EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Dunes as palaeo-wind vanes: Investigating palaeowind regimes using semi-automated remote sensing approaches to dunefield mapping and orientation quantification 

Maike Nowatzki1,2,3, Kathryn Fitzsimmons3, Hartwig Harder4, and Hans-Joachim Rosner2
Maike Nowatzki et al.
  • 1School of Geography and the Environment, University of Oxford, Oxford, United Kingdom (
  • 2Department of Geography, University of Tübingen, Tübingen, Germany
  • 3Research Group for Terrestrial Palaeoclimates, Max Planck Institute for Chemistry, Mainz, Germany
  • 4Department of Atmospheric Chemistry, Max Planck Institute for Chemistry, Mainz, Germany

Many dryland regions of the world are at high risk of desertification from combined human land use and anthropogenic climate change. One symptom of desertification is the reactivation of previously stable dunefields. Since morphologies of stable dunes are thought to reflect wind regimes at the time of their formation, the degree to which dune orientation reflects modern winds may be one way to assess changes in wind regimes and the progression of desertification in a region.

Here we investigate the relationship between wind dynamics and desert dune orientation in one region at risk of desertification, southeast Kazakhstan in Central Asia, on the basis of open-source software and open-access datasets. Using Google Earth Engine, we map dunes or interdune spaces within six palaeo-dunefields in the Ili-Balkhash area, by performing a multi-layer object-based image analysis (OBIA) on satellite remote sensing data (Sentinel-2 optical imagery and SRTM digital elevation models). A semi-automated GIS approach is used to undertake data cleansing and the quantification of dominant palaeo-dunefield orientations. The resulting orientation trends are concurrent with the region’s topography: The dunefields within the Ili valley show a narrow, mostly E-W oriented trend concurrent with the course of the valley while the orientation ranges become broader towards the open pre-Balkhash area.

We then predict modern dune orientations by applying the maximum gross bedform-normal transport rule on reanalysed wind data for 2008-2018. This approach by Rubin and Hunter (1987) allows the deduction of sand transport and resulting bedform trends from wind direction frequencies. The predicted modern orientation trends for the dunefields in the Ili-Balkhash area yield only partial consensus with observed palaeo-bedform trends. We therefore propose that modern wind regimes are not exclusively responsible for existing dune morphologies in the region, and that dune orientation may be inherited from earlier wind regimes.

How to cite: Nowatzki, M., Fitzsimmons, K., Harder, H., and Rosner, H.-J.: Dunes as palaeo-wind vanes: Investigating palaeowind regimes using semi-automated remote sensing approaches to dunefield mapping and orientation quantification , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6067,, 2021.


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