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Using the NASA EOSDIS Common Metadata Repository

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  • Alaska Tidewater Glacier Terminus Positions, Version 1

    https://cmr.earthdata.nasa.gov/search/concepts/C1386250732-NSIDCV0.xml
    Description:

    This data set contains Alaska tidewater glacier terminus positions digitized from USGS topographic maps and Landsat images.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 56.5 -151 61.5 -132

    NSIDCV0 Short Name: NSIDC-0634 Version ID: 1 Unique ID: C1386250732-NSIDCV0

  • Amery Ice Shelf Grounding Zone defined as interpreted slope break in MODIS images

    https://cmr.earthdata.nasa.gov/search/concepts/C1214311485-AU_AADC.xml
    Description:

    Grounding Zone of the Amery Ice Shelf, East Antarctica defined by break of surface slope as determined through interpretation of MODIS images. It defines the landward edge of the grounding zone and therefore the maximum extent of the ice shelf. The MODIS data from the 250 m Channel 2 were processed to a reflectance product and remapped to a Polar Stereographic Projection. The image contrast was stretched so that subtle variations in reflectance could be perceived. The variation in reflectance was used as an indicator of variation in slope. The break of slope of the snow surface was picked interactively on an image display at a frequency sufficient to define the shape of the grounding zone margin. The series of points are provided as a Point shapefile file as well as a set of arcs connecting the points. The point positions are given in geographic coordinates. This work was completed as part of ASAC projects 2224 and 3067 (ASAC_2224, ASAC_3067).

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -73.3 66.3 -68.4 74

    AU_AADC Short Name: aad_ais_gz_modis_slope_break Version ID: 1 Unique ID: C1214311485-AU_AADC

  • Amery Ice Shelf velocity time series from Landsat images

    https://cmr.earthdata.nasa.gov/search/concepts/C1214305516-AU_AADC.xml
    Description:

    A time series of ice velocity values have been derived by analysis of LandSat-7 ETM+ images for the Lambert Glacier and Amery Ice Shelf system. The analysis technique uses feature tracking in pairs of Landsat-7 ETM+ images. This process uses surface features that persist with time and move with the ice as tracers of the ice motion. The displacement of these features over the time interval between acquisition of the two images in a pair is determined by image correlation. The analysis is made at regular increments across and along the images, to produce a regular grid of values. The derived values are filtered and validated according to set of a prior constraints for the flow in a local region and the statistics of a set of velocity values within a window. The images have been projected onto a common reference system, and spliced together in order to produce a seamless set of velocity values. Horizontal components of strain rate are derived from the velocity data using a set of derivative operators in a least-squares solution of an over-constrained set of equations, which uses all velocity values within a computation window. This procedure effectively produces a set of average velocity and strain rate values and accounts for much of the noise in the individual velocity observations. Values of the local longitudinal, transverse and shear strain rate components are derived by rotation of the cartesian values to the local flow direction. The procedure is described in Young and Hyland (2002). This metadata record has been derived from work performed under the auspices of ASAC project 3067 (ASAC_3067).

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -75 62 -73 70

    AU_AADC Short Name: AAD_Ant_AIS_vel_series Version ID: 1 Unique ID: C1214305516-AU_AADC

  • AMSRIce03 Landsat-7 ETM+ Imagery, Version 1

    https://cmr.earthdata.nasa.gov/search/concepts/C1386250481-NSIDCV0.xml
    Description:

    This data set contains Landsat-7 Enhanced Thematic Mapper Plus (ETM+) satellite imagery of the Bering Sea and Chukchi Sea areas to complement the joint in situ and aircraft Advanced Microwave Scanning Radiometer Sea Ice Product Validation (AMSRIce03) campaign.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 58 -175 74 -145

    NSIDCV0 Short Name: NSIDC-0431 Version ID: 1 Unique ID: C1386250481-NSIDCV0

  • Analysis of Glacier Hazard Potentials By Knowledge-Based Remote Sensing Fusion for GIS Modeling (AGREG)

    https://cmr.earthdata.nasa.gov/search/concepts/C1214614963-SCIOPS.xml
    Description:

    Snow, glaciers and permafrost in cold mountain areas such as the Swiss Alps are especially sensitive to changes in environmental conditions due to their proximity to melting conditions. In addition, mass wasting is most intensive in those mountain areas with high relief energy. Environmental changes in high mountain regions substantially influence the potential for glacial and periglacial hazards. Ice- and moraine-dammed lakes represent a widespread hazard potential closely related to glacier fluctuations. Magnitude and frequency of ice avalanches from steep glaciers - in principle a normal expression of mass exchange under such topographic conditions - are coupled with stability conditions affected by glacier advance/retreat and, hence, with long-term atmospheric impacts. Steep and unstable reservoirs of loose debris, a potential source of debris flows, are often the result of glacier shrinkage. In a similar way, changes in the stress regime due to vanishing glaciers lead to potential destabilization of adjacent valley flanks. Since the Alps are among the most densely populated high mountain areas in the world, Switzerland is particularly impacted by glacial and periglacial hazards but, on the other hand, also has an extensive and well-recognized tradition in investigating such processes. A number of specific monitoring and modeling studies related to single hazardous situations have been performed, mainly based on recent catastrophes or imminent hazard situations. An urgent need exists for area-wide modeling of glacier hazard potentials with a view to establishing an integrated and adequate information base for planning and detailed monitoring, but a corresponding systematic approach is, for the present, still lacking. The proposed project aims at closing this gap in several ways: Work Package (WP) (1): By developing techniques for detection of glacier hazard potentials based on optical spaceborne remote sensing data which rarely has been used to date in Swiss glacier monitoring; multispectral analyses and multitemporal and multiscale fusion will play a major role in this, with a special focus on recent or upcoming high resolution sensors. WP (2): By integrating empirical models for glacier hazard assessment into geographical information systems (GIS) which have proven to be successful for hazard simulation but have not been used yet for determining glacier hazard potentials; GIS modeling especially allows for the fusion of remote sensing and elevation data for spatial (3D) analyses. To ensure high synergy, WPs (1) and (2) will be closely related to the ongoing SNF project "The Swiss Glacier Inventory 2000" (SWI 2000) (no. 21-54073.98) and the international project "Global Land Ice Monitoring from Space" (GLIMS). WP (3): By applying the methods from WPs (1) and (2), an initial attempt will be undertaken to implement an area-wide model for integrating glacier hazard potentials of extensive regions in the Swiss Alps following a downscaling strategy with varying resolution and accuracy levels, both with respect to data and to models. As hazard management in Switzerland is the domain of local and regional authorities, the proposed project does not aim at preparing detailed local hazard maps (Gefahrenkarten), but rather will provide new remote sensing and modeling techniques for decision support. It should demonstrate the usefulness of these techniques for overview mapping (Gefahrenhinweiskarten) as a basis for decision-making and for scenario simulations in connection with climate change effects. The efforts made in this project will contribute to handle economically complex mathematical and physical models and represent a decision basis for the specific need of further detailed case studies. A further outcome will be a documentation of historical glacier catastrophes in the Swiss Alps, which will - among others - be used for model calibration and verification. [Summary provided by Christian Huggel, University of Zurich.]

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -90 -180 90 180

    SCIOPS Short Name: UNIZH_AGREG Version ID: Not provided Unique ID: C1214614963-SCIOPS

  • Atlas of the Shallow-Water Benthic Habitats of the Northwestern Hawaiian Islands

    https://cmr.earthdata.nasa.gov/search/concepts/C1214422207-SCIOPS.xml
    Description:

    Released by the Remote Sensing Team (part of the National Oceanic and Atmospheric Administration), these detailed maps released in February 2003 focus on the Northwest Hawaiian Islands. The Remote Sensing Team led development of the first benthic habitat maps made for the Northwest Hawaiian Islands. The NWHI chain extends across 2200 km of open ocean, and the total shallow water area of the ten atolls encompasses over 8,000 square km. Due to the remoteness and large spatial extent of these reefs, high-resolution satellite imagery was the primary source of data for this effort. Field data collected during a NOS cruise to NWHI in Aug-Sep 2001 and provided by the NMFS, Honolulu Lab were also essential to map production. The satellite data used was IKONOS multispectral (blue/green/red/near-infrared bands) and panchromatic imagery from Space Imaging, collected between 2000 and 2002. Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery was also obtained for all ten atolls as well as for most of the bank areas. Map products for NWHI include georeferenced true color images derived from IKONOS satellite data, estimated bathymetry (in meters) derived from the imagery, benthic habitat cover, and detailed benthic habitat classes. The process of map development is described in detail in the NWHI_map_development.pdf "http://ccma.nos.noaa.gov/ecosystems/coralreef/nwhi/pdf/NWHI_map_development.pdf" and a description of the classification scheme and classes can be found in the NWHI_class_scheme.pdf "http://ccma.nos.noaa.gov/ecosystems/coralreef/nwhi/pdf/NWHI_class_scheme.pdf". A PDF file with larger versions of the colorbars for the depth scales and the legends for habitat cover and detailed class is also available in the NWHI_map_legend.pdf "http://ccma.nos.noaa.gov/ecosystems/coralreef/nwhi/pdf/NWHI_map_legend.pdf".

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -80 100 70 -60

    SCIOPS Short Name: ocean_atlas Version ID: Not provided Unique ID: C1214422207-SCIOPS

  • Australian Antarctic Territory Coastline 2003

    https://cmr.earthdata.nasa.gov/search/concepts/C1214305672-AU_AADC.xml
    Description:

    The 'Australian Antarctic Territory coastline 2003' dataset is a digital vector representation of the coastline of Antarctica, between 45 to 160 degrees east, based on both the edge of permanent ice and grounding line, derived by means of remote sensing interpretation. A 'proof of concept' methodology over a test area was carried out to compare a number of complementary remote sensing techniques, including interferometry and airborne ice radar profiling, to confirm validation of grounding line as mapped from Landsat 7 ETM+ imagery. This methodology concept then served to validate grounding line locations elsewhere along the coast of the AAT. The National Mapping Division of Geoscience Australia and the Australian Antarctic Division developed this dataset as a joint project. Where available, Australian Antarctic Division supplied large-scale vector data of various areas around the AAT, which were included as part of the main coastline dataset. These included: * Holme Bay 1:25,000 GIS dataset * Larsemann Hills - Mapping from aerial photography captured February 1998 * Rauer Group 1:50000 Topographic GIS Dataset * Vestfold Hills Topographic GIS Dataset * Windmill Islands 1:50000 Topographic GIS Dataset * Cape Denison and McKellar Islands GIS dataset from Ikonos satellite imagery Refer to the metadata record for each of these datasets for further information. The coastline dataset is comprised of three parts: one polygon coverage consisting of ice features, and another one consisting of coastal features. A third coverage consists of only island point features (islands too small to be shown as polygons). This dataset supersedes the Australian Antarctic Territory Coastline 2001 dataset which is also part of SCAR's Antarctic Digital Database (ADD) version 4 and version 5. It replaces data digitised from Landsat 4 and 5, with that from Landsat 7 ETM+, because of its more reliable positional accuracy and more recent acquisition. The Australian Antarctic Territory Coastline 2001 dataset and metadata record have been archived. Please contact the Australian Antarctic Data Centre if you would like a copy of this data and metadata.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -82.679 42.723 -64.929 169.333

    AU_AADC Short Name: AAT_Coastline_2003 Version ID: 1 Unique ID: C1214305672-AU_AADC

  • Big Cypress-Pine Island Satellite Image Map

    https://cmr.earthdata.nasa.gov/search/concepts/C1214603622-SCIOPS.xml
    Description:

    ABSTRACT: The map is a composite image of spectral bands 3 (630-690 nanometers, red), 4 (775-900 nanometers, near-infrared), and 5 (1,550-1750 nanometers, middle-infrared) and the new panchromatic band (520-900, green to near-infrared) acquired by the Landsat 7 enhanced thematic mapper (ETM) sensor on January 27, 2000.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 25.78 -82.27 26.7 -81.13

    SCIOPS Short Name: USGS_SOFIA_BigCypress_PineIsland Version ID: SatMap Unique ID: C1214603622-SCIOPS

  • BigFoot Land Cover Surfaces for North and South American Sites, 2000-2003

    https://cmr.earthdata.nasa.gov/search/concepts/C179003725-ORNL_DAAC.xml
    Description:

    The BigFoot project gathered data for nine EOS Land Validation Sites located from Alaska to Brazil from 2000 to 2003. Each site is representative of one or two distinct biomes, including the Arctic tundra; boreal evergreen needleleaf forest; temperate cropland, grassland, evergreen needleleaf forest, and deciduous broadleaf forest; desert grassland and shrubland; and tropical evergreen broadleaf forest. These surfaces were produced from Landsat ETM+ imagery to explicitly characterize the land cover at the BigFoot Sites to provide validation of the MODIS land cover product. BigFoot was funded by NASA's Terrestrial Ecology Program.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -2.86 -156.61 71.27 -54.96

    ORNL_DAAC Short Name: bigfoot_landcove_748 Version ID: 1 Unique ID: C179003725-ORNL_DAAC

  • BigFoot Leaf Area Index Surfaces for North and South American Sites, 2000-2003

    https://cmr.earthdata.nasa.gov/search/concepts/C179003573-ORNL_DAAC.xml
    Description:

    The BigFoot project gathered leaf area index (LAI) data for nine EOS Land Validation Sites located from Alaska to Brazil from 2000 to 2003. Each site is representative of one or two distinct biomes, including the Arctic tundra; boreal evergreen needleleaf forest; temperate cropland, grassland, evergreen needleleaf forest, and deciduous broadleaf forest; desert grassland and shrubland; and tropical evergreen broadleaf forest. LAI was measured at plots within each site for at least two years using standard direct and optical methods at each site. BigFoot was funded by NASA's Terrestrial Ecology Program.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -2.86 -156.61 71.27 -54.96

    ORNL_DAAC Short Name: bigfoot_lai_747 Version ID: 1 Unique ID: C179003573-ORNL_DAAC