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Roads constructed on permafrost can have a significant impact on the surrounding environment, potentially inducing permafrost degradation. These impacts arise from factors such as snow accumulation near the road, which affects the soil's thermal and hydrological regime, and road dust that decreases the snow's albedo, altering the timing of snowmelt. However, our current understanding of the magnitude and the spatial extent of these effects is limited. In this study we addressed this gap by using remote sensing techniques to assess the spatial effect of the Inuvik to Tuktoyaktuk Highway (ITH) in Northwest Territories, Canada, on snow accumulation, snow albedo and snowmelt patterns. With a new, high resolution snow depth raster from airborne laser scanning, we quantified the snow accumulation at road segments in the Trail Valley Creek area using digital elevation model differencing. We found increased snow accumulation up to 36m from the road center. The magnitude of this snow accumulation was influenced by the prevailing wind direction and the embankment height. Furthermore, by analyzing 43 Sentinel-2 satellite images between February and May 2020, we observed reduced snow albedo values within 500m of the road, resulting in a 12-days-earlier onset of snowmelt within 100m from the road. We examined snowmelt patterns before, during and after the road construction using the normalized difference snow index from Landsat-7 and Landsat-8 imagery. Our analysis revealed that the road affected the snowmelt pattern up to 600m from the road, even in areas which appeared undisturbed. In summary, our study improves our understanding of the spatial impact of gravel roads on permafrost due to enhanced snow accumulation, reduced snow albedo and earlier snowmelt. Our study underscores the important contribution that remote sensing can provide to improve our understanding of the effects of infrastructure development on permafrost environments. [ABSTRACT FROM AUTHOR]

In the warming Arctic, retrogressive thaw slumping (RTS) has emerged as the primary thermokarst modifier of ice-rich permafrost slopes, raising urgency to investigate the distribution and intensification of disturbances and the cascade of effects. Tracking RTS is challenging due to the constraints of remote sensing products and a narrow understanding of complex, thaw-driven landforms; however, high-resolution elevation models provide new insights into geomorphic change. Structural traits, such as RTS depth of thaw or volume, can be obtained through allometric scaling. To address fundamental knowledge gaps related to area–volume scaling of RTS, a suitable surface interpolation technique was first needed to model pre-disturbance topography upon which volume estimates could be based. Among eight methods with 32 parameterizations, natural neighbour surface interpolation achieved the best precision in reconstructing pre-disturbed slope topography (90th percentile root mean square difference ±1.0 m). An inverse association between RTS volume and relative volumetric error was observed, with uncertainties < 10 % for large slumps and < 20 % for small to medium slumps. Second, a multisource slump inventory (MSI) for two study areas in the Beaufort Delta (Canada) region was developed to characterize the diverse range of disturbance morphologies and activity levels, which provided consistent characterization of thaw-slump-affected slopes between regions and through time. The MSI delineation of high-resolution hillshade digital elevation models (DEMs) for three time periods (airborne stereo-imagery, lidar, ArcticDEM) revealed temporal and spatial trends in these chronic mass-wasting features. For example, in the Tuktoyaktuk Coastlands, a + 38 % increase in active RTS counts and + 69 % increase in total active surface area were observed between 2004 and 2016. However, the total disturbance area of RTS-affected terrain did not change considerably (+ 3.5 %) because the vast majority of active thaw slumping processes occurred in association with past disturbances. Interpretation of thaw-driven change is thus dependent on how active RTS is defined to support disturbance inventories. Our results highlight that active RTS is tightly linked to past disturbances, underscoring the importance of inventorying inactive scar areas. Third, the pre-disturbance topographies, MSI digitizations, and DEMs were integrated to explore allometric scaling relationships between RTS area and eroded volume. The power-law model indicated non-linearity in the rates of RTS expansion and intensification across scales (adj- R2 of 0.85, n= 1522) but also revealed that elongated, shoreline RTS reflects outliers poorly represented by the modelling. These results indicate that variation in the allometric scaling of RTS populations is based on morphometry, terrain position, and complexity of the disturbance area, as well as the method and ontology by which slumps are inventoried. This study highlights the importance of linking field-based knowledge to feature identification and the utility of high-resolution DEMs in quantifying rates of RTS erosion beyond tracking changes in the planimetric area. [ABSTRACT FROM AUTHOR]

Northern boreal forests are characterized by open stands whereby trees, understory background, and shadow are all significant components of the spectral response within a pixels' spatial footprint. To overcome this mixed pixel problem, accurate spectral characterization of these (endmember) components is necessary for spectral mixture analysis (SMA) to generate forest classifications at the species level. Obtaining these endmember spectra in the field, however, can be difficult or impossible. This study examined whether image endmember spectra can be identified using forest inventory information to derive dominant tree species classifications. This was tested using multiple-endmember SMA (MESMA) and single- and multi-date Landsat imagery of a forested area in the Northwest Territories, Canada. Image classifications (n = 80) were generated based on 20 image-date combinations and four unmixing models. Accuracies of 80% and 82% were achieved for open and medium dense forest stands, respectively using multi-date imagery, which outperformed single-date imagery acquired at peak phenology. The overall accuracy is 72%; lower due to challenges in very open stands. The multi-date MESMA approach was robust for both compositionally pure and mixed stands. The approach merits further investigation, particularly within the context of the increasing availability of regional-scale satellite imagery enabling composite time-series and spectral-temporal image features. [ABSTRACT FROM AUTHOR]

The effects of recent climate change are accelerating permafrost thaw, including ice‐rich landscapes of the western Canadian Arctic. However, regional drivers of permafrost slope failure in hillslopes with warm, thin permafrost remain poorly understood. Repeat satellite imagery (1984–2020) indicates rapid increases in retrogressive thaw slumps (RTSs) and deep‐seated permafrost landslides (DSPLs) since 2004, indicating a change in slope stability thresholds in an area that otherwise appeared thaw stable. The widespread occurrence of DSPL represents a contrasting geomorphic response to the RTS‐dominated ice‐rich permafrost landscapes. In this study area, RTS and DSPL occur predominantly in areas that were burned by forest fires in the 1990s, indicating a legacy thermal disturbance that preconditioned permafrost hillslopes for failure. The relations between historic fires and the later development of widespread permafrost slope failures represent an outstanding example of the complex interactions between inherited landscape sensitivity in ice‐rich terrain and ongoing climate change. Plain Language Summary: We characterize the type and nature of permafrost slope failures in the central Mackenzie Valley, NWT and find hillslope failures have increased rapidly over the past ∼15 years. This growth occurred in conjunction with increasing air temperatures and summer precipitation but the distribution of permafrost slope failures in this area is largely constrained by forest fire extents that affected the area in the 1990s. These fires have led to increased landscape sensitivity of this ice‐rich terrain through their impacts on ground temperatures. Key Points: Recent increases in permafrost mass‐wasting frequency (278%) and magnitude (602%) reveal a permafrost landscape in geomorphic transitionMore than 80% of failures occur in areas burned in the 1990sCompounding effects of legacy thermal disturbance and climate drivers of thaw likely to increase slope instability of warm permafrost [ABSTRACT FROM AUTHOR]

In the warming Arctic, retrogressive thaw slumping (RTS) has emerged as the primary thermokarst modifier of icerich permafrost slopes, raising urgency to investigate the distribution and intensification of disturbances and to determine trajectories of landscape evolution and the cascade of effects. Tracking RTS is challenging due to constraints of remote sensing products and a narrow understanding of thaw-driven landforms, however, high-resolution elevation models provide new insights into geomorphic change. Structural traits, such as RTS depth-of-thaw or volume, can be obtained through allometric scaling. To address fundamental knowledge gaps related to area-volume scaling of RTS, a suitable surface interpolation technique was first needed to model pre-disturbance topography upon which volume estimates could be based. Among 8 methods with 32 parameterizations, Natural Neighbour surface interpolation achieved the best precision in reconstructing pre-disturbed slope topography (90th percentile Root Mean Square Difference ± 1.0 m). An inverse association between RTS volume and relative volumetric error was observed, with uncertainties <10% for large slumps and <20% for small-to-medium slumps. Second, a Multisource Slump Inventory (MSI) for two study areas in the Beaufort Delta (Canada) was required to characterize the diverse range of disturbance morphologies and activity levels, which provided temporally consistent information on thaw slump affected slopes and attributes. The MSI delineation of three high-resolution hillshade DEMs (airborne stereo-imagery, LiDAR, ArcticDEM) revealed temporal and spatial trends in these multi-year, chronic mass-wasting features. For example, in the Tuktoyaktuk Coastal Plains, a +38% increase in active RTS and +69% increase in total active surface area were observed between 2004 and 2016. However, the total area of RTS did not change considerably (+3.5%) because the vast majority of active thaw slumping processes have occurred in association with past disturbances. Interpretation of thaw-driven change is thus dependent on how active RTS are defined to support disturbance inventories. Third, the pre-disturbance topographies, MSI digitizations, and DEMs were integrated to explore allometric scaling relationships between RTS area and eroded volume. The power-law model indicated non-linearity in the rates of RTS expansion and intensification across scale (adj-R2 of 0.85, n=1,522), but also revealed that elongated, shoreline RTS reflects outliers poorly represented by the modelling. This study highlights the importance of linking field-based knowledge to feature identification and the utility of high-resolution DEMs in quantifying rates of RTS erosion beyond tracking change in the planimetric area. Observations further suggested variation in depth-scaling of RTS populations is based on morphometry, terrain position, and complexity of the disturbance area, as well as the method and ontology by which slumps are inventoried. [ABSTRACT FROM AUTHOR]

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The intensification of thaw-driven mass wasting is transforming glacially conditioned permafrost terrain, coupling slopes with aquatic systems, and triggering a cascade of downstream effects. Within the context of recent, rapidly evolving climate controls on the geomorphology of permafrost terrain, we (A) quantify three-dimensional retrogressive thaw slump enlargement and describe the processes and thresholds coupling slopes to downstream systems, (B) investigate catchment-scale patterns of slope thermokarst impacts and the geomorphic implications, and (C) map the propagation of effects through hydrological networks draining permafrost terrain of northwestern Canada. Power-law relationships between retrogressive thaw slump area and volume (R2=0.90) , as well as the thickness of permafrost thawed (R2=0.63), combined with the multi-decadal (1986–2018) increase in the areal extent of thaw slump disturbance, show a 2 order of magnitude increase in catchment-scale geomorphic activity and the coupling of slope and hydrological systems. Predominant effects are to first- and second-order streams where sediment delivery, often indicated by formation of recent debris tongue deposits, commonly exceeds the transport capacity of headwater streams by orders of magnitude, signaling centennial- to millennial-scale perturbation of downstream systems. Assessment of hydrological networks indicates that thaw-driven mass wasting directly affects over 5538 km of stream segments, 889 km of coastline, and 1379 lakes in the 994 860 km2 study area. Downstream propagation of slope thermokarst indicates a potential increase in the number of affected lakes by at least a factor of 4 (n>5692) and impacted stream length by a factor of 8 (>44343 km), and it defines several major impact zones on lakes, deltas, and coastal areas. Prince of Wales Strait is the receiving marine environment for greatly increased sediment and geochemical fluxes from numerous slump-impacted hydrological networks draining Banks Island and Victoria Island. The Peel and Mackenzie rivers are globally significant conveyors of the slope thermokarst cascade, delivering effects to North America's largest Arctic delta and the Beaufort Sea. Climate-driven erosion of ice-rich slopes in permafrost-preserved glaciated terrain has triggered a time-transient cascade of downstream effects that signal the rejuvenation of post-glacial landscape evolution. Glacial legacy, ground-ice conditions, and continental drainage patterns dictate that terrestrial, freshwater, coastal, and marine environments of western Arctic Canada will be an interconnected hotspot of thaw-driven change through the coming millennia. [ABSTRACT FROM AUTHOR]

Wildfires are a dominant disturbance to boreal forests, and in North America, they typically cause widespread tree mortality. Forest fire burn severity is often measured at a plot scale using the Composite Burn Index (CBI), which was originally developed as a means of assigning severity levels to the Normalized Burn Ratio (NBR) computed from Landsat satellite imagery. Our study investigated the potential to map biophysical indicators of burn severity (residual green vegetation and charred organic surface) at very high (3 cm) resolution, using color orthomosaics and vegetation height models derived from UAV-based photographic surveys and Structure from Motion methods. These indicators were scaled to 30 m resolution Landsat pixel footprints and compared to the post-burn NBR (post-NBR) and differenced NBR (dNBR) ratios computed from pre- and post-fire Landsat imagery. The post-NBR showed the strongest relationship to both the fraction of charred surface (exponential R2 = 0.79) and the fraction of green crown vegetation above 5 m (exponential R2 = 0.81), while the dNBR was more closely related to the total green vegetation fraction (exponential R2 = 0.69). Additionally, the UAV green fraction and Landsat indices could individually explain more than 50% of the variance in the overall CBI measured in 39 plots. These results provide a proof-of-concept for using low-cost UAV photogrammetric mapping to quantify key measures of boreal burn severity at landscape scales, which could be used to calibrate and assign a biophysical meaning to Landsat spectral indices for mapping severity at regional scales. [ABSTRACT FROM AUTHOR]

Sustainable forest management requires information on the spatial distribution, composition, and structure of forests. However, jurisdictions with large tracts of noncommercial forest, such as the Northwest Territories (NWT) of Canada, often lack detailed forest information across their land base. The goal of the Multisource Vegetation Inventory (MVI) project was to create a large area forest inventory (FI) map that could support strategic forest management in the NWT using optical, radar, and light detection and ranging (LiDAR) satellite remote sensing anchored on limited field plots and airborne LiDAR data. A new landcover map based on Landsat imagery was the first step to stratify forestland into broad forest types. A modelling chain linking FI plots to airborne and spaceborne LiDAR was then developed to circumvent the scarcity of field data in the region. The developed models allowed the estimation of forest attributes in thousands of surrogate FI plots corresponding to spaceborne LiDAR footprints distributed across the project area. The surrogate plots were used as a reference dataset for estimating each forest attribute in each 30 m forest cell within the project area. The estimation was based on the k-nearest neighbour (k-NN) algorithm, where the selection of the four most similar surrogate FI plots to each cell was based on satellite, topographic, and climatic data. Wall-to-wall 30 m raster maps of broad forest type, stand height, crown closure, stand volume, total volume, aboveground biomass, and stand age were created for a ~400,000 km2 area, validated with independent data, and generalized into a polygon GIS layer resembling a traditional FI map. The MVI project showed that a reasonably accurate FI map for large, remote, predominantly non-inventoried boreal regions can be obtained at a low cost by combining limited field data with remote sensing data from multiple sources. [ABSTRACT FROM AUTHOR]

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 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. 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. [ABSTRACT FROM AUTHOR]