UNDERCOVEREISAGENTEN - INTEGRATING LOW-COST UAVS AND COMMUNITY INSIGHTS FOR ENHANCED PERMAFROST MONITORING - Mueller, Marlin M.; Dietenberger, Steffen; Nestler, Maximilian; Dubois, Clemence; Kaiser, Soraya; Lenz, Josefine; Langer, Moritz; Fritz, Oliver; Marx, Sabrina; Thiel, Christian (IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 2024)
This study investigates the integration of low-cost unoccupied aerial vehicles (UAVs) and community engagement in permafrost monitoring. Utilizing novel UAV flight patterns and crowdsourced data analysis, including a Convolutional Neural Network (CNN), the study enhances digital surface models (DSMs) for identifying ice-wedge polygons. Conducted in rapidly changing Arctic regions, it demonstrates an overall accuracy of 74.56% in feature detection. This approach offers improved resolution in environmental monitoring and suggests potential for broader application and rapid disaster response through community-sourced scientific analysis and consumer UAVs.