Remote Sensing of Landscape Change in Permafrost Regions

• Published in: Permafrost and Periglacial Processes
• Main Authors: Jorgenson, Mark Torre, Grosse, Guido
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Wiley 2016
• Subjects: Arctic; Global warming; permafrost; Permafrost and Periglacial Processes; Thermokarst
• Online Access: https://epic.awi.de/id/eprint/41895/; https://doi.org/10.1002/ppp.1914; https://hdl.handle.net/10013/epic.48719

Amplification of global warming in Arctic and boreal regions is causing significant changes to permafrost-affected landscapes. The nature and extent of the change is complicated by ecological responses that take place across strong gradients in environmental conditions and disturbance regimes. Emerging remote sensing techniques based on a growing array of satellite and airborne platforms that cover a wide range of spatial and temporal scales increasingly allow robust detection of changes in permafrost landscapes. In this review, we summarise recent developments (2010 − 15) in remote sensing applications to detect and monitor landscape changes involving surface temperatures, snow cover, topography, surface water, vegetation cover and structure, and disturbances from fire and human activities. We then focus on indicators of degrading permafrost, including thermokarst lakes and drained lake basins, thermokarst bogs and fens, thaw slumps and active-layer detachment slides, thermal erosion gullies, thermokarst pits and troughs, and coastal erosion and flooding. Our review highlights the expanding sensor capabilities, new image processing and multivariate analysis techniques, enhanced public access to data and increasingly long image archives that are facilitating novel insights into the multi-decadal dynamics of permafrost landscapes. Remote sensing methods that appear especially promising for change detection include: repeat light detection and ranging, interferometric synthetic aperture radar and airborne geophysics for detecting topographic and subsurface changes; temporally dense analyses at high spatial resolution; and multi-sensor data fusion. Remotely sensed data are also becoming used more frequently as driving parameters in permafrost model and mapping schemes.