Before-, during-, and after-flood UAV-generated images of the distal part of Zackenberg river, northeast Greenland (August 2017)

This dataset contains a time series of very high-resolution images of the distal part of Zackenberg River, northeast Greenland. Images were captured using an unmanned aerial vehicle (UAV) immediately before (5th August 2017), during (6th August 2017), and after (8th August 2017) the glacier lake outburst flood.

Data cover a 2.1-km-long distal section of Zackenberg river, from the delta to the bridge. Images were captured with high overlap; therefore, they can be processed in photogrammetric software. They are georeferenced using UAV onboard GNSS system and can be coregistered using a model-to-model approach or external ground control points. Images are organized into three zipped files, according to the capture date.

Potential applications of the presented dataset include:

assessment and quantification of landscape changes as an immediate result of glacier lake outburst flood;

long-term monitoring of high-Arctic river valley development (in conjunction with other datasets);

establishing a baseline for quantification of geomorphological impacts of future glacier lake outburst floods;

assessment of geohazards related to bank erosion and debris flow development (hazards for research station infrastructure – station buildings and bridge);

monitoring of permafrost degradation; and

modelling flood impacts on river ecosystem, transport capacity, and channel stability.

This dataset contains unprocessed images. Photogrammetric products derived from the images (orthomosaics, digital elevation models, hillshade models) and GIS products, which are the results of the geomorphological mapping, can be accessed at:  https://doi.org /10.5281/zenodo.4498296  (Tomczyk and Ewertowski, 2021)

Tomczyk A.M., Ewertowski M.W., 2021: Before-, during-, and after-flood UAV-generated digital elevation models, orthomosaics, and GIS datasets of the distal part of Zackenberg river, northeast Greenland (August 2017), https://doi.org /10.5281/zenodo.4498296