This dataset provides stream networks for three river basins in eastern Sri Lanka (Mundeni Aru, Maduru Oya and Miyangolla Ela). The stream networks were developed for use in hydrologic modelling and are provided as shapefiles. The work was supported by the Natural Environment Research Council (Grant NE/S005838/1). Full details about this dataset can be found at https://doi.org/10.5285/0537af26-5cab-4381-aca0-d997db421111

Tsunami trimlines identified across different islands of the Tonga archipelago. Trimlines have been used as a reference land feature following the January 2022 Tonga tsunami event that ripped off vegetation and built-up areas. Trimlines are distinctive limits between an area with sand coverage, vegetation destruction, and soil erosion on the one hand, and the unaffected natural vegetation on the other. This distinction provides a good landmark to map the inundation width and the landward extension of tsunami runup. In this case, the trimlines have been manually delineated by BGS - Earth Observation team using different high-resolution satellite datasets both optical (KompSat, Planet, Pleiades, WorldView) and radar (TerraSAR-X). Trimlines are well known from task-force publications documenting recent tsunami detection efforts and provide key information to support tsunami triggering mechanism models. For more info, see https://www.usgs.gov/media/images/tsunami-terms and Scheffers et al. (2012), https://doi.org/10.1007/s11069-010-9691-6

Waterlines have been extracted to delimit the edge of the Hunga Tonga - Hunga Ha'apai island between April 2017 and April 2022. Waterline is defined as the instantaneous land - water boundary at the time of the imaging process. Waterlines have been generated by BGS - Earth Observation team through a thresholding-based classification based on Sentinel-2 multispectral imagery and developed on Google Earth Engine. Specifically, the thresholding has been applied to the Normalized Difference Water Index (NDWI) has been derived as a basis to discriminate between the land and sea based on their spectral characteristics. Changes in waterlines over volcanic islands can provide key information to understand volcanic processes. For more info on the methodology, see Novellino et al. (2020) https://doi.org/10.3390/app10020536

This dataset is a characterisation of discontinuity types found within rocks and soils in Great Britain. Discontinuities are breaks, fractures or planes of weakness in the rock mass. The dataset includes type, frequency and orientation of discontinuities within rock and soil materials at formation (local to regional) scale. The discontinuities are classified in 3 categories: stratification (bedding planes), foliation (mineral banding) and rock mass description. The dataset aims to facilitate the preliminary research for planning and design of buildings, infrastructure and resource extraction. It forms part of the DiGMap Plus dataset series of GIS layers which describes the engineering properties of materials from the base of pedological soil down to c. 3m depth (ie the uppermost c.2m of geology). These deposits display a variable degree of weathering, but still exhibit core engineering characteristics relating to their lithologies.

This dataset consists of a vector layer (based on 1 by 1° grid), of modelled surface ozone concentrations (ppb). The values per cell are daily mean surface ozone for the period 6am – 6pm. The seasonal average has been calculated for the grassland growing season, for the period spanning mid-April to mid-July, for the UK and the USA, for 2018. Full details about this dataset can be found at https://doi.org/10.5285/4b0871a9-196a-48e1-a0c8-c5f53e17e9a7

This dataset contains the areas affected by landslides triggered by Typhoon Parma in the area of Itogon (Benguet, Philippines) between the 2nd and 5th October 2009. The polygons were mapped using Google Earth imagery dated 31 December 2003 for pre-event and images and 31 December 2009 for post-event images. The area has an extension of 150 km2. Full details about this dataset can be found at https://doi.org/10.5285/2e15dbd2-71c3-4e86-aa90-6029d37bd417

This dataset is the Corine Land Cover (CLC) change map between 2012 and 2018, consisting of 44 classes in the hierarchical three level Corine nomenclature. The Corine land cover changes between 2012 and 2018 for the UK, Isle of Man, Jersey and Guernsey dataset forms part of the Corine Land Cover Maps collection and is produced within the frame of the Copernicus programme on land monitoring. Corine Land Cover (CLC) provides consistent information on land cover and land cover changes across Europe; this change map is the UK component of the European coverage. This inventory was initiated in 1985 (reference year 1990) and established a time series of land cover information with updates in 2000, 2006 and 2012 being the last iteration. CLC products are based on photointerpretation 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) of status layers is 25 hectares; minimum width of linear elements is 100 metres; 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 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. More information about the Corine Land Cover (CLC) and Copernicus land monitoring data in general can be found at http://land.copernicus.eu/. Full details about this dataset can be found at https://doi.org/10.5285/027b6432-f44d-41ab-b349-89fae673d5f5

These spatial layers contain the predicted occurrence and abundance of three heathland shrubs, Arctostaphylos uva-ursi, Vaccinium myrtillus and Vaccinium vitis-idaea identified as susceptible host species for Phytophthora ramorum and Phytophthora kernoviae in Scotland. The distribution models were developed from quadrat vegetation data kindly provided by Scottish Natural Heritage combined with data on climate and soil conditions as well as deer abundance and were fitted using a Bayesian Generalised Mixed Modelling approach adapted for input data on the DOMIN scale. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forestry Commission, the Food and Environment Research Agency (FERA) and the Centre for Ecology & Hydrology (CEH). Full details about this dataset can be found at https://doi.org/10.5285/5749df3d-000c-445e-a37f-dc0763b4d5ec

This data set provides a spatial stratification of forest cover into discrete vegetation classes according to the High Carbon Stock (HCS) Approach. The data set covers the Stability of Altered Forest Ecosystems (SAFE) project site located in Sabah, Malaysian Borneo. Data were collected in 2015 during a project which was included in the NERC Human-modified tropical forest (HMTF) programme. Full details about this dataset can be found at https://doi.org/10.5285/81cad1ef-b5cc-4592-a71f-204a5d04b700

This dataset includes polygons representing ecosystem types (ET) and their respective ecosystem services (ES) and disservices (EDS) in the Luanhe River Basin, with attributes recording 14 ecosystem types (ET), 11 provisioning services (PS), ten regulating services (RS), five cultural services (CS), 7 Ecological integrity indicators (EI), and 11 ecosystem disservices (EDS). Full details about this dataset can be found at https://doi.org/10.5285/2252d8a4-0ef3-403f-b2c3-3f7acbcac1d5