Figure 5 - uploaded by Stephen A. Wolfe
Content may be subject to copyright.
General trajectory of regenerating wildfires in RGB trend space from recently burned forest (1), expanding broadleaf cover (2-3) and succession towards needleleaf species (4-5). Also shown are the linear regression TC slopes averaged by age of burn with third-order polynomial curves overlaid to show the shape of the trajectories. The three TC slope values on the graphs are combined to generate the RGB colour trajectory (left) labelled as 1-5.
Source publication
Spatially detailed information on permafrost distribution and change with climate is important for land-use planning and for environmental and ecological 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...
Contexts in source publication
Context 1
... extent of vegetation recovery and post-fire successional stages are clearly visible in the RGB TC trend space shown in Figure 4. The RGB changes associated with this successional trajectory are shown in Figure 5: Recently burned forest appears dark (1), then brightens to orange and yellow with expanding broadleaf cover (2-3). Gradual forest crown closure and succession towards needle-leaf species results in stands that appear in blue (4-5). ...
Context 2
... values are typically treated as regression outliers and therefore recent disturbances are not normally visible in the trend images. It is likely that variation in TC slope trajectories among fires with similar burn dates ( Figure 5 right) is related to differences in burn severity, regeneration rates, and species composition of forest stands during succession [33,34]. Although fires with similar ages have similar TC slope trajectories, the interpretation of linear trajectories is complicated by the fact that the overall spectral trajectory of burned forest through vegetation succession is non-linear [35]. ...
Context 3
... lines are widely detectable in the trend imagery, despite having an average width less than 10 m, or one-third of the Landsat resolution. Strong spectral contrast produced by vigorous regeneration of broadleaf vegetation within seismic lines [57] is sufficient to make them visible throughout region 1. Figure 15 shows a highly dynamic region surrounding the town of Norman Wells, situated along the Mackenzie River. Here, a network of seismic lines is visible, along with many of the other change types discussed previously, including regenerating fires from 1955 to 2003, shifting river sand bars, draining lakes, and forest succession along the old Canol Road and pipeline built during the Second World War to transport oil to the Yukon. ...
Context 4
... of TC trend imagery north of Yellowknife showing abandoned mining sites with regeneration (teal) and the footprint of recently developed diamond mines (red and dark blue). Figure 15. TC trend image for area surrounding Norman Wells, which has been heavily developed for oil and gas during the past 60 years. ...
Similar publications
Abstract. 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 pro...
The time-domain electromagnetic (TDEM) method provides virtually the only surface
geophysical technique suitable for interpreting deep permafrost conditions. This report describes
profiles collected in early spring in a transitional area of the Mackenzie Delta, Arctic Canada, with
differing permafrost conditions and surficial geology. These data...
Citations
... According to Obu et al. [415], 22% of exposed land area on the Northern Hemisphere are underlain by permafrost, which is roughly 2 × 10 6 km 2 less compared to previous estimations. Both the circumpolar MAGT and permafrost distribution maps are openly available as listed in Table 4. Another study by Zhang et al. [220] mapped the distribution of permafrost on a 20 m resolution scale for an area covering ∼8836 km 2 in the Canadian Northwest Territories. The incorporation of satellite derived land cover maps hereby enabled Zhang et al. [220] to map permafrost on a higher spatial resolution compared to existing maps. ...
... Both the circumpolar MAGT and permafrost distribution maps are openly available as listed in Table 4. Another study by Zhang et al. [220] mapped the distribution of permafrost on a 20 m resolution scale for an area covering ∼8836 km 2 in the Canadian Northwest Territories. The incorporation of satellite derived land cover maps hereby enabled Zhang et al. [220] to map permafrost on a higher spatial resolution compared to existing maps. However, the coarser resolution of available soil and ground condition data were a major limitation for high-resolution mapping of frozen ground [220]. ...
... The incorporation of satellite derived land cover maps hereby enabled Zhang et al. [220] to map permafrost on a higher spatial resolution compared to existing maps. However, the coarser resolution of available soil and ground condition data were a major limitation for high-resolution mapping of frozen ground [220]. ...
Climate change and associated Arctic amplification cause a degradation of permafrost which in turn has major implications for the environment. The potential turnover of frozen ground from a carbon sink to a carbon source, eroding coastlines, landslides, amplified surface deformation and endangerment of human infrastructure are some of the consequences connected with thawing permafrost. Satellite remote sensing is hereby a powerful tool to identify and monitor these features and processes on a spatially explicit, cheap, operational, long-term basis and up to circum-Arctic scale. By filtering after a selection of relevant keywords, a total of 325 articles from 30 international journals published during the last two decades were analyzed based on study location, spatio-temporal resolution of applied remote sensing data, platform, sensor combination and studied environmental focus for a comprehensive overview of past achievements, current efforts, together with future challenges and opportunities. The temporal development of publication frequency, utilized platforms/sensors and the addressed environmental topic is thereby highlighted. The total number of publications more than doubled since 2015. Distinct geographical study hot spots were revealed, while at the same time large portions of the continuous permafrost zone are still only sparsely covered by satellite remote sensing investigations. Moreover, studies related to Arctic greenhouse gas emissions in the context of permafrost degradation appear heavily underrepresented. New tools (e.g., Google Earth Engine (GEE)), methodologies (e.g., deep learning or data fusion etc.) and satellite data (e.g., the Methane Remote Sensing LiDAR Mission (Merlin) and the Sentinel-fleet) will thereby enable future studies to further investigate the distribution of permafrost, its thermal state and its implications on the environment such as thermokarst features and greenhouse gas emission rates on increasingly larger spatial and temporal scales.
... 24 The resultant landscape is a mosaic of bedrock outcrop dominated by jack pine, and lacustrine sediments hosting permafrost and dominated by black spruce, mixed spruce, and deciduous forests. 6,48 The forested terrain is interspersed with small areas of white spruce, black spruce-dominated peatlands, and treeless or sparsely forested fens. 43 Microtopographical relief is often present in permafrost-affected forests where freeze-thaw and frost heave give rise to turbic cryosols and earth hummocks. ...
The acceleration of permafrost thaw due to warming, wetting, and disturbance is altering circumpolar landscapes. The effect of thaw is largely determined by ground ice content in near‐surface permafrost, making the characterization and prediction of ground ice content critical. Here we evaluate the spatial and stratigraphic variation of near‐surface ground ice characteristics in the dominant forest types in the North Slave region near Yellowknife, Northwest Territories, Canada. Physical variation in the permafrost was assessed through cryostructure, soil properties, and volumetric ice content, and relationships between these parameters were determined. Near‐surface ground ice characteristics were contrasted between forest types. In black spruce forests the top of the permafrost was ice‐rich and characterized by lenticular and ataxitic cryostructures, indicating the presence of an intermediate layer. Most white spruce/birch forests showed similar patterns; however, an increase in the active layer thickness and permafrost thaw at some sites have eradicated the transition zone, and the large ice lenses encountered at depth reflect segregated ground ice developed during initial downward aggradation of permafrost. Our findings indicate that white spruce/birch terrain will be less sensitive than black spruce forests to near‐surface permafrost thaw. However, if permafrost thaws completely, white spruce/birch terrain will probably be transformed into wetland–thaw lake complexes due to high ground ice content at depth.
... Other studies that conducted permafrost mapping and its degradation assessment due to climate change were by Jorgenson et al. (2006), Zhang et al. (2014), andWright et al. (2003). ...
Permafrost occupies about a quarter of the northern hemisphere land with 25.5 million ha. Global warming and anthropogenic activities affect the dynamics of permafrost. Snow and permafrost, in turn, serve as an indicator of climate change and human activity disturbance. The dynamics of permafrost are often estimated using interferometric Synthetic Aperture Radar (InSAR) methods. However, acquiring and processing InSAR images is costly and computation intensive. Due to various spectral variables and indices available from optical images, Landsat satellite images that are free-downloadable provide the potential for studying and monitoring changes of permafrost.
The overall objective of this study was to explore the use of optical images as a cost-effective method to map permafrost in the Donnelly Training Area (DTA) - an installation located in Alaska. First, Landsat 8 OLI/TIRS images from January 2014 to December 2018 were used to calculate various remote sensing variables. The variables included Land Surface Temperature (LST), albedo, Soil Moisture Index (SMI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Snow Index (NDSI), Normalized Difference Built-up Index (NDBI), Normalized Difference Water Index (NDWI), Simple Ratio (SR), Soil Adjusted Vegetation Index (SAVI), Normalized Burn Ratio (NBR), Triangular Vegetation Index(TVI), Visible Atmospherically Resistant Index (VARI), and Active Layer Thickness (ALT). Moreover, elevation, slope, and aspect were obtained from a digital elevation model (DEM). The variables
ii
were used to estimate the probabilities of permafrost presence (POP) for DTA. The logistic and linear models were respectively selected and optimized based on logistic and linear stepwise regression for the estimation of and ALT. A total of 414 field observations that were collected from 1994 to 2012 were utilized for the validation of models.
The results showed that the POP in DTA was significantly affected by all the factors except aspect and EVI. The factor that was most correlated with ln((1-POP)/POP) was elevation, then NDVI, albedo, ALT, LST, NDWI, NDSI, slope, TVI, RSR, SMI, NDBI, SR, SAVI, NBR and VARI. A total of six prediction models were obtained. The elevation, NDVI, LST, TVI, ALT, SLOPE, RSR, SMI, NBR, and NDSI were finally chosen in the best model 5.6 with the smallest relative root mean square error (RMSE) and Akaike information criterion (AIC). The albedo used in previous studies was excluded in the final model, implying that the albedo was not critical to the prediction of POP. In addition to the previously used elevation, NDVI, and SMI, other predictors including LST, TVI, ALT, SLOPE, RSR, NBR and NDSI could not be ignored in the prediction of POP. The model generated reasonable spatial distribution of POP in which POP had greater values in the east, northeast, north and northwest parts and smaller in the south and southwest parts. Except for NDVI, NDWI, NDSI, aspect and RSR, moreover, all other predictors showed significant contributions to the prediction of ALT. The SMI, ELEVATION, SAVI, NDBI, SLOPE, LST, SR, EVI, VARI and TVI were finally selected in the best model 5.14 with the smallest relative RMSE and AIC. The ALT highly varied over the study area with the spatial patterns inversely consistent with those of POP.
The results are essential for the governments, policymakers, and other concerned stakeholders to estimate the degradation of permafrost in DTA and minimize the risk of policy decision-making for land use management and planning. This study will help to understand the
iii
global climate change, changing ecosystems, increasing concentration in the atmosphere, and human activity-induced disturbance.
... However, on larger scales and in places where rock glaciers do not exist other elements can be used, though with greater uncertainty and inaccuracy in the delineation of existing frozen grounds. Therefore, different indicators based on fieldwork, monitoring and remote sensing permit detailed maps of frozen ground distribution to be made in relatively small areas (Zhang et al., 2014). ...
... The most common permafrost maps are based on a spatial classification of permafrost (continuous, discontinuous and sporadic) but also in the degree of certainty about its existence (possible and probable, Table 2) and combine field observations and semi-empirical models (Keller, 1992;Hoetzle et al., 1993;Keller et al., 1998;Heginbottom, 2002;Boeckli et al., 2012;Zhang et al., 2014;Bockheim, 2015). Alpine permafrost distribution can be statistically differentiated as probable or possible permafrost (Hoetzle et al., 1993;Keller et al., 1998;Heginbottom, 2002). ...
This paper shows the creation of a map of frozen ground potential for the Tucarroya valley in Ordesa National Park. To create this map, it was necessary to combine the identified landforms associated to the presence of frozen ground by fieldwork, ground temperature data continuously recorded during two years by automatic loggers, a Basal Temperature Survey (BTS), and predictor variables derived from a high resolution Digital Elevation Model (DEM). Four environments have been differentiated: unfrozen ground, seasonal frozen ground, possible permafrost and probable permafrost. The map confirms a very limited variety and extension of permafrost, above 2700 m a.s.l. on gentle and shadowed slopes. Seasonal frozen ground is the most common thermal regime, as it can be developed above 2500 m a.s.l. Snow-pack duration and thickness tightly control the duration of frozen ground and the freezing-thawing cycles. Frost activity and unfrozen ground is restricted from 2570 to 2750 m a.s.l.
... Permafrost is present in the widespread forestcovered fine-grained (glacio) lacustrine sediments and within peatlands, but not beneath bedrock outcrops, resulting in discontinuous permafrost distribution (Morse et al. 2016). Permafrost temperatures are in thermal disequilibrium with contemporary climate, which has warmed since at least the mid-1960s ( Morse et al. 2016), and permafrost extent is expected to decline (Zhang et al. 2014(Zhang et al. , 2015. Thermokarst is widespread in the region and is associated with fine-grained deposits . ...
In the North Slave region, permafrost developed in a time transgressive manner throughout the Holocene with lake-level recession, giving rise to the Great Slave Lowland and Great Slave Upland ecoregions of the subarctic Canadian Shield. Thermokarst in the region is commonly associated with degradation of numerous ice-cored mounds called lithalsas. Here we use site descriptions and air photos to document the distinctive geomorphic signatures associated with degrading lithalsas and develop a conceptual model for lithalsa degradation in this region, which builds upon an earlier model of lithalsa development. Physical degradation of lithalsas is dominated by two main processes: (i) subsidence indicated by the common occurrence of ponded water with partially submerged standing dead trees, and (ii) colluviation of thawed sediments toward the lithalsa margin that results in a rampart. According to these diagnostic criteria, satellite image analysis suggests that lithalsas were more widespread at higher elevations in the past, but the majority have degraded. This explains, in part, the reduction of lithalsa abundance with increasing elevation. The results suggest that lithalsas are vulnerable to thaw. Following from our observations and findings, we develop a conceptual model of lithalsa degradation. It suggests that soil hysteresis effects would likely prevent re-initiation of lithalsa formation if permafrost were to re-aggrade in the future.
... Such an increase can warm the ground through energy exchange at the surface and result in significant permafrost degradation. The distribution and changes of permafrost with climate is necessary for infrastructure development, ecological and environmental assessments, and climate system modeling (Luo et al., 2017;Luo et 15 al., 2012;Zhang et al., 2014). ...
... Permafrost is a subsurface feature that is difficult to directly observe and map. These methods integrate the effects of air and ground temperatures, topography, vegetation, and soil properties to map permafrost spatially and explicitly (Gisnå s et al., 2013;Jafarov et al., 2012;Zhang et al., 2014). Weather observation data, including air and soil temperatures with different depths, are the 15 main inputs for single-point simulation. ...
... The probability of permafrost occurrence and most likely permafrost conditions are determined by computing the 16 indices. Although PIC quantitatively integrates most of these indices based on previous studies (Jafarov et al., 2012;Nelson et al., 1997;Riseborough 15 et al., 2008;Smith and Riseborough, 2010;Zhang et al., 2005;Zhang et al., 2014), it still has several limitations. ...
An R package permafrost indices computing (PIC) was developed, which integrates meteorological observations, remote sensing data, and field measurements to compute the factors or indices of permafrost and seasonal frozen soil. At present, 16 temperature/depth-related indices are integrated into the R package PIC to estimate the possible change trends of frozen soil in the Qinghai–Tibet Plateau (QTP). These indices include the mean annual air temperature, mean annual ground surface temperature, mean annual ground temperature, seasonal thawing/freezing n factor (nt/nf), thawing/freezing degree-days of air and ground surface (DDTa/DDTs/DDFa/DDFs), temperature at the top of the permafrost, active layer thickness, and maximum seasonal freeze depth. The PIC package supports two computational modes, namely, the stations and region calculation that enables statistical analysis and intuitive visualization on the time series and spatial simulations. Over 10 statistical methods were adopted to evaluate these indices in stations, and a sequential Mann-Kendall trend test and spatial trend method were adopted. Multiple visual manners display the temporal and spatial variabilities on the stations and region. The data sets of 52 weather stations and a central region of QTP were prepared and simulated to evaluate the temporal–spatial change trends of permafrost with the climate. Simulation results show extensive permafrost degradation in QTP, and the temporal–spatial trends of the permafrost conditions in QTP were consistent with those of previous studies. The PIC package will serve engineering applications and can be used to assess the impact of climate change on permafrost.
... surface conditions on permafrost. 13 Zhao et al. 14 comprehensively evaluated several simple models and found that they significantly overestimated permafrost distribution on the QTP. Previous studies have consistently called for the application of physically explicit models, such as a land surface model (LSM), to fully account for local factors and accurately simulate permafrost evolution. ...
... 14,15 Process-based physical models provide more sophisticated capabilities to deal with localized effects and the water and energy exchanges at the ground surface. 13 Recently, LSMs have been used to simulate the properties and evolution of permafrost on the QTP (eg, 16,17 ). However, these studies are typically restricted to specific sites or small areas because the data and parameters required for the entire QTP are difficult to obtain. ...
Accurate information on the distribution of permafrost and its thermal and hydrological properties is critical for environmental management and engineering development. This study modeled the current state of permafrost on the Qinghai-Tibet Plateau (QTP), including the spatial distribution of permafrost, active-layer thickness (ALT), mean annual ground temperature (MAGT), depth of zero annual amplitude (DZAA) and ground-ice content using an improved Noah land surface model (LSM). The improved model was examined at a typical permafrost site and then applied to the entire QTP using existing gridded meteorological data and newly developed soil data. The simulated permafrost distribution and properties were validated against existing permafrost maps in three representative survey areas and with measurements from 54 boreholes. The results indicate that the Noah LSM with augmented physics and proper soil data support can model per-mafrost over the QTP. Permafrost was simulated to underlie an area of 1.113 × 10 6 km 2 in 2010, accounting for 43.8% of the entire area of the QTP. The modeled regional average ALT and MAGT were 3.23 m and −1.56°C, respectively. Spatially, MAGT increases and DZAA becomes shallower from north to south. Thermally unstable permafrost (MAGT above −0.5°C) is predominant , accounting for 38.75% of the whole permafrost area on the QTP. Ice-rich permafrost was mainly simulated around lakes across the north-central QTP. KEYWORDS hydrological and thermal properties, land surface model, permafrost distribution, Qinghai-Tibet Plateau
... As noted earlier, the occurrence of extensive discontinuous permafrost in the Great Slave Lowland is attributed primarily to the presence of permafrost beneath forested areas underlain by unconsolidated fine-grained sediments and to localized peatlands. Notably, Zhang et al. (2014) have predicted that permafrost extent in this region could be reduced to only about 2.5 % by the end of the century, with permafrost occurring only within peatlands. This projection does not account for the substantive latent heat effect associated with ice-rich permafrost, which may aid to reduce the rate of thaw. ...
The Great Slave Lowland of the Taiga Shield is an 11,000 km2 low-elevation granitic bedrock plain along the north shore of Great Slave Lake, Northwest Territories. It is characterized by a mosaic of coniferous and deciduous forest cover, wetlands, sparsely vegetated bedrock outcrops, and peatlands. The region was glaciated until about 13,000 years ago and then inundated by Glacial Lake McConnell and by ancestral Great Slave Lake, which gradually declined towards the present lake elevation. Consequently, fine-grained glacilacustrine and nearshore lacustrine sediments are broadly distributed across the region. Permafrost is widespread within forest-covered sediments and peatlands, but is not sustained beneath bedrock outcrops, leading to an extensive, but discontinuous, permafrost distribution. Lithalsas, which are permafrost mounds up to 8 m in height and several hundred metres in length, are also abundant. These form by ice segregation within mineral soil, as permafrost aggrades into the fine-grained sediments following lake level recession. Lithalsas are most common within the first few tens of metres above the present level of Great Slave Lake, indicating that many are late Holocene in age and some <1000 years. These elevated surfaces favour the establishment of deciduous forests with thin organic ground cover and with mean annual ground temperatures typically between −0.5 and −1.5 °C. With annual mean air temperatures consistently warming since the 1940s, this terrain is vulnerable to thawing and subsidence, with impacts on the ecology, hydrology, and population of the region.
... For example, while a recent expert assessment established that increased fire activity and changes in water balance will have significant impacts on SOC that would turn these permafrost environments into a carbon source (Abbott et al., 2016), there is little consensus on the net offset due to temperature-driven vegetation uptake of CO 2 , which counteracts certain carbon release processes (Voigt et al., 2016;Abbott et al., 2016). To accurately address the NHL's contribution to the global carbon cycle, not only the magnitude of the C reservoir but crucially the extent of permafrost and the rate of permafrost thaw need to be determined and quantified on the landscape scale (Zhang et al., 2014). ...
Remotely-sensed climate data records (CDRs) provide a basis for spatially distributed global climate model (GCM) inputs and validation methods. GCMs can take advantage of land surface models (LSMs), which aim to resolve surface energy, water and carbon budgets and hence these LSMs present important boundary conditions at the land-atmosphere interface. Pertinently, satellite data assimilation approaches are essential for improved land surface modelling for northern high latitudes ecosystems where permafrost degradation is reported to be ongoing. Permafrost, however, is an Essential Climate Variable (ECV) that cannot directly be monitored from space.
Here, we advocate that CDRs, such as those compiled under the European Space Agency (ESA) Climate Change Initiative (CCI) programme, may be used in combination with permafrost models to improve our understanding of permafrost extent and degradation in a changing climate system. We describe the current types of remotely-sensed surface feature products that are widely used as indicators for permafrost related features. Furthermore, we highlight issues of using these site-specific permafrost proxies related to spatial scale, as well as the uncertainties in establishing present-day permafrost extent itself.
Our assessment of the key ECVs that impact on permafrost, demonstrates how models that incorporate EO CDRs have the potential to boost our knowledge of permafrost conditions through better parametrisation of the thermal regime of permafrost soils.
... For example, the largest difference in estimates for the boreal region were between DOS-TEM and the GIPL model, where DOS-TEM accounts for the effect of fire on the organic layer and the consequences on the soil thermal and hydrological regimes and the GIPL model does not. The inclusion of remote sensing information into process models has remained limited, but has potential for improving historical simulations of permafrost distribution and response to disturbance (National Research Council 2014, Zhang et al. 2014. Likewise, empirical models that incorporate remote sensing information have been shown to estimate postfire permafrost conditions with high fidelity (Minsley et al. 2016). ...
Modern climate change in Alaska has resulted in widespread thawing of permafrost, increased fire activity, and extensive changes in vegetation characteristics that have significant consequences for socio-ecological systems. Despite observations of the heightened sensitivity of these systems to change, there has not been a comprehensive assessment of factors that drive ecosystem changes throughout Alaska. Here we present research that improves our understanding of the main drivers of the spatiotemporal patterns of carbon dynamics using in situ observations, remote sensing data, and an array of modeling techniques. In the last 60 years, Alaska has seen a large increase in mean annual air temperature (1.7 °C), with the greatest warming occurring over winter and spring. Warming trends are projected to continue throughout the 21st century and will likely result in landscape-level changes to ecosystem structure and function. Wetlands, mainly bogs and fens, which are currently estimated to cover 12.5% of the landscape, strongly influence exchange of methane between Alaska's ecosystems and the atmosphere and are expected to be affected by thawing permafrost and shifts in hydrology. Simulations suggest the current proportion of near-surface (within 1 m) and deep (within 5 m) permafrost extent will be reduced by 9-74% and 33-55% by the end of the 21st century, respectively. Since 2000, an average of 678,595 ha/yr was burned, more than twice the annual average during 1950-1999. The largest increase in fire activity is projected for the boreal forest, which could result in a reduction in late-successional spruce forest (8-44%) and an increase in early-succession deciduous forest (25-113%) that would mediate future fire activity and weaken permafrost stability in the region. Climate warming will also affect vegetation communities across arctic regions, where the coverage of deciduous forest could increase (223-620%), shrub tundra may increase (4-21%), and graminoid tundra might decrease (10-24%). This study sheds light on the sensitivity of Alaska's ecosystems to change that has the potential to significantly affect local and regional carbon balance, but more research is needed to improve estimates of land-surface and subsurface properties, and to better account for ecosystem dynamics affected by a myriad of biophysical factors and interactions. This article is protected by copyright. All rights reserved.
