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Using the NASA EOSDIS Common Metadata Repository

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  • ABoVE: NDVI Trends across Alaska and Canada from Landsat, 1984-2012

    https://cmr.earthdata.nasa.gov/search/concepts/C2162131333-ORNL_CLOUD.xml
    Description:

    This dataset provides the summer NDVI trend and trend significance for the period 1984-2012 over Alaska and Canada. The NDVI were calculated per-pixel from all available peak-summer 30-m Landsat 5 and 7 surface reflectance data for the period. NDVI time series were assembled for each 30-m land location (i.e., non-water, non-snow), from observations that were unaffected by clouds as indicated by data-quality masks and following additional processing to remove anomalous NDVI values. A simple linear regression via ordinary least squares was applied to the per-pixel NDVI time series. The slope of the regression was taken as the annual NDVI trend (unit NDVI change per year) and is reported in the "trend" data files. A Student's t-test was used to assess the significance of the trend and the per-pixel significance is reported in the "trend_sig" data files. A significant positive slope indicates a greening trend, and a significant negative slope indicates a browning trend.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 41.61 -169.97 80.51 -50.17

    ORNL_CLOUD Short Name: Vegetation_greenness_trend_1576 Version ID: 1 Unique ID: C2162131333-ORNL_CLOUD

  • ABoVE: River Ice Breakup and Freeze-up Stages, Yukon River Basin, Alaska, 1972-2016

    https://cmr.earthdata.nasa.gov/search/concepts/C2143403517-ORNL_CLOUD.xml
    Description:

    This dataset provides estimates of river ice breakup and freeze-up stages along selected reaches of the Yukon and Tanana Rivers in the Yukon River Basin in interior Alaska from 1972-2016. Time series of Landsat satellite images were visually interpreted to identify the day of year and characteristics of the different stages of river ice seasonality. The stages of breakup or freeze-up were distinguished from one another based on the spatial extent and patterns of open water and ice cover. Images were displayed as false color composites, with the shortwave infrared (SWIR), near infrared (NIR), and green bands represented by red, green, and blue.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 62.9 -160.07 66.36 -142.99

    ORNL_CLOUD Short Name: River_Ice_Breakup_Freezeup_1697 Version ID: 1 Unique ID: C2143403517-ORNL_CLOUD

  • ABoVE: Riverbank Erosion and Vegetation Changes, Yukon River Basin, Alaska, 1984-2017

    https://cmr.earthdata.nasa.gov/search/concepts/C2162145546-ORNL_CLOUD.xml
    Description:

    This dataset provides a time series of riverbank erosion and vegetation colonization along reaches of the Yukon River (3 study areas), Tanana and Nenana Rivers (1 area), and Chandalar River (1 area) in interior Alaska over the period 1984-2017. The change data were derived from selected 30-m images from Landsat TM, Landsat ETM+, and Landsat Operational Land Imager (OLI) surface reflectance products. Image classification used the Normalized Differenced Vegetation Index (NDVI) with an NDVI threshold of 0.2 to differentiate vegetated from non-vegetated pixels. Images were assigned to one of seven or eight multiyear intervals, within the 1984-2017 overall range, for each study area. Time intervals vary by study site. Change detection identified shifts from one time interval to the next: changes from vegetated to non-vegetated classes were considered riverbank erosion and changes from non-vegetated to vegetated classes were considered vegetation colonization.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 61.91 -161.46 68.15 -143.3

    ORNL_CLOUD Short Name: Erosion_Vegetation_Yukon_1616 Version ID: 1 Unique ID: C2162145546-ORNL_CLOUD

  • ABoVE: Surface Water Extent, Boreal and Tundra Regions, North America, 1991-2011

    https://cmr.earthdata.nasa.gov/search/concepts/C2162118169-ORNL_CLOUD.xml
    Description:

    This data set provides the location and extent of surface water (open water not including vegetated wetlands) for the entire Boreal and Tundra regions of North America for three epochs, centered on 1991, 2001, and 2011. Each of the products were generated with at least three years of ice-free Landsat imagery. The data are at 30-m resolution and were derived from time series of Landsat 4 and 5 Thematic Mapper (TM) data and Landsat 7 Enhanced Thematic Mapper (ETM+) covering all of Alaska and all provinces of Canada. The overall goal was to generate a map of the nominal extent of water for a given epoch, where nominal is neither the maximum nor the minimum but rather a representative extent for that time period.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 41.7 -177.48 82.37 -53.94

    ORNL_CLOUD Short Name: Decadal_Water_Maps_1324 Version ID: 1.1 Unique ID: C2162118169-ORNL_CLOUD

  • ABoVE: Tundra Plant Functional Type Continuous-Cover, North Slope, Alaska, 2010-2015

    https://cmr.earthdata.nasa.gov/search/concepts/C2143401689-ORNL_CLOUD.xml
    Description:

    This dataset provides predicted continuous-field cover for tundra plant functional types (PFTs), across ~125,000 km2 of Alaska's North Slope at 30-m resolution. The data cover the period 2010-07-01 to 2015-08-31. The data were derived using a random forest data-mining algorithm, predictors derived from Landsat satellite observations (surface reflectance composites for ~15-day periods from May-August), and field vegetation cover and site characterization data spanning bioclimatic and geomorphic gradients. The field vegetation cover was stratified by nine PFTs, plus open water, bare ground and litter, and using the cover metrics total cover (areal cover including the understory) and top cover (uppermost canopy or ground cover), resulting in a total of 19 field cover types. The field data and predictor values at the field sites are also included.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 65.59 -167.48 73.8 -143.98

    ORNL_CLOUD Short Name: AK_Tundra_PFT_FractionalCover_1830 Version ID: 1 Unique ID: C2143401689-ORNL_CLOUD

  • 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