Keyword

Land cover

73 record(s)
 
Type of resources
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
From 1 - 10 / 73
  • Categories  

    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.

  • 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.

  • Categories  

    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.

  • 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.

  • 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.

  • 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.

  • 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. 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.

  • The BEDMAP (Bed Topography of the Antarctic) database contains data collected on surveys over the past 50 years that describe the thickness of the Antarctic ice sheet. This has allowed the compilation of a suite of seamless digital topographic models for the Antarctic continent and surrounding ocean. The suite includes grids representing: - ice-sheet ... thickness over the ice sheet and shelves, - water-column thickness beneath the floating ice shelves, - bed elevation beneath the grounded ice sheet, - bathymetry to 60 degrees South including the areas beneath the ice shelves. These grids are consistent with a recent high-resolution surface elevation model of Antarctica. While the digital models have a nominal spatial resolution of 5 km, such high resolution is not strictly justified by the original data density over all parts of the ice sheet. The suite does however provide an unparalleled vision of the geosphere beneath the ice sheet and a more reliable basis for ice sheet modelling. The bed elevation DEM, which includes the entire geosphere south of 60 degrees South, provides an improved delineation of the boundary between East and West Antarctica and sheds new light on the morphology of the contiguous East Antarctic landmass, much of which is buried below an average of 2500 m of ice.

  • 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. This dataset has been generalised from the high resolution vector polygons. Medium resolution versions of ADD data are suitable for scales smaller than 1:1,000,000, although certain regions will appear more detailed than others due to variable data availability and coastline characteristics. Changes in v7.6 include updates to the Amery Ice Shelf front, ice shelves and glaciers east of Law Dome, and sections of coast and ice shelf around Abbot Ice Shelf and Pine Island Glacier. 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.

  • We present here the land cover classification across West Antarctica and the McMurdo Dry Valley produced from Landsat-8 Operational Land Imager (OLI) images of six proglacial regions of Antarctica at 30 m resolution, with an overall accuracy of 77.0 % for proglacial land classes. We conducted this classification using an unsupervised K-means clustering approach, which circumvented the need for training data and was highly effective at picking up key land classes, such as vegetation, water, and different sedimentary surfaces. This work is supported by the Leeds-York-Hull Natural Environment Research Council (NERC) Doctoral Training Partnership (DTP) Panorama under grant NE/S007458/1. The Ministry of Education, Youth and Sports of the Czech Republic project VAN 1/2022 and the Czech Antarctic Foundation funded fieldwork that contributed to part of this work.