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This dataset consists of image mosaics of submarine canyons off Morocco collected using TOBI side-scan sonar on RV Maria S. Merian cruise MSM32, which occurred between 25 September and 30 October 2013. Imaging was conducted using a TOBI deep tow sidescan sonar, a high-resolution 2D seismic system consisting of a 150m long 88 channel digital streamer and a standard GI-gun. This cruise formed the field component of NERC Discovery Science project ‘How do submarine landslides disintegrate and form long run-out turbidity currents in the deep ocean, and how erosive are these flows?’ The study aimed to generate the first ever field dataset tracing a large-scale submarine landslide and its associated sediment-gravity flow from source-to-sink. This resulting dataset will aim to answer three important science questions: 1) How quickly do large submarine landslides disintegrate into long run-out sediment flows, and how is this process influenced by shape of the slope? 2) How efficiently do landslides remove failed material, i.e. what proportion of landslide debris is deposited on the slope and how much transforms into a flow that is transported distally? 3) How much sediment is incorporated into the flow through seafloor erosion, and where does most of this erosion take place? The Discovery Science project was composed of Standard Grant reference NE/J012955/1 and was led by Professor Russell Barry Wynn (National Oceanography Centre, Science and Technology). Funding ran from 07 June 2013 to 06 June 2014. Data have been received by BODC as raw files from the RRS James Cook and are available on request from BODC enquiries.
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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 MODIS land cover classification data. The MODIS Land Cover Type product contains multiple classification schemes, which describe land cover properties derived from observations spanning a year's input of Terra and Aqua data. The primary land cover scheme identifies 17 land cover classes defined by the International Geosphere Biosphere Programme (IGBP), which includes 11 natural vegetation classes, 3 developed and mosaicked land classes, and three non-vegetated land classes. The MODIS Terra + Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid product incorporates five different land cover classification schemes, derived through a supervised decision-tree classification method: * Land Cover Type 1: IGBP global vegetation classification scheme * Land Cover Type 2: University of Maryland (UMD) scheme * Land Cover Type 3: MODIS-derived LAI/fPAR scheme * Land Cover Type 4: MODIS-derived Net Primary Production (NPP) scheme * Land Cover Type 5: Plant Functional Type (PFT) scheme The dataset stored here has been aggregated onto a 10 arc minute grid by Jose Gomez-Dans, working within the QUEST FIREMAFS project.
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Two collections of benthic still images were obtained using a downward-looking camera mounted on the UK ISIS Remotely Operated Vehicle (ROV), deployed from the RRS James Cook during cruise JC241, 2023. Three further benthic still image collections were acquired using the UK Autosub5 Autonomous Underwater Vehicle (AUV), deployed from the RRS James Cook during cruise JC257, 2024. All surveys were undertaken in the abyssal plain of the Clarion-Clipperton Zone (CCZ), Pacific Ocean (~4100-4700 m depth). The Grasshopper2 GS2-GE-50S5C camera system was mounted on each vehicle and captured vertically orientated still images at a target altitude of 2.5 - 3 m above the seabed. One ROV survey from JC241 was undertaken to assess benthic biological patterns in an area disturbed by a deep-sea mining machine operated by the Ocean Minerals Company (OMCO) in 1979. The second ROV survey from JC241 and one AUV survey from JC257 was undertaken in the UK-1 exploration area. The second AUV survey from JC257 was undertaken 30 km south of the northern border of the UK-1 exploration area. The third AUV survey from JC257 was undertaken 100 km south of the northern border of the UK-1 exploration area. The surveys were undertaken to derive ecological understanding on the influence of seabed topography on seabed community composition. The data were collected by scientists from the National Oceanography Centre, Southampton, UK as part of the NERC-funded Seabed Mining And Resilience To EXperimental impact (SMARTEX) project (NE/T003537/1).
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Benthic imagery and light attenuation data from Paluma Shoals, Halifax Bay, Great Barrier Reef, 2016
This dataset consists of underwater benthic imagery and measurements of light attenuation taken from Paluma Shoals in the Coral Sea following a 2016 El Niño coral bleaching event. Data were collected between 09 and 11 August 2016. Benthic imagery was captured using a SeaViewer Sea-Drop™ Camera (950 Analog model) on 10 August 2016. Light attenuation measurements were taken using a LiCOR LI-192SA Light Meter deployed at a range of depths below the sea surface. These cruises formed the field component of NERC Discovery Science project "Quantifying ENSO-related bleaching on nearshore, turbid-zone coral reefs grant story”. The data were collected following a major El Niño event which caused mass coral bleaching across the Great Barrier Reef. The event provided opportunity to undertake a rapid assessment of the impacts of bleaching on the turbid-zone reefs in the vicinity of Paluma Shoals (central Halifax Bay). The aim of the project is to ascertain: 1) The total extent of bleaching-induced mortality; 2) The extent to which specific coral species have been impacted; 3) Any immediate impacts on the structural complexity and diversity of the reefs. The Discovery Science project was composed of Standard Grant NE/P007694/1. The grant was held by the University of Exeter, School of Geography and led by Professor Christopher Perry. The funding period ran from 01 July 2016 to 31 March 2017. All data described have been received by BODC from the RRS James Clark Ross and will be processed and made available online in the future. Raw data are available on request. No further data are expected from this project.
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A coastline of Kalaallit Nunaat/ Greenland covering all land and islands, produced in 2017 for the BAS map ''Greenland and the European Arctic''. The dataset was produced by extracting the land mask from the Greenland BedMachine dataset and manually editing anomalous data. Some missing islands were added and glacier fronts were updated using 2017 satellite imagery. The dataset can be used for cartography, analysis and as a mask, amongst other uses. At very large scales, the data will appear angular due to the nature of being extracted from a raster with 150 m cell size, but the dataset should be suitable for use at most scales and can be edited by the user to exclude very small islands if required. The projection of the dataset is WGS 84 NSIDC Sea Ice Polar Stereographic North, EPSG 3413. The dataset does not promise to cover every island and coastlines were digitised using the data creator''s interpretation of the landforms from the images.
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A geographic database of lakes on the Antarctic Peninsula compiled over the past five years from a number of information sources: satellite images, aerial photography, old maps and reports. The database fields include: Lake unique id; Name; location; imager reference/how identified; locality; size (longest axis); area; type (as per Hutchinson''s lake classification); reference - any existing scientific work on the lake; salinity; depth; x co-ordinate; y co-ordinate. Many of the lakes are previously unknown, and very few have been studied before. The list represents the first attempt to collate all the lakes in the area into one usable dataset. The data is available as a down-loadable text file with point co-ordinates, or as a polygon coverage downloadable from the Antarctic Digital database.
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Polar View delivers a range of environmental information services for the polar regions derived primarily from satellite imagery and data. The project aims to coordinate delivery of these information products direct to users. Services include enhanced sea ice information (charts and forecasts) as well as ice-edge and iceberg monitoring data. We also provide monitoring services for lake and river ice, snow cover maps and glacier monitoring and assessment. any services are delivered in near real time and are readily accessible via the Internet.
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The dataset contains BioCam visual seafloor mapping device from data collected between 23rd September to 5th October 2022. These data were collected by the University of Southampton and the National Oceanography Centre (NOC) as part of the INSITE (Influence of man-made structures in the ecosystem) AT-SEA (Autonomous Techniques for anthropogenic Structure Ecological Assessment NE/T010649/1) project. Two shore-launched Autonomous Underwater Vehicles (AUVs) deployments were conducted in the North Sea, at the site of the decommissioned North West Hutton oil platform and Miller platform. These data include colour corrected strobed images, and cm-resolution bathymetry maps and texture maps. These data were collected using the BioCam seafloor mapping device mounted to the 6000 m rated Autosub Long Range (ALR). To collect colour imagery, a strobe was mounted at the front and another one at the back of the Autonomous Underwater Vehicle (AUV) and were used to illuminate the seafloor when the colour camera of BioCam, mounted at the centre of the AUV, acquired those images once every 3 s. The strobed colour images were stored in raw format along with their timestamps. A line laser mounted at the front and another one mounted at the back of the AUV projected lines onto the seafloor at the same time. The lasers were permanently on, except when the strobes were triggered, when they were briefly turned off to avoid projecting the laser lines onto the strobed colour photos. Images of the laser line projection were acquired at 10 Hz and saved along with their timestamps. Post mission, the strobed images were colour corrected with an algorithm implemented in oplab-pipeline in post processing. Bathymetric data were computed using the laser line images that were processed with a light-sectioning algorithm published by Bodenmann, Thornton and Ura (2016). Texture maps were generated by projecting the colour-corrected images onto the 3D reconstructed bathymetry as detailed by Bodenmann, Thornton and Ura (2016).
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A new version of this dataset exists. To see the last version of the Antarctic Digital Database, have a look here: https://data.bas.ac.uk/collections/e74543c0-4c4e-4b41-aa33-5bb2f67df389/ Coastline for Antarctica created from various mapping and remote sensing sources, provided as polygons with ''land'', ''ice shelf'', ''ice tongue'' or ''rumple'''' attribute. Covering all land and ice shelves south of 60S. Suitable for topographic mapping and analysis. Data compiled, managed and distributed by the Mapping and Geographic Information Centre and the UK Polar Data Centre, British Antarctic Survey on behalf of the Scientific Committee on Antarctic Research. Major changes in v7.4 include updates to coastline and ice shelves between Gipps Ice Rise and Ronne Ice Shelf, updated ice shelf fronts for Brunt, Stange and West ice shelves, Pine Island Glacier, and an updated coastline for Adelaide Island.
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A new version of this dataset exists. To see the last version of the Antarctic Digital Database, have a look here: https://data.bas.ac.uk/collections/e74543c0-4c4e-4b41-aa33-5bb2f67df389/ A medium resolution seamask for regions south of 60S, comprised of a roundel polygon with all land and ice shelves erased.