ArcticDEM Mosaic V4.1

UMN/PGC/ArcticDEM/V4/2m_mosaic
Dataset Availability
2012-06-03T00:00:00Z–2020-09-03T23:59:59Z
Dataset Provider
Earth Engine Snippet
ee.Image("UMN/PGC/ArcticDEM/V4/2m_mosaic")
Tags
arctic dem elevation-topography geophysical pgc umn

Description

ArcticDEM is a National Geospatial-Intelligence Agency (NGA) and National Science Foundation (NSF) public-private initiative to automatically produce a high-resolution, high-quality digital surface model (DSM) of the Arctic using optical stereo imagery, high-performance computing, and open source photogrammetry software. It includes vegetation, tree canopy, buildings, and other man-made surface features. The 2m asset is a collection of strips rather than a single mosaic due to projection differences between strips.

Mosaicked DEM files are compiled from the best quality strip DEM files which have been blended and feathered to reduce void areas and edge-matching artifacts. Filtered IceSAT altimetry data has been applied to the raster files to improve absolute accuracy.

These version (V4.1) mosaics include additional raster bands: 'count', 'mad','mindate', and 'maxdate' to provide information on data provenance and uncertainty.

Bands

Pixel Size
2 meters

Bands

Name Units Min Max Description
elevation m -416.45* 5971.24*

Elevation
count

Number of source DEMs used to calculate the elevation value at that pixel.
mad m

Median absolute deviation of the stack of source datasets from the median elevation value.
mindate

Earliest date of the source DEMs used to build the mosaic, as the number of days since January 1, 2000.
maxdate

Latest date of the source DEMs used to build the mosaic, as the number of days since January 1, 2000.
datamask

Data mask indicates whether the elevation was 0 or 1. where 0 indicates , Filled/merged with another dataset or masked out as NoData in quality control steps. 1 indicates output by SETSM, the Ohio State University’s Surface Extraction with TIN-based Search-space Minimization software package.
* estimated min or max value

Terms of Use

Terms of Use

National Science Foundation (PGC's primary funding source) policy requires researchers to acknowledge NSF support in all publications, web pages, and media interviews.

By using PGC data in Earth Engine, users agree to cite PGC and its sponsorship by the NSF. The original source of any third-party data supplied by PGC must also be properly attributed.

For more information see the PGC's Acknowledgement Policy.

Citations

Citations:

  • DEM(s) created by the Polar Geospatial Center from DigitalGlobe, Inc. imagery. Porter, Claire; Morin, Paul; Howat, Ian; Noh, Myoung-Jon; Bates, Brian; Peterman, Kenneth; Keesey, Scott; Schlenk, Matthew; Gardiner, Judith; Tomko, Karen; Willis, Michael; Kelleher, Cole; Cloutier, Michael; Husby, Eric; Foga, Steven; Nakamura, Hitomi; Platson, Melisa; Wethington, Michael, Jr.; Williamson, Cathleen; Bauer, Gregory; Enos, Jeremy; Arnold, Galen; Kramer, William; Becker, Peter; Doshi, Abhijit; D'Souza, Cristelle; Cummens, Pat; Laurier, Fabien; Bojesen, Mikkel, 2018, ArcticDEM, Harvard Dataverse, V1, [Date Accessed].

DOIs

Explore with Earth Engine

Code Editor (JavaScript)

var dataset = ee.Image('UMN/PGC/ArcticDEM/V4/2m_mosaic');

var elevationVis = {
  min: -50.0,
  max: 1000.0,
  palette: ['0d13d8', '60e1ff', 'ffffff'],
  bands: ['elevation'],
};

var countVis = {
  min: 0,
  max: 10,
  palette: [
    'black',
    'blue',
    'purple',
    'cyan',
    'green',
    'yellow',
    'red',
  ],
  bands: ['count'],
};

var madVis = {
  min: 0,
  max: 50,
  palette: [
    '006633',
    'E69800',
    'D4E157',
    'FFF59D',
  ],
  bands: ['mad'],
};

var datamaskVis = {
  min: 0,
  max: 1,
  palette: [
    'black',
    'white',
  ],
  bands: ['datamask'],
};

Map.setCenter(-63.402, 66.368, 7);

Map.addLayer(dataset, elevationVis, 'Elevation', true);
Map.addLayer(dataset, countVis, 'Data Count', false);
Map.addLayer(dataset, madVis, 'MAD', false);
Map.addLayer(dataset, datamaskVis, 'Data Mask', false);
Open in Code Editor
ArcticDEM is a National Geospatial-Intelligence Agency (NGA) and National Science Foundation (NSF) public-private initiative to automatically produce a high-resolution, high-quality digital surface model (DSM) of the Arctic using optical stereo imagery, high-performance computing, and open source photogrammetry software. It includes vegetation, tree canopy, buildings, and other man-made surface features. The …
UMN/PGC/ArcticDEM/V4/2m_mosaic, arctic,dem,elevation-topography,geophysical,pgc,umn
2012-06-03T00:00:00Z/2020-09-03T23:59:59Z
50 -180 90 180
Google Earth Engine