EGU23-2698, updated on 24 Sep 2023
https://doi.org/10.5194/egusphere-egu23-2698
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

UndercoverEisAgenten - Monitoring Permafrost Thaw in the Arctic using Local Knowledge and UAVs

Marlin M. Mueller1, Christian Thiel1, Soraya Kaiser2, Josefine Lenz2, Moritz Langer2, Hugues Lantuit2, Sabrina Marx3, Oliver Fritz3, and Alexander Zipf3
Marlin M. Mueller et al.
  • 1German Aerspace Center, Institute of Data Science, Jena, Germany (marlin.mueller@dlr.de)
  • 2Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany
  • 3Heidelberg Institute for Geoinformation Technology, Heidelberg, Germany

The Arctic is experiencing severe changes to its landscapes due to the thawing of permafrost influenced by the twofold increase of temperature across the Arctic due to global warming compared to the global average. This process, which affects the livelihoods of indigenous people, is also associated with the further release of greenhouse gases and also connected to ecological impacts on the arctic flora and fauna. These small-scale changes and disturbances to the land surface caused by permafrost thaw have been inadequately documented.

To better understand and monitor land surface changes, the project "UndercoverEisAgenten" is using a combination of local knowledge, satellite remote sensing, and data from unmanned aerial vehicles (UAVs) to study permafrost thaw impacts in Northwest Canada. The high-resolution UAV data will serve as a baseline for further analysis of optical and radar remote sensing time series data. The project aims to achieve two main goals: 1) to demonstrate the value of using unmanned aerial vehicle (UAV) data in remote regions of the global north, and 2) to involve young citizen scientists from schools in Canada and Germany in the process. By involving students in the project, the project aims to not only expand the use of remote sensing in these regions, but also provides educational opportunities for the participating students. By using UAVs and satellite imagery, the project aims to develop a comprehensive archive of observable surface features that indicate the degree of permafrost degradation. This will be accomplished through the use of automatic image enhancement techniques, as well as classical image processing approaches and machine learning-based classification methods. The data is being prepared to be shared and analyzed through a web-based crowd mapping application. The project aims to involve the students in independently acquiring data and developing their own scientific questions through the use of this application.

In September 2022, a first expedition was conducted in the Northwest Territories, Canada and UAV data was collected with the assistance of students from Moose Kerr School in Aklavik. The data consists of approximately 30,000 individual photos taken over an area of around 13 km². The expedition also provided an opportunity for the students to learn about the basics of data collection and the goals of the collaborative permafrost survey, which included the incorporation of local knowledge to address the questions of the local community.

By involving school students in the data acquisition, classification and evaluation process, the project also seeks to transfer knowledge and raise awareness about global warming, permafrost, and related regional and global challenges. Additionally, a connection through the shared research experience between students in Germany and Canada is established to enable the exchange of knowledge. The resulting scientific data will provide new insights into biophysical processes in Arctic regions and contribute to a better understanding of the state and change of permafrost in the Arctic. This project is funded by the German Federal Ministry of Education and Research and was initiated in 2021.

How to cite: Mueller, M. M., Thiel, C., Kaiser, S., Lenz, J., Langer, M., Lantuit, H., Marx, S., Fritz, O., and Zipf, A.: UndercoverEisAgenten - Monitoring Permafrost Thaw in the Arctic using Local Knowledge and UAVs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2698, https://doi.org/10.5194/egusphere-egu23-2698, 2023.