Permafrost Terrain Dynamics and Infrastructure Impacts Revealed by UAV Photogrammetry and Thermal Imaging

Abstract

Unmanned Aerial Vehicle (UAV) systems, sensors, and photogrammetric processing techniques have enabled timely and highly detailed three-dimensional surface reconstructions at a scale that bridges the gap between conventional remote-sensing and field-scale observations. In this work 29 rotary and fixed-wing UAV surveys were conducted during multiple field campaigns, totaling 47 flights and over 14.3 km2, to document permafrost thaw subsidence impacts on or close to road infrastructure in the Northwest Territories, Canada. This paper provides four case studies: (1) terrain models and orthomosaic time series revealed the morphology and daily to annual dynamics of thaw-driven mass wasting phenomenon (retrogressive thaw slumps; RTS). Scar zone cut volume estimates ranged between 3.2 × 103 and 5.9 × 106 m3. The annual net erosion of RTS surveyed ranged between 0.35 × 103 and 0.39 × 106 m3. The largest RTS produced a long debris tongue with an estimated volume of 1.9 × 106 m3. Downslope transport of scar zone and embankment fill materials was visualized using flow vectors, while thermal imaging revealed areas of exposed ground ice and mobile lobes of saturated, thawed materials. (2) Stratigraphic models were developed for RTS headwalls, delineating ground-ice bodies and stratigraphic unconformities. (3) In poorly drained areas along road embankments, UAV surveys detected seasonal terrain uplift and settlement of up to 0.5 m (>1700 m2 in extent) as a result of injection ice development. (4) Time series of terrain models highlighted the thaw-driven evolution of a borrow pit (6.4 × 105 m3 cut volume) constructed in permafrost terrain, whereby fluvial and thaw-driven sediment transfer (1.1 and 3.9 × 103 m3 a−1 respectively) was observed and whereby annual slope profile reconfiguration was monitored to gain management insights concerning site stabilization. Elevation model vertical accuracies were also assessed as part of the case studies and ranged between 0.02 and 0.13 m Root Mean Square Error, whereby photogrammetric models processed with Post-processed Kinematic image solutions achieved similar accuracies without ground control points over much larger and complex areas than previously reported. The high resolution of UAV surveys, and the capacity to derive quantitative time series provides novel insights into permafrost processes that are otherwise challenging to study. The timely emergence of these tools bridges field-based research and applied studies with broad-scale remote-sensing approaches during a period when climate change is transforming permafrost environments.

UAV-Based High Resolution Thermal Imaging for Vegetation Monitoring, and Plant Phenotyping Using ICI 8640 P, FLIR Vue Pro R 640, and thermoMap Cameras

“…It briefly closes its shutter at each waypoint, takes a photo of the back of the shutter, and automatically calibrates itself during the mission. To calibrate the level of grey in the photos, that photo is then compared to the temperature that was measured by the built-in temperature sensor [49,56,57]. In this case, the radiometric TIFF image was converted to temperature in degree Celsius directly with the equation designated for this camera with the Pix4DMapper software package [48,49].…”

Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects

“…Additional considerations for flight planning are to keep flight orientation consistent among repeated flights to maintain shadow location and to follow parallel tracks because cross-tracks add extra flight time and have been found to be unhelpful in increasing point cloud density or accuracy if adequate control points are available [94,118]. Finally, van der Sluijs et al [91] recommended a methodology that includes a minimum and optimized GNSS-based GCP/CP network, and if available, incorporates regional high-resolution airborne laser scanning topographic data to tie in fine-scale DSM-like products derived by UAV surveys.…”

“…Another permafrost application by Gonzalez, et al [77] used UAVs to create high-resolution DSMs to describe pingo (conical ice-cored hill) morphologies, but at the time of writing, this work was not yet published in the final form. Van der Sluijs et al [91] used various fixed wing and multirotor UAVs with five optical and one thermal sensor to identify thaw slump features using a previous LiDAR survey as a baseline. Additionally, they were able to collect high-resolution soil stratification images along a headwall, which would have been a hazardous task to sample otherwise.…”

“…Considerations when selecting RGB cameras should include a quality lens to reduce geometric distortions, and less obvious, the charge-coupled device that could influence the signal-to-noise ratio of collected data [117]. Van der Sluijs et al [91], when mapping permafrost thaw features, suggested using a standard minimum size and resolution of greater than or equal to 1 inch sensor and 16-20 megapixels, respectively, to ensure precision and accuracy of DSMs. This protocol proved to be useful for a range of flight altitudes 40-120 m above ground.…”

“…Lastly, several studies used the preinstalled camera from off-the-shelf DJI products. While these served many applications well, van der Sluijs et al [91] found the Zenmuse X5 camera onboard the DJI Inspire 1 Pro had a relatively slow-rolling shutter, producing motion distortions that had to be corrected post-flight. Increasing shutter speeds while balancing other exposure parameters such as ISO and lens aperture can improve blurred distortions [118], although specific calibrations vary with sensor, illumination, and flight plan.…”