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  • A digital elevation model of the bed of Rutford Ice Stream, Antarctica, derived from radio-echo sounding data. The data cover an 18 x 40 km area immediately upstream of the grounding line of the ice stream. This area is of particular interest because repeated seismic surveys have shown that rapid erosion and deposition of subglacial sediments has taken place. The bed topography shows a range of different subglacial landforms including mega-scale glacial lineations, drumlins and hummocks. This dataset will form a baseline survey which, when compared to future surveys, should reveal how active subglacial landscapes change over time. The dataset comprises observed ice thickness data, an interpolated bed elevation grid, observed surface elevation data and a surface elevation grid.

  • The data set contains values of basal slipperiness (C) and the rate factor (A) for the whole of the Antarctic Ice Sheet. The slipperiness was estimated through model inversion from measurements of surface velocities (1) and ice thickness (2) using the ice-flow model Ua (3). The ice was assumed to deform according to Glen''s flow law with a stress exponent n=3. Basal sliding was assumed to follow Weertman sliding law with m=3, with u_b = C tau^m, where u_b is the basal sliding velocity and tau the (tangential) basal traction.

  • A netcdf-formatted file containing the original binned data (described in Shore et al [2017]), in their state before they were subjected to EOF analysis. These have had additional processing applied to the SuperMAG data (publically available at http://supermag.jhuapl.edu/) in the form of sampling them to the centroid of the bins, thus they are worth providing here despite the large file size (approximately 12GB). To conserve file space, we have removed empty bins, thus the temporal and spatial basis for these data are provided for each filled bin element. Please note that the binned data had not had the temporal mean values (described in Shore et al [2017], and available in the Supporting Information) removed when they were stored in this netcdf file. The file contains 144 (monthly) sets of 8 variables. These variables are named: 1: filled_bin_data_YYYYMM_r 2: filled_bin_data_YYYYMM_theta 3: filled_bin_data_YYYYMM_phi Variables 1 to 3 contain the nanoTesla vales of the binned data for each of the three magnetic field components in the Quasi-Dipole frame. 4: filled_bin_contrib_stations_YYYYMM The three-letter SuperMAG acronym of the station which contributed to each 5-minute mean data point. 5: filled_bin_colats_YYYYMM 6: filled_bin_longs_YYYYMM Variables 5 and 6 are the co-latitude and longitude coordinates of each filled bin element. 7: filled_bin_times_YYYYMM The 5-minute-mean epoch of each filled bin element, with columns in the order: year, month, day, hour, minute, second). 8: filled_bin_indices_YYYYMM A set of fiducial values describing how the sparse elements of the 1D vector of filled bin values relate to the fiducials of the (transposed!) EOF prediction a 2D matrix product of the spatial and temporal eigenvectors with values in every bin. An example of the usage of these data is given in the MATLAB program Shore-ms01.m, provided in the Supporting Information of Shore et al [2017]. ***** PLEASE BE ADVISED TO USE VERSION 2.0 DATA ***** The VERSION 2.0 data set has been corrected for a bug which led to the bins which span the local midnight meridian having fewer samples than they should. The data density in these bins is now in-line with the rest of the polar coverage. Apart from that change, the original and updated data sets are the same.

  • A netcdf-formatted file containing the original binned data (described in Shore et al [2017]), in their state before they were subjected to EOF analysis. These have had additional processing applied to the SuperMAG data (publically available at http://supermag.jhuapl.edu/) in the form of sampling them to the centroid of the bins, thus they are worth providing here despite the large file size (approximately 12GB). To conserve file space, we have removed empty bins, thus the temporal and spatial basis for these data are provided for each filled bin element. Please note that the binned data had not had the temporal mean values (described in Shore et al [2017], and available in the Supporting Information) removed when they were stored in this netcdf file. The file contains 144 (monthly) sets of 8 variables. These variables are named: 1: filled_bin_data_YYYYMM_r 2: filled_bin_data_YYYYMM_theta 3: filled_bin_data_YYYYMM_phi Variables 1 to 3 contain the nanoTesla vales of the binned data for each of the three magnetic field components in the Quasi-Dipole frame. 4: filled_bin_contrib_stations_YYYYMM The three-letter SuperMAG acronym of the station which contributed to each 5-minute mean data point. 5: filled_bin_colats_YYYYMM 6: filled_bin_longs_YYYYMM Variables 5 and 6 are the co-latitude and longitude coordinates of each filled bin element. 7: filled_bin_times_YYYYMM The 5-minute-mean epoch of each filled bin element, with columns in the order: year, month, day, hour, minute, second). 8: filled_bin_indices_YYYYMM A set of fiducial values describing how the sparse elements of the 1D vector of filled bin values relate to the fiducials of the (transposed!) EOF prediction a 2D matrix product of the spatial and temporal eigenvectors with values in every bin. An example of the usage of these data is given in the MATLAB program Shore-ms01.m, provided in the Supporting Information of Shore et al [2017]. ***** PLEASE BE ADVISED TO USE VERSION 2.0 DATA ***** The VERSION 2.0 data set (see ''Related Data Set Metadata'' link below) has been corrected for a bug which led to the bins which span the local midnight meridian having fewer samples than they should. The data density in these bins is now in-line with the rest of the polar coverage. Apart from that change, the original and updated data sets are the same.

  • **This dataset has been superseded. The latest version is newGeoSure Insurance Product version 8 2020.1**The newGeoSure Insurance Product (newGIP) provides the potential insurance risk due to natural ground movement. It incorporates the combined effects of the 6 GeoSure hazards on (low-rise) buildings. This data is available as vector data, 25m gridded data or alternatively linked to a postcode database – the Derived Postcode Database. A series of GIS (Geographical Information System) maps show the most significant hazard areas. The ground movement, or subsidence, hazards included are landslides, shrink-swell clays, soluble rocks, running sands, compressible ground and collapsible deposits. The newGeoSure Insurance Product uses the individual GeoSure data layers and evaluates them using a series of processes including statistical analyses and expert elicitation techniques to create a derived product that can be used for insurance purposes such as identifying and estimating risk and susceptibility. The Derived Postcode Database (DPD) contains generalised information at a postcode level. The DPD is designed to provide a ‘summary’ value representing the combined effects of the GeoSure dataset across a postcode sector area. It is available as a GIS point dataset or a text (.txt) file format. The DPD contains a normalised hazard rating for each of the 6 GeoSure themes hazards (i.e. each GeoSure theme has been balanced against each other) and a combined unified hazard rating for each postcode in Great Britain. The combined hazard rating for each postcode is available as a standalone product. The Derived Postcode Database is available in a point data format or text file format. It is available in a range of GIS formats including ArcGIS (*.shp), ArcInfo Coverages and MapInfo (*.tab). More specialised formats may be available but may incur additional processing costs. The newGeoSure Insurance Product dataset has been created as vector data but is also available as a raster grid. This data is available in a range of GIS formats, including ArcGIS (*.shp), ArcInfo coverage’s and MapInfo (*.tab). More specialised formats may be available but may incur additional processing costs. Data for the newGIP is provided for national coverage across Great Britain. The newGeoSure Insurance Product dataset is produced for use at 1:50 000 scale providing 50 m ground resolution. This dataset has been specifically developed for the insurance of low-rise buildings. The GeoSure datasets have been developed to identify the potential hazard for low-rise buildings and those with shallow foundations of less than 2 m deep. The identification of ground instability and other geological hazards can assist regional planners; rapidly identifying areas with potential problems and aid local government offices in making development plans by helping to define land suited to different uses. Other users of these data may include developers, homeowners, solicitors, loss adjusters, the insurance industry, architects and surveyors. Version 7 released June 2015.

  • The K-index scale summarises geomagnetic activity at an observatory by assigning a code, an integer in the range 0 to 9 (0 being the least active field and 9 the most active field) to each 3-hour Universal Time (UT) interval. K-Indices are available for Lerwick, Eskdalemuir, Greenwich, Abinger and Hartland Magnetic Observatories. From 1954-90 the values are hand scaled, from 1991 to the present day they are automatically scaled. The data not only aids scientific research into rates of change of the magnetic field and increases the accuracy of the BGS Global Geomagnetic Model, but also provides data to exploration geophysicists engaged in current and future oil exploration.

  • The NIGL (NERC Isotope Geosciences Laboratories) laboratory records comprise paper output from mass spectrometers, which is retained for 5 years from the date of analysis, and mass spectrometer loading sheets, which are retained indefinitely. NIGL is a comprehensive stable and radiogenic isotope laboratory facility that undertakes environmental, life, archaeological and earth science research, and educates and trains PhD students, in a collaborative research environment.

  • This is the core collection of photographs in BGS it represents photographs taken by professional photographers and selected by subject and quality for public reference in the BGS libraries. The collection dates from c 1890 to c.1995 and is organized in a series of sub-collections depending on which office the photographers were based. The collection covers photography taken in the field during the geological mapping programme. Series A, the main Land Survey collection for England and Wales, are all taken by professional photographers and are of high quality. Dates from c.1890 to the start of the current "P" system, the first 7500 are glass plates. Series B, Edinburgh, part of the main Land Survey collection for Scotland, full plate size and all glass plates. Series C, Edinburgh, part of the main Land Survey collection for Scotland, half plate size. Series D, Edinburgh, part of the main Land Survey collection for Scotland consists of large format negative size with additional 35mm transparencies, earlier parts of the collection are black and white, later, colour. Series L, Keyworth, the main Land Survey collection for Northern England and Wales emanating from the Leeds Office, all are taken by professional photographers and include large format black and white, colour originals and colour 35 mm transparencies. Access constraints are only physical constraints relating to handling negatives and glass plates. scans are available in the Geoscience Imagebase. Photographs are either: Out of copyright; Crown or NERC.

  • This data set contains land cover/land use data for the year 1990 and 2015 obtained through processing of Landsat images of US Geological Survey. These data sets were obtained through a supervised classification carried out with Landsat 8 image for 2015; Landsat 4 and 5 were used for land use classification of 1990. Gro for GooD: Groundwater Risk Management for Growth and Development

  • The Single Onshore Borehole Index (SOBI) is an index of over 1 million boreholes, shafts and wells and references collections of digital and analogue records from all forms of drilling and site investigation work held by the BGS. The index covers onshore and near shore boreholes from Great Britain dating back to at least 1790 and ranging from one to several thousand metres deep. Some 50,000 new boreholes are added each year. The majority of the records contain written descriptions of the ground encountered. The SOBI index database originated in 1988 from a number of existing tables and from data input from a variety of coding forms. Therefore not all fields in the database are populated and data that should be in some fields may currently form part of the entries in another. The index is available on the BGS website via the Geoindex