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Spatially detailed information on permafrost distribution and change with climate is important for land use planning, infrastructure development, and environmental assessments. However, the required soil and surficial geology maps in the North are coarse, and projected climate scenarios vary widely. Considering these uncertainties, we propose a new approach to mapping permafrost distribution and change by integrating remote sensing data, field measurements, and a process-based model. Land cover types from satellite imagery are used to capture the general land conditions and to improve the resolution of existing permafrost maps. For each land cover type, field observations are used to estimate the probabilities of different ground conditions. A process-based model is used to quantify the evolution of permafrost for each ground condition under three representative climate scenarios (low, medium, and high warming). From the model results, the probability of permafrost occurrence and the most likely permafrost conditions are determined. We apply this approach at 20 m resolution to a large area in Northwest Territories, Canada. Mapped permafrost conditions are in agreement with field observations and other studies. The data requirements, model robustness, and computation time are reasonable, and this approach may serve as a practical means to mapping permafrost and changes at high resolution in other regions.

Most spatial modelling of climate change impacts on permafrost has been conducted at half-degree latitude/longitude or coarser spatial resolution. At such coarse resolution, topographic effects on insolation cannot be considered accurately and the results are not suitable for land-use planning and ecological assessment. Here we mapped climate change impacts on permafrost from 1968 to 2100 at 10 m resolution using a process-based model for Ivvavik National Park, an Arctic region with complex terrain in northern Yukon, Canada. Soil and drainage conditions were defined based on ecosystem types, which were mapped using SPOT imagery. Leaf area indices were mapped using Landsat imagery and the ecosystem map. Climate distribution was estimated based on elevation and station observations, and the effects of topography on insolation were calculated based on slope, aspect and viewshed. To reduce computation time, we clustered climate distribution and topographic effects on insolation into discrete types. The modelled active-layer thickness and permafrost distribution were comparable with field observations and other studies. The map portrayed large variations in active-layer thickness, with ecosystem types being the most important controlling variable, followed by climate, including topographic effects on insolation. The results show deepening in active-layer thickness and progressive degradation of permafrost, although permafrost will persist in most of the park during the 21st century. This study also shows that ground conditions and climate scenarios are the major sources of uncertainty for high-resolution permafrost mapping.

Northern environments are changing in response to recent climate warming, resource development, and natural disturbances. The Arctic climate has warmed by 2–3°C since the 1950’s, causing a range of cryospheric changes including declines in sea ice extent, snow cover duration, and glacier mass, and warming permafrost. The terrestrial Arctic has also undergone significant temperature-driven changes in the form of increased thermokarst, larger tundra fires, and enhanced shrub growth. Monitoring these changes to inform land managers and decision makers is challenging due to the vast spatial extents involved and difficult access. Environmental monitoring in Canada’s North is often based on local-scale measurements derived from aerial reconnaissance and photography, and ecological, hydrologic, and geologic sampling and surveying. Satellite remote sensing can provide a complementary tool for more spatially comprehensive monitoring but at coarser spatial resolutions. Satellite remote sensing has been used to map Arctic landscape changes related to vegetation productivity, lake expansion and drainage, glacier retreat, thermokarst, and wildfire activity. However, a current limitation with existing satellite-based techniques is the measurement gap between field measurements and high resolution satellite imagery. Bridging this gap is important for scaling up field measurements to landscape levels, and validating and calibrating satellite-based analyses. This gap can be filled to a certain extent using helicopter or fixed-wing aerial surveys, but at a cost that is often prohibitive. Unmanned aerial vehicle (UAV) technology has only recently progressed to the point where it can provide an inexpensive and efficient means of capturing imagery at this middle scale of measurement with detail that is adequate to interpret Arctic vegetation (i.e. 1–5 cm) and coverage that can be directly related to satellite imagery (1–10 km2). Unlike satellite measurements, UAVs permit frequent surveys (e.g. for monitoring vegetation phenology, fires, and hydrology), are not constrained by repeat cycle or cloud cover, can be rapidly deployed following a significant event, and are better suited than manned aircraft for mapping small areas. UAVs are becoming more common for agriculture, law enforcement, and marketing, but their use in the Arctic is still rare and represents untapped technology for northern mapping, monitoring, and environmental research. We are conducting surveys over a range of sensitive or changing northern landscapes using a variety of UAV multicopter platforms and small sensors. Survey targets include retrogressive thaw slumps, tundra shrub vegetation, recently burned vegetation, road infrastructure, and snow. Working with scientific partners involved in northern monitoring programs (NWT CIMP, CHARS, NASA ABOVE, NRCan-GSC) we are investigating the advantages, challenges, and best practices for acquiring high resolution imagery from multicopters to create detailed orthomosaics and co-registered 3D terrain models. Colour and multispectral orthomosaics are being integrated with field measurements and satellite imagery to conduct spatial scaling of environmental parameters. Highly detailed digital terrain models derived using structure from motion (SfM) photogrammetry are being applied to measure thaw slump morphology and change, snow depth, tundra vegetation structure, and surface condition of road infrastructure. These surveys and monitoring applications demonstrate that UAV-based photogrammetry is poised to make a rapid contribution to a wide range of northern monitoring and research applications.

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