The Permafrost Airborne SAR Experiment campaign (PermASAR) is an airborne Synthetic Aperture Radar (SAR) campaign carried out by the German Aerospace Center (DLR) over several sites in Canada. The aim of the campaign was to contribute to the investigation and understanding of the interactions between radar waves and the elements of permafrost landscapes, in particular soil and vegetation. The campaign entailed two consecutive missions, which took place in summer 2018 and winter 2019, so as to capture the seasonal variations of landscape elements. Ten sites along a North-South gradient in Canada, ranging from tundra landscapes to boreal forest, were imaged with DLR’s experimental airborne sensor F-SAR [1]. The acquisitions were made at several frequencies (X-, C-, S- and L-band), in fully-polarimetric mode, and with different configurations (interferometric, tomographic). The images have sub-meter spatial resolution.

F-SAR data from the PermASAR campaign was used in the frame of the Hidden Image of Thawing Permafrost (HIT Permafrost) project. The HIT project was a collaboration between the DLR and the Alfred Wegener Institute (AWI). It aimed at improving the description of permafrost landscapes and permafrost subsurface features using a combination of remote sensing techniques (radar data, optical data, laser scanning) and relying both on physical modelling and machine learning approaches. A test site common to both institutions (AWI, DLR) was chosen, namely the Trail Valley Creek site (68.7°N, 133.5°W, Nortwest Territories, Canada). Trail Valley Creek is well monitored continuous permafrost site in the Western Canadian Arctic, at the transition between boreal forest and tundra. F-SAR acquisitions over Trail Valley Creek on the 15th August 2018 and 23rd of March 2019 were used to analyze both summer and winter conditions [2].

The PermASAR dataset is archived on DLR's EOWEB portal (https://eoweb.dlr.de/) and is available upon request.

[1] Reigber et al. (2013), "Very-High-Resolution Airborne Synthetic Aperture Radar Imaging: Signal Processing and Applications", Proceedings of the IEEE 101, 759–783.

[2] Saporta et al. (2025), "Observing seasonal variabilities of a permafrost landscape with PolSAR, InSAR and Pol-InSAR", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 10733-10748.