DOI: 10.5281/zenodo.12826263
title: Unmanned aerial system data of Lirung Glacier and Langtang Glacier for 2013–2018

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Warning

Use Latest Dataset Version (1.2.0)



Please use the latest version of the dataset (1.2.0), which can be found at https://zenodo.org/records/13073856. Version 1.1.0 was mistakenly linked as supplementary data in the article below. The correct supplementary data for the paper is version 1.2.0.

 



Kraaijenbrink, P. D. A., & Immerzeel, W. W. (2025). Spatial and Temporal Variability of the Surface Mass Balance of Debris-Covered Glacier Tongues. Journal of Geophysical Research: Earth Surface, 130(3), e2024JF007935. https://doi.org/10.1029/2024JF007935

 



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This dataset contains the raw data as well as produced image mosaics, digital elevation models (DEMs) and data derivatives of optical (RGB) unmanned aerial system (UAS) 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>.tar20 cm resolution DEMs that were derived from the raw UAS images. DEMs of all survey dates are included in the tar archives. File format is GeoTIFF. 

orthomosaics_<glacier>.tar10 cm resolution image mosaics of orthorectified source imagery (orthomosaics) that were derived from the raw UAS images. Orthomosaics of all survey dates are included in the tar archives. File format is GeoTIFF. 

point-clouds_<glacier>.tar.gzDense point clouds that were derived from the raw UAS 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>.tarRaw 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 UAS flight associated to that specific survey, indicated by f1, f2, ..., fn. The flight directories have the following contents:



imgSubdirectory that contains the individual images in JPEG format captured by the UAS camera.

*flight_path.kml (not present for all surveys)Keyhole Markup Language file that contains the flight path of the UAS recorded by its internal GPS+GLONASS sensor.

*image_geoinfo.txtTable with coordinates (x,y,z) and UAS orientation (roll, tilt, yaw) for every image in img, which were recorded by the UAS' internal GPS+GLONASS sensor and gyroscope, respectively.

*drone_log.bbx or *drone_log.bb3Binary flight log file from the UAS containing detailed flight information. Can be read by the proprietary eMotion software by UAS manufacturer senseFly. 



supplementary-animation_<glacier>.gifAnimations 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.tarData derivatives as presented in Kraaijenbrink & Immerzeel (2024). The tar archive contains a README file with additional information for each of the datasets present in the archive. The archive contains:



Three dimensional error measurements of the UAS-derived orthomosaics and elevation models

Vector outlines of the areas of interest of both glaciers

Surface displacement (i.e. velocity) between survey pairs (8 m resolution)

Uncorrected and flow-corrected DEMs (1 m resolution)

Elevation change (dh/dt) and surface mass balance (db/dt) grids based on pixel-wise regression (1 m resolution)

Point cloud extracts of supraglacial ice cliff cross profiles




 

License

This dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).(https://creativecommons.org/licenses/by/4.0/)

 

Correspondence

Dr Philip Kraaijenbrink (p.d.a.kraaijenbrink@uu.nl)Prof Dr Walter Immerzeel (w.w.immerzeel@uu.nl)

 

 
description: 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).