Abstract
Thaw slumps are one of the most dynamic features in permafrost terrain. Improved temporal and spatial resolution monitoring of slump activity is required to better characterize their dynamics over the thaw season. We assess how a ground-based stationary camera array in a time-lapse configuration can be integrated with unmanned aerial vehicle (UAV)-based surveys and Structure-from-Motion processing to monitor the activity of thaw slumps at high temporal and spatial resolutions. We successfully constructed point-clouds and digital surface models of the headwall area of a thaw slump at 6- to 13-day intervals over the summer, significantly improving the decadal to annual temporal resolution of previous studies. The successfully modeled headwall portion of the slump revealed that headwall retreat rates were significantly correlated with mean daily air temperature, thawing degree-days, and average net short-wave radiation and suggest a two-phased slump activity. The main challenges were related to strong JPEG image compression, drifting camera clocks, and highly dynamic nature of the feature. Combined with annual UAV-based surveys, the proposed methodology can address temporal gaps in our understanding of factors driving thaw slump activity. Such insight could help predict how slumps could modify their behavior under changing climate.
Highlights
The warmer and wetter northern climate during recent decades has led to increased thermokarst activity in permafrost terrain (Kokelj and Jorgenson 2013; Liljedahl et al 2016; Segal et al 2016; Fraser et al 2018)
Thaw slump activity has been investigated at regional scales using a variety of remote sensing approaches, including (i) historical air photographs acquired at decadal time-scales (Lantuit and Pollard 2005, 2008; Lacelle et al 2010; Swanson 2012); (ii) mediumresolution satellite imagery acquired at an annual time-scale, such as visual observations using SPOT or Landsat images (Kokelj et al 2017; Swanson and Nolan 2018) or tasseled cap trend analysis of Landsat image stacks (Brooker et al 2014; Fraser et al 2014); and (iii) radar interferometry performed at sub-seasonal time-scales (Short et al 2011; Zwieback et al 2018)
Thaw slump dynamics have been characterized at more local scales using (i) digital surface model (DSM) differencing of LiDAR datasets acquired at annual time-scales (Obu et al 2017); (ii) optical imagery acquired with an unmanned aerial vehicles (UAVs) at annual to sub-seasonal time-scales; (iii) high-frequency repeat terrestrial laser scanning (Barnhart and Crosby 2013); (iv) dense high-resolution TerraSAR-X time-series (Stettner et al 2018); or (v) time-lapse photography from a single ground-based stationary camera from which a qualitative index of change over the thaw season was developed (Kokelj et al 2015)
Summary
The warmer and wetter northern climate during recent decades has led to increased thermokarst activity in permafrost terrain (Kokelj and Jorgenson 2013; Liljedahl et al 2016; Segal et al 2016; Fraser et al 2018). In northwestern Canada, thousands of thaw slumps have been inventoried (Lantuit et al 2012; Lacelle et al 2015; Obu et al 2016; Segal et al 2016; Kokelj et al 2017) and these have been shown to modify the discharge of streams and rivers (Kokelj et al 2013) and the geochemical composition and sediment loads of streams and lakes (Kokelj et al 2009; Malone et al 2013; Rudy et al 2017; Tanski et al 2017) This has negatively affected aquatic ecosystems, including benthic macroinvertebrates communities (Chin et al 2016). Despite the variety of remote sensing approaches, a gap exists in the monitoring of thaw slumps (and other thermokarst landforms) at high spatio-temporal resolution, which could improve the understanding of short-term drivers modifying the features (Kokelj and Jorgenson 2013)
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