OpenSearch

Using the NASA EOSDIS Common Metadata Repository

Collection Search

  • A Fusion Dataset for Crop Type Classification in Germany

    https://cmr.earthdata.nasa.gov/search/concepts/C2781412484-MLHUB.xml
    Description:

    This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Brandenburg, Germany. There are nine crop types in this dataset from years 2018 and 2019: Wheat, Rye, Barley, Oats, Corn, Oil Seeds, Root Crops, Meadows, Forage Crops. The 2018 labels from one of the tiles are provided for training, and the 2019 labels from a neighboring tile will be used for scoring in the competition. Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection. The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 52.4179888 13.6339485 52.8494418 14.3529903

    MLHUB Short Name: A Fusion Dataset for Crop Type Classification in Germany Version ID: 1 Unique ID: C2781412484-MLHUB

  • A Fusion Dataset for Crop Type Classification in Western Cape, South Africa

    https://cmr.earthdata.nasa.gov/search/concepts/C2781412697-MLHUB.xml
    Description:

    This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Western Cape, South Africa. There are five crop types from the year 2017: Wheat, Barely, Canola, Lucerne/Medics, Small grain grazing. The AOI is split to three tiles. Two tiles are provided as training labels, and one tile will be used for scoring in the competition. Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection. The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license. The Western Cape Department of Agriculture (WCDoA) vector data are supplied via Radiant Earth Foundation with limited distribution rights. Data supplied by the WCDoA may not be distributed further or used for commercial purposes. The vector data supplied are intended strictly for use within the scope of this remote sensing competition - for the purpose of academic research to our mutual benefit. The data is intended for research purposes only and the WCDoA cannot be held responsible for any errors or omissions which may occur in the data.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -34.413256 20.5212157 -33.9796334 21.043415

    MLHUB Short Name: A Fusion Dataset for Crop Type Classification in Western Cape, South Africa Version ID: 1 Unique ID: C2781412697-MLHUB

  • ABoVE: Wetland Inundation Coverage at Yukon Flats, AK and PA Delta, Canada, 2017-2019

    https://cmr.earthdata.nasa.gov/search/concepts/C2482179223-ORNL_CLOUD.xml
    Description:

    This dataset provides time series of wetland inundation coverage maps and corresponding inundation frequency maps at ~10-meter resolution estimated every 12 days during the free-water period (May to October) for the years 2017-2019 over the Yukon Flats (YK) portion of the Yukon River, Alaska, USA, and the Peace-Athabasca Delta (PAD), Alberta, Canada. Wetland inundation coverage was determined by a two-step modified decision-tree classification approach that first used Sentinel-1 C-band SAR to identify likely inundated areas across a study site and was followed by a decision-tree classification step with C-band SAR backscatter statistics thresholds to distinguish among different inundation components. The result of this process was five classes for each inundation map, namely Open Water (OW), Floating Plants (FP), Emergent Plants (EP), Flooded Vegetation (FV), and Dry Land (DRY). After all the individual (every 12 days) inundation coverage maps were derived for a study site, they were generalized to two-class maps which maintained only inundation status. These generalized maps were then stacked and summarized to produce the inundation frequency map for the site. In these maps, higher values signify more frequently inundated areas, with the maximum value representing permanently inundated pixels. The Sentinel-1 inundation mapping capability demonstrated here provided frequent, broad-scale mapping of different wetland inundation components. Integration of such products with process-based methane (CH4) models would improve simulation of CH4 emissions from wetlands.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 58.25 -146.43 66.81 -110.92

    ORNL_CLOUD Short Name: InundationMap_YkFlats_PeaceAth_1901 Version ID: 1 Unique ID: C2482179223-ORNL_CLOUD

  • ARIA Sentinel-1 Geocoded Unwrapped Interferograms

    https://cmr.earthdata.nasa.gov/search/concepts/C2859376221-ASF.xml
    Description:

    Level-2 interferometric products generated by the Jet Propulsion Lab (JPL) ARIA project. The creation, discovery, and distribution of these products support InSAR science around tectonically active regions, volcanoes, or areas of subsidence/uplift.

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

    ASF Short Name: ARIA_S1_GUNW Version ID: 1 Unique ID: C2859376221-ASF

  • Automated Greenland Glacier Termini Position Time Series, Version 1

    https://cmr.earthdata.nasa.gov/search/concepts/C2849438379-NSIDCV0.xml
    Description:

    This data set contains shapefiles of termini traces from 294 Greenland glaciers, derived using a deep learning algorithm (AutoTerm) applied to satellite imagery. The model functions as a pipeline, imputing publicly availably satellite imagery from Google Earth Engine (GEE) and outputting shapefiles of glacial termini positions for each image. Also available are supplementary data, including temporal coverage of termini traces, time series data of termini variations, and updated land, ocean, and ice masks derived from the <a href="https://nsidc.org/data/nsidc-0714/versions/1">Greenland Ice Sheet Mapping Project (GrIMP) ice masks</a>.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 57 -75 85 -8

    NSIDCV0 Short Name: NSIDC-0788 Version ID: 1 Unique ID: C2849438379-NSIDCV0

  • Cloud to Street - Microsoft flood dataset

    https://cmr.earthdata.nasa.gov/search/concepts/C2781412798-MLHUB.xml
    Description:

    The C2S-MS Floods Dataset is a dataset of global flood events with labeled Sentinel-1 & Sentinel-2 pairs. There are 900 sets (1800 total) of near-coincident Sentinel-1 and Sentinel-2 chips (512 x 512 pixels) from 18 global flood events. Each chip contains a water label for both Sentinel-1 and Sentinel-2, as well as a cloud/cloud shadow mask for Sentinel-2. The dataset was constructed by Cloud to Street in collaboration with and funded by the Microsoft Planetary Computer team.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -25.250962 -96.631888 48.745167 141.118143

    MLHUB Short Name: Cloud to Street - Microsoft flood dataset Version ID: 1 Unique ID: C2781412798-MLHUB

  • ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2017 and 2018, v2

    https://cmr.earthdata.nasa.gov/search/concepts/C2548142753-FEDEO.xml
    Description:

    This dataset comprises estimates of forest above-ground biomass for the years 2010, 2017 and 2018. They are derived from a combination of Earth observation data, depending on the year, from the Copernicus Sentinel-1 mission, Envisat’s ASAR instrument and JAXA’s Advanced Land Observing Satellite (ALOS-1 and ALOS-2), along with additional information from Earth observation sources. The data has been produced as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme by the Biomass CCI team. The data products consist of two (2) global layers that include estimates of:1) above ground biomass (AGB, unit: tons/ha i.e., Mg/ha) (raster dataset). This is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots2) per-pixel estimates of above-ground biomass uncertainty expressed as the standard deviation in Mg/ha (raster dataset)This release of the data is version 2, with data provided in both netcdf and geotiff format. The quantification of AGB changes by taking the difference of two maps is strongly discouraged due to local biases and uncertainties. Version 3 maps will ensure a more realistic representation of AGB changes.

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

    FEDEO Short Name: 84403d09cef3485883158f4df2989b0c Version ID: NA Unique ID: C2548142753-FEDEO

  • ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Calving Front Locations, v3.0

    https://cmr.earthdata.nasa.gov/search/concepts/C2548142650-FEDEO.xml
    Description:

    The data set provides calving front locations of 28 major outlet glaciers of the Greenland Ice Sheet, produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. The Calving Front Location (CFL) of outlet glaciers from ice sheets is a basic parameter for ice dynamic modelling, for computing the mass fluxes at the calving gate, and for mapping glacier area change. The calving front location has been derived by manual delineation using SAR (Synthetic Aperture Radar) data from the ERS-1/2, Envisat and Sentinel-1 satellites and satellite imagery from LANDSAT 5,7,8. The digitized calving fronts are stored in ESRI vector shape-file format and include metadata information on the sensor and processing steps in the corresponding attribute table.The product was generated by ENVEO (Environmental Earth Observation Information Technology GmbH)

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 60 -80 90 -10

    FEDEO Short Name: 8889dfe3de45406e815bce13ae8a0c92 Version ID: NA Unique ID: C2548142650-FEDEO

  • ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map, Winter 2016-2017, v1.0

    https://cmr.earthdata.nasa.gov/search/concepts/C2548142785-FEDEO.xml
    Description:

    This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2016-2017, derived from Sentinel-1 SAR data acquired from 23/12/2016 to 27/02/2017, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. In total approximately 1800 S-1A & S-1B scenes are used to derive the surface velocity applying feature tracking techniques. The ice velocity map is provided at 500m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity is provided in true meters per day, towards EASTING(vx) and NORTHING(vy) direction of the grid, and the vertical displacement (vz), derived from a digital elevation model is also provided. The product was generated by ENVEO (Earth Observation Information Technology GmbH).

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 60 -80 90 -10

    FEDEO Short Name: 24dc5d5429434ccdb349db04a1a3233d Version ID: NA Unique ID: C2548142785-FEDEO

  • ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map, Winter 2017-2018, v1.0

    https://cmr.earthdata.nasa.gov/search/concepts/C2548143413-FEDEO.xml
    Description:

    This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2017-2018, derived from Sentinel-1 SAR data acquired from 28/12/2017 to 28/02/2018, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. In total approximately 1900 S-1A & S-1B scenes are used to derive the surface velocity applying feature tracking techniques. The ice velocity map is provided at 500m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity is provided in true meters per day, towards EASTING(vx) and NORTHING(vy) direction of the grid, and the vertical displacement (vz),derived from a digital elevation model, is also provided. The product was generated by ENVEO (Earth Observation Information Technology GmbH).

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 60 -80 90 -10

    FEDEO Short Name: eaed9fba86c44e9c854dfbdec9d16b99 Version ID: NA Unique ID: C2548143413-FEDEO