Dataset Open Access

Chamoli Disaster Pre-event 2-m DEM Composite: September 2015

Bhushan, Shashank; Shean, David


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  <dc:creator>Bhushan, Shashank</dc:creator>
  <dc:creator>Shean, David</dc:creator>
  <dc:date>2021-02-21</dc:date>
  <dc:description>These “fine-quality” 2-m DEM composites and auxiliary products were created using 38 cross-track stereo DEMs generated from 11 overlapping monoscopic Maxar/DigitalGlobe WorldView-1 and WorldView-2 images acquired between August 28, 2015 and October 5, 2015. The original Level-1B WorldView-1/2 (© 2015 Maxar/DigitalGlobe, Inc.) are available under the NGA NextView license.

All unique stereo combinations between these input images were processed using the NASA Ames Stereo Pipeline v2.6.2_post (Beyer et. al, 2018; build d7eb7c8) and a modified version of the methodology presented in Shean et al. (2016; 2020). Input images were orthorectified at native GSD using the 30-m Copernicus DEM (converted to ellipsoidal heights) and cropped to the region of interest for the February 7, 2021 Chamoli event. See http://doi.org/10.5281/zenodo.4533679 for additional details on the "fine-quality" processing.

Each output DEM (height above the WGS84 ellipsoid) was posted at 2.0 m with UTM 44N projection (EPSG:32644). Each output DEM was then co-registered to a filtered/masked version of the HMA 8-m DEM Mosaic v2 (http://doi.org/10.5281/zenodo.4532391) using the demcoreg/dem_align.py utility (http://doi.org/10.5281/zenodo.3243481). A final filter was applied to mask any DEM pixels with elevation values that differed by more than +/- 80 m from the HMA 8-m DEM Mosaic v2.

Several DEM composites were produced from the co-registered, filtered DEMs using the ASP dem_mosaic utility (https://stereopipeline.readthedocs.io/en/latest/tools/dem_mosaic.html).  The first composite is the per-pixel weighted mean of all valid elevation values (*wmean.tif). This approach uses a weighting scheme that favors spatially continuous coverage (as opposed to small clusters of valid pixel separated by nodata values), resulting in a more seamless, blended composite. The second composite is the per-pixel median of all valid elevation values (*med.tif).

Additional composites were created for the per-pixel DEM count (*count.tif) and per-pixel normalized median absolute deviation (NMAD, *nmad.tif). The latter captures the spread of elevation values in the input DEMs and offers a metric of relative accuracy.

Shaded relief maps (*hs.tif) are included for visualization of the two elevation composites.  All files are tiled, LZW-compressed GeoTiff format with internal overviews (GDAL gauss resampling).

Many of the input images include scattered clouds, often over mountain peaks (e.g., https://api.discover.digitalglobe.com/show?id=1020010042B88700), leading to nodata gaps and residual artifacts in the corresponding stereo DEMs. These problematic areas can be identified by their low per-pixel count and high per-pixel NMAD values, and we recommend that users mask or avoid analysis in these areas. Higher NMAD values are also observed over forests, steep slopes and open water.

Note that the westernmost ~3 km of the composite is only covered by a single input stereo DEM, resulting in higher error and more artifacts. We chose not to crop this region, as it included additional portions of the affected river system. We hope to integrate additional monoscopic images over this area to improve future DEM composite quality.

We performed a preliminary evaluation of the DEM composites for areas within ~1-2 km of the river systems affected by the February 7, 2021 event. We observed residual artifacts in places, and recommend that users exercise caution when performing quantitative analysis and detailed geomorphologic interpretation.

If possible, the corresponding WorldView-1 and WorldView-2 orthoimages should be used during interpretation of the DEM products to distinguish artifacts from real features. These orthoimages cannot be distributed with the derived DEM products, but they are available via the NGA NextView License for U.S. federal research and can be purchased from Maxar/DigitalGlobe, Inc. Some of these images are licensed and publicly available through services like Google Earth (see Historical Imagery option, https://support.google.com/earth/answer/148094), and others are available through Maxar's Open Data program (https://www.maxar.com/open-data/uttarakhand-flooding, accessed February 22, 2021).

If you use these data products for any purposes, please use the recommended attribution/citation for this Zenodo repository (https://doi.org/10.5281/zenodo.4554647) and cite the following papers:


	Shean, D. E., Bhushan, S., Montesano, P., Rounce, D. R., Arendt, A., &amp; Osmanoglu, B. (2020). A Systematic, Regional Assessment of High Mountain Asia Glacier Mass Balance. Frontiers in Earth Science, 7. https://doi.org/10.3389/feart.2019.00363.
	Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R., Porter, C., &amp; Morin, P. (2016). An automated, open-source pipeline for mass production of digital elevation models (DEMs) from very-high-resolution commercial stereo satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 116, 101–117. https://doi.org/10.1016/j.isprsjprs.2016.03.012.


Support provided by NASA Future Investigators in NASA Earth and Space Science and Technology (FINESST) and NASA High-Mountain Asia Team (HiMAT) programs. The Level-1B WorldView images (© 2015 Maxar/DigitalGlobe, Inc.) were accessed under the NGA NextView license. Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center. 

Input monoscopic WorldView-1 and WorldView-2 images (See https://discover.digitalglobe.com/df08c9e2-74e6-11eb-b74d-e26e2db4a45e for interactive visualization):


	Image ID, Date (YYYYMMDD)
	10200100412F9B00, 20150914
	1020010041635900, 20150914
	1020010042A0F500, 20150910
	1020010042B88700, 20151005
	102001004319BE00, 20150901
	10200100431D4000, 20151001
	10200100438F3E00, 20151001
	1020010044A2A400, 20150901
	10200100456B4C00, 20151005
	103001004866C100, 20150928
	103001004973DC00, 20150928


Corresponding Cross-track Stereo Pairs


	WV01WV01_20150905_102001004319BE00_1020010042A0F500
	WV01WV01_20150905_1020010044A2A400_1020010042A0F500
	WV01WV01_20150907_102001004319BE00_10200100412F9B00
	WV01WV01_20150907_1020010044A2A400_10200100412F9B00
	WV01WV01_20150907_1020010044A2A400_1020010041635900
	WV01WV01_20150912_1020010042A0F500_10200100412F9B00
	WV01WV01_20150912_1020010042A0F500_1020010041635900
	WV01WV01_20150916_102001004319BE00_10200100438F3E00
	WV01WV01_20150916_10200100431D4000_102001004319BE00
	WV01WV01_20150916_10200100431D4000_1020010044A2A400
	WV01WV01_20150918_1020010044A2A400_1020010042B88700
	WV01WV01_20150918_1020010044A2A400_10200100456B4C00
	WV01WV01_20150918_10200100456B4C00_102001004319BE00
	WV01WV01_20150920_1020010042A0F500_10200100438F3E00
	WV01WV01_20150920_10200100431D4000_1020010042A0F500
	WV01WV01_20150922_10200100412F9B00_10200100438F3E00
	WV01WV01_20150922_1020010042B88700_1020010042A0F500
	WV01WV01_20150922_10200100431D4000_10200100412F9B00
	WV01WV01_20150922_10200100431D4000_1020010041635900
	WV01WV01_20150922_10200100456B4C00_1020010042A0F500
	WV01WV01_20150924_1020010042B88700_1020010041635900
	WV01WV01_20150924_10200100456B4C00_10200100412F9B00
	WV01WV01_20151001_10200100431D4000_10200100438F3E00
	WV01WV01_20151003_10200100431D4000_1020010042B88700
	WV01WV01_20151003_10200100431D4000_10200100456B4C00
	WV01WV01_20151003_10200100456B4C00_10200100438F3E00
	WV01WV02_20150914_102001004319BE00_103001004866C100
	WV01WV02_20150914_1020010044A2A400_103001004866C100
	WV01WV02_20150914_1020010044A2A400_103001004973DC00
	WV01WV02_20150919_1020010042A0F500_103001004866C100
	WV01WV02_20150921_10200100412F9B00_103001004866C100
	WV01WV02_20150929_10200100431D4000_103001004866C100
	WV01WV02_20150929_10200100431D4000_103001004973DC00
	WV01WV02_20150929_10200100438F3E00_103001004866C100
	WV01WV02_20151001_10200100456B4C00_103001004866C100
	WV02WV01_20150919_103001004973DC00_1020010042A0F500
	WV02WV01_20150921_103001004973DC00_1020010041635900
	WV02WV01_20151001_103001004973DC00_1020010042B88700
</dc:description>
  <dc:identifier>https://zenodo.org/record/4554647</dc:identifier>
  <dc:identifier>10.5281/zenodo.4554647</dc:identifier>
  <dc:identifier>oai:zenodo.org:4554647</dc:identifier>
  <dc:relation>doi:10.5281/zenodo.4533678</dc:relation>
  <dc:relation>doi:10.5281/zenodo.4554646</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc/4.0/legalcode</dc:rights>
  <dc:title>Chamoli Disaster Pre-event 2-m DEM Composite: September 2015</dc:title>
  <dc:type>info:eu-repo/semantics/other</dc:type>
  <dc:type>dataset</dc:type>
</oai_dc:dc>
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