OpenSearch

Using the NASA EOSDIS Common Metadata Repository

Collection Search

  • Casey Station Footprint GIS Layers, 2002-2018

    https://cmr.earthdata.nasa.gov/search/concepts/C2102891782-AU_AADC.xml
    Description:

    This dataset contains GIS spatial layers of the medium and heavy disturbance footprint surrounding Casey Research Station at the years 2002, 2008, 2015 and 2018. The footprint mapping used a consistent methodology for digitisation for the years 2002, 2015, and 2018, whereas the year 2008 included ground-truther field measurements. Some variation in the footprint is due to snow cover hiding areas of disturbance. The sources and date of the data used is as follows: • 2018 Casey Heavy Disturbance – digitised by S. Brooks from Worldview-3 imagery, captured 27/1/2018. • 2018 Casey Medium Disturbance – digitised by S. Brooks from Worldview-3 imagery, captured 27/1/2018. • 2015 Casey Heavy Disturbance – digitised by S. Brooks from AAS 5024 UAV-imagery. • 2015 Casey Medium Disturbance – digitised by S. Brooks from AAS 5024 UAV-imagery. • 2008 Casey Heavy Disturbance – produced from data associated with: Brooks, S.T. 2014. Developing a Standardised Approach to Measuring the Environmental Footprint of Antarctic Research Stations. Journal of Environmental Assessment Policy and Management, 16(04), 1450037. • 2008 Casey Medium Disturbance – produced from aerial imagery and field data opportunistically collected in association with: Brooks, S.T. 2014. Developing a Standardised Approach to Measuring the Environmental Footprint of Antarctic Research Stations. Journal of Environmental Assessment Policy and Management, 16(04), 1450037. • 2002 Casey Heavy Disturbance – digitised by S. Brooks from 2002 AADC-held Orthophoto • 2002 Casey Medium Disturbance – digitised by S. Brooks from 2002 AADC-held Orthophoto

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -66.36835 110.39612 -66.20488 110.7312

    AU_AADC Short Name: AAS_4565_2020_CASEY Version ID: 1 Unique ID: C2102891782-AU_AADC

  • High Mountain Asia 8-meter DEM Mosaics Derived from Optical Imagery V001

    https://cmr.earthdata.nasa.gov/search/concepts/C1431539277-NSIDC_ECS.xml
    Description:

    This data set contains 8-meter Digital Elevation Model (DEM) mosaics of high mountain Asia glacier and snow regions generated from very-high-resolution (VHR) commercial satellite imagery.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 26 67 46 103

    NSIDC_ECS Short Name: HMA_DEM8m_MOS Version ID: 1 Unique ID: C1431539277-NSIDC_ECS

  • High Mountain Asia 8-meter DEMs Derived from Along-track Optical Imagery V001

    https://cmr.earthdata.nasa.gov/search/concepts/C1442092309-NSIDC_ECS.xml
    Description:

    This data set contains 8-meter Digital Elevation Models (DEMs) of high mountain Asia glacier and snow regions generated from very-high-resolution commercial stereoscopic satellite imagery.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 26 67 46 103

    NSIDC_ECS Short Name: HMA_DEM8m_AT Version ID: 1 Unique ID: C1442092309-NSIDC_ECS

  • High Mountain Asia 8-meter DEMs Derived from Cross-track Optical Imagery V001

    https://cmr.earthdata.nasa.gov/search/concepts/C1432250096-NSIDC_ECS.xml
    Description:

    This data set contains 8-meter Digital Elevation Model (DEM) mosaics of high mountain Asia glacier and snow regions generated from from very-high-resolution commercial stereo satellite imagery.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 26 67 46 103

    NSIDC_ECS Short Name: HMA_DEM8m_CT Version ID: 1 Unique ID: C1432250096-NSIDC_ECS

  • Land Cover Classification, Snow Cover, and Fractional Snow-Covered Area Maps from Maxar WorldView Satellite Images V001

    https://cmr.earthdata.nasa.gov/search/concepts/C2695676729-NSIDC_ECS.xml
    Description:

    This data set includes: (1) fine-scale snow and land cover maps from two mountainous study sites in the Western U.S., produced using machine-learning models trained to extract land cover data from WorldView-2 and WorldView-3 stereo panchromatic and multispectral images; (2) binary snow maps derived from the land cover maps; and (3) 30 m and 465 m fractional snow-covered area (fSCA) maps, produced via downsampling of the binary snow maps. The land cover classification maps feature between three and six classes common to mountainous regions and integral for accurate stereo snow depth mapping: illuminated snow, shaded snow, vegetation, exposed surfaces, surface water, and clouds. Also included are Landsat and MODSCAG fSCA map products. The source imagery for these data are the Maxar WorldView-2 and Maxar WorldView-3 Level-1B 8-band multispectral images, orthorectified and converted to top-of-atmosphere reflectance. These Level-1B images are available under the NGA NextView/EnhancedView license.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 48.269722 -121.179528 48.441717 -120.932614

    NSIDC_ECS Short Name: WV_LCC_SC_FSCA Version ID: 1 Unique ID: C2695676729-NSIDC_ECS

  • MEaSUREs Greenland Ice Mapping Project (GrIMP) Digital Elevation Model from GeoEye and WorldView Imagery V002

    https://cmr.earthdata.nasa.gov/search/concepts/C2295286903-NSIDC_ECS.xml
    Description:

    This data set consists of an enhanced resolution digital elevation model (DEM) for the Greenland Ice Sheet, derived from sub-meter resolution, panchromatic stereoscopic imagery collected by the GeoEye-1, WorldView-1, -2, and -3 satellites operated by Maxar Technologies. The DEM was created from in-track image pairs (i.e., both images collected minutes apart along the same orbital pass) and cross-track images (i.e., from different orbits) within the in-track imaging geometry and maximum time separation criteria. The DEM is registered to ATLAS/ICESat-2 L3A Land Ice Height, Version 5 (ATL06, V5) data collected in the summers of 2019 and 2020. See <a href="http://nsidc.org/data/measures/gimp">Greenland Ice Mapping Project (GrIMP)</a> for related data

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 60 -75 83 -14

    NSIDC_ECS Short Name: NSIDC-0715 Version ID: 2 Unique ID: C2295286903-NSIDC_ECS

  • Orthorectification, Mosaicking and Pan-sharpening of WV3 imagery over Vestfold Hills, Dec 2017

    https://cmr.earthdata.nasa.gov/search/concepts/C1458563850-AU_AADC.xml
    Description:

    Orthorectification, Mosaicking and Pan-sharpening of WorldView 3 imagery over Vestfold Hills. 3 swathes were acquired on 21st Dec 2017 covering 881sq km. The processing of this image was done by a contractor. See the attached document for details on the processing performed.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: -68.683333 77.752778 -68.34 78.629167

    AU_AADC Short Name: WV3_vestfold_21Feb2017 Version ID: 1 Unique ID: C1458563850-AU_AADC

  • ramp Building Footprint Dataset - Barishal, Bangladesh

    https://cmr.earthdata.nasa.gov/search/concepts/C2781412722-MLHUB.xml
    Description:

    This chipped training dataset is over Barishal and includes high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 pixel tile/label pairs. This dataset is a ramp Tier 1 dataset, meaning it has been thoroughly reviewed and improved. This dataset was used in developing the ramp baseline model and contains 3,024 tiles and 41,248 individual buildings. The satellite imagery resolution is 40 cm and was sourced from Maxar ODP (105001001597B000). Dataset keywords: Urban, Peri-urban, River

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 22.6475678 90.3039757 22.7800298 90.3893401

    MLHUB Short Name: ramp Building Footprint Dataset - Barishal, Bangladesh Version ID: 1 Unique ID: C2781412722-MLHUB

  • ramp Building Footprint Dataset - Bentiu, South Sudan

    https://cmr.earthdata.nasa.gov/search/concepts/C2781412757-MLHUB.xml
    Description:

    This chipped training dataset is over Bentiu and includes high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 pixel tile/label pairs. This dataset is a ramp Tier 1 dataset, meaning it has been thoroughly reviewed and improved. This dataset was used in developing the ramp baseline model and contains 1,789 tiles and 22,396 individual buildings. The satellite imagery resolution is 35 cm and was sourced from Maxar ODP (104001004DAECE00). Dataset keywords: Refugee Settlement, Rural.

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 9.2285638 29.7779526 9.3421338 29.8314928

    MLHUB Short Name: ramp Building Footprint Dataset - Bentiu, South Sudan Version ID: 1 Unique ID: C2781412757-MLHUB

  • ramp Building Footprint Dataset - Chittagong, Bangladesh

    https://cmr.earthdata.nasa.gov/search/concepts/C2781412778-MLHUB.xml
    Description:

    This chipped training dataset is over Chittagong and parts of the Kutupalong Refugee Camp and includes high-resolution imagery (.tif format) and corresponding building footprint vector labels (.geojson format) in 256 x 256 pixel tile/label pairs. This dataset is a ramp Tier 1 dataset, meaning it has been thoroughly reviewed and improved. This dataset was used in the development and testing of a localized ramp model and contains 5,229 tiles and 38,096 individual buildings. The satellite imagery resolution is 40 cm and was sourced from Maxar ODP (105001001AC98900). Dataset keywords: Agricultural, Peri-urban, Refugee Camp, Rural

    Links: Temporal Extent: Spatial Extent:
    Minimum Bounding Rectangle: 21.0153288 92.1153814 21.4707151 92.2418205

    MLHUB Short Name: ramp Building Footprint Dataset - Chittagong, Bangladesh Version ID: 1 Unique ID: C2781412778-MLHUB