Dataset Restricted Access

Unmanned aerial vehicle data of Lirung Glacier and Langtang Glacier for 2013–2018

Kraaijenbrink, P. D. A.; Immerzeel, W. W.

Data collector(s)
Steiner, J. F.; Stigter, E. E.; Shea, J. M.; Koch, I; Wagnon, P.; de Jong, S. M.

This dataset contains the raw data as well as produced image mosaics, digital elevation models (DEMs) and data derivatives of optical (RGB) unmanned aerial vehicle surveys of the debris-covered Lirung Glacier (9 surveys, 2013–2018) and Langtang Glacier (7 surveys, 2014–2018) in the Langtang Catchment, Nepalese Himalaya.

All data in this dataset are stored in tape archive (tar) or gzip-compressed tape archive (tar.gz) formats and require extraction before use.

The projected coordinate system used in this dataset is WGS 1984 UTM Zone 45N (EPSG:32645). Survey dates are always provided as yyyymmdd.


File descriptions

  • dems_<glacier>.tar
    20 cm resolution DEMs that were derived from the raw UAV images. DEMs of all survey dates are included in the tar archives. File format is GeoTIFF.
  • orthomosaics_<glacier>.tar
    10 cm resolution image mosaics of orthorectified source imagery (orthomosaics) that were derived from the raw UAV images. Orthomosaics of all survey dates are included in the tar archives. File format is GeoTIFF.
  • point-clouds_<glacier>.tar.gz
    Raw dense point clouds that were derived from the raw UAV images. Point clouds of all survey dates are included in the tar archive. File format is ASPRS LAS. Note that additional gzip-compression has been applied to the archives.
  • raw-data_<glacier>_<datestamp>.tar
    Raw data of each of the surveys that were performed over 2013–2018. The filename includes the glacier name and the survey date. Each tar archive contains directories for each UAV flight associated to that specific survey, indicated by f1, f2, ..., fn. The flight directories have the following contents:
    • img
      Subdirectory that contains the individual images in JPEG format captured by the UAV camera.
    • *flight_path.kml (not present for all surveys)
      Keyhole Markup Language file that contains the flight path of the UAV recorded by the UAV's internal GPS+GLONASS sensor.
    • *image_geoinfo.txt
      Table with coordinates (x,y,z) and UAV orientation (roll, tilt, yaw) for every image in img, which were recorded by the UAV's internal GPS+GLONASS sensor and gyroscope, respectively.
    • *drone_log.bbx or *drone_log.bb3
      Binary flight log file from the UAV containing detailed flight information. Can be read by the proprietary eMotion software by UAV manufacturer senseFly.
  • supplementary-animation_<glacier>.gif
    Animations of Langtang Glacier (2014–2018) and Lirung Glacier (2013–2017) supplementary to Kraaijenbrink & Immerzeel (2020). The high resolution time lapse animations are constructed from composites of the orthomosaic and hillshaded DEM. Since the animations are in GIF format, they are best viewed in a web browser in which they can be zoomed and panned.
  • supplementary-data-to-article.tar
    Data derivatives as presented in Kraaijenbrink & Immerzeel (2020). The tar archive contains a README file with additional information and metadata for each of the datasets present in the archive. The archive contains:
    • Independent error measurements of the Lirung Glacier UAV product
    • Vector outlines of the area of interests of both glaciers
    • Point cloud extracts of supraglacial ice cliff cross profiles
    • Flow and gradient corrected DEMs (1 m resolution)
    • Pixel-wise regression of the flow-corrected DEMs (1 m resolution)
    • Surface velocity between survey pairs (8 m resolution)



For further information, e.g. about the UAV systems and cameras used, as well as detailed descriptions of the data and the applied data processing please refer to:

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This dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).



Dr Philip Kraaijenbrink (
Prof Dr Walter Immerzeel (



This dataset is enabled by the funds of the Climate-KIC programme from the European Institute of Innovation and Technology (EIT), The UK Department for International Development (grant agreement No. PO40082504), the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 676819), The Netherlands Organization for Scientific Research (NWO) under the Innovational Research Incentives Scheme VIDI (grant agreement 016.181.308), by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant agreement number XDA20100300), and by core funds of The International Centre of Integrated Mountain Development (ICIMOD).
Restricted Access

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