Published February 21, 2021 | Version 1.0
Dataset Open

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

  • 1. University of Washington


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.

Specific "fine quality" ASP correlator settings, beyond defaults (

  • --stereo-algorithm 2 (More Global Matching (MGM))
  • --cost-mode 3 (census transform)
  • --subpixel-mode 9 (SGM Poly4) 
  • --corr-kernel 7x7 px 
  • --subpixel-kernel 15x15 px

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 ( using the demcoreg/ utility ( 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 (  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.,, 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,, and others are available through Maxar's Open Data program (, accessed February 22, 2021).

If you use these data products for any purposes, please use the recommended attribution/citation for this Zenodo repository ( and cite the following papers:

  • Shugar, D. H., M. Jacquemart, D. Shean, S. Bhushan, K. Upadhyay, A. Sattar, W. Schwanghart, S. McBride, M. V. W. de Vries, M. Mergili, A. Emmer, C. Deschamps-Berger, M. McDonnell, R. Bhambri, S. Allen, E. Berthier, J. L. Carrivick, J. J. Clague, M. Dokukin, S. A. Dunning, H. Frey, S. Gascoin, U. K. Haritashya, C. Huggel, A. Kääb, J. S. Kargel, J. L. Kavanaugh, P. Lacroix, D. Petley, S. Rupper, M. F. Azam, S. J. Cook, A. P. Dimri, M. Eriksson, D. Farinotti, J. Fiddes, K. R. Gnyawali, S. Harrison, M. Jha, M. Koppes, A. Kumar, S. Leinss, U. Majeed, S. Mal, A. Muhuri, J. Noetzli, F. Paul, I. Rashid, K. Sain, J. Steiner, F. Ugalde, C. S. Watson, and M. J. Westoby (2021), A massive rock and ice avalanche caused the 2021 disaster at Chamoli, Indian Himalaya, Science, 373(6552), 300–306, doi:10.1126/science.abh4455.

  • Shean, D. E., Alexandrov, O., Moratto, Z. M., Smith, B. E., Joughin, I. R., Porter, C., & 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.

  • Shean, D. E., Bhushan, S., Montesano, P., Rounce, D. R., Arendt, A., & Osmanoglu, B. (2020). A Systematic, Regional Assessment of High Mountain Asia Glacier Mass Balance. Frontiers in Earth Science, 7.

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 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



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Additional details

Related works

Is new version of
Dataset: 10.5281/zenodo.4533678 (DOI)
Is supplement to
Journal article: 10.1126/science.abh4455 (DOI)