|Paper title||UndercoverEisAgenten - Bird's Eye View of Permafrost Thawing|
|Form of presentation||Poster|
People in the Arctic have been experiencing severe changes to their landscapes for several decades. One cause is the thawing of permafrost and thermokarst, which affects the livelihoods of indigenous people. The thawing process of permafrost is also associated with ecological impacts including the release of greenhouse gases.
Thawing is evident from very small-scale changes and disturbances to the land surface, which have been inadequately documented. By fusing local knowledge on landscape changes in Northwest Canada and remote sensing, we seek to thoroughly understand and monitor land surface changes attributable to permafrost thaw. The goal is to improve our knowledge on permafrost thaw impacts through the acquisition and analysis of UAV (Unmanned Aerial Vehicle) and satellite imagery together with young Citizen Scientists from schools in Northwest Canada and Germany. The high-resolution UAV data will be utilized as a ground truthing baseline dataset for further analyses employing optical and radar remote sensing time series data to gain a better understanding of the long-term changes in the region. This approach allows for the expansion of spaceborne remote sensing to very inaccessible regions in the global north while maintaining knowledge of the conditions on the ground. Due to the planned acquisition period of multiple years as well as the fast pace of changing environments on the ground, a change detection is possible within a short time period. Because one of the main goals of this project is the employment of cost-efficient consumer-grade UAVs, flight parameters must be optimized to enable precise 3D-models created by SfM (Structure from Motion), which are comparable over time as well as consistent with the spaceborne remote sensing datasets.
Permafrost soil oftentimes stands out due to its striking polygonal surface features, especially if degradation processes have already set in. These structures range over different spatial scales and can be utilized to determine the grade of degradation. The very high-resolution UAV imagery provide insights into the small-scale thermo-hydrological and geomorphological processes controlling permafrost thaw. Using UAV datasets to deliver labeled datasets to train automatic AI-based classification and image enhancement schemes, land surface disturbances could be detected on the Arctic scale with the high temporal repeat acquisitions of satellite remote sensing platforms. Thus, a comprehensive archive of observable surface features indicating the degree of degradation can be developed. For this, an automated workflow is going to be implemented, deriving the surface features from the acquired datasets with a subsequent analysis and monitoring of permafrost degradation based on classical image processing approaches as well as KI-based classification methods.
In support of these methods, citizen scientist are involved in the classification and evaluation process. To this end, school classes from both countries will participate in "virtual shared classrooms" to collect and analyze high-resolution remote sensing data. Students in Germany will be able to gain a direct connection to Northwest Canada through data and knowledge exchange with class mentors. The goals are to transfer knowledge and raise awareness about global warming, permafrost, and related regional and global challenges. The scientific data will provide new insights into biophysical processes in Arctic regions and contribute to a large-scale understanding of the state and change of permafrost in the Arctic.
The project “UndercoverEisAgenten”, funded by the Federal Ministry of Education and Research in Germany, was initiated in summer 2021.