M. A. Sutton (2012) The global distribution of ammonia emissions from seabird colonies. Atmospheric Environment, 55 (2012), pp. 319-327 https://doi.org/10.1016/j.atmosenv.2012.02.052 Full details about this dataset can be found at https://doi.org/10.5285/c9e802b3-43c8-4b36-a3a3-8861d9da8ea9

This is a 10m 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 two-band raster in GeoTiff format. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover. A full description of this and all UKCEH LCM2024 products are available from the LCM2024 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/db1ea1f3-4101-4a52-b2b3-582473f724ea

This is a vector data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. This vector Land Parcel dataset is the result of intersecting the 10m raster classified pixel dataset with the UKCEH Land Parcel Spatial Framework to generate summary land parcel attributes for each land cover parcel. A full description of this and all UKCEH LCM2024 products are available from the LCM2024 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/99ecdc84-5313-48c2-9fad-6a5e8ad3953e