Remote sensing-based statistical approach for defining drained lake basins in a continuous Permafrost region, North Slope of Alaska

• Main Authors: Bergstedt, Helena, Jones, Benjamin M., Hinkel, Kenneth M, Farquharson, Louise, Gaglioti, Benjamin V., Parsekian, Andrew D., Kanevskiy, Mikhail, Ohara, Noriaki, Breen, Amy L., Rangel, Rodrigo C., Grosse, Guido, Nitze, Ingmar
• Format: Text
• Language: unknown
• Published: Digital Commons @ Michigan Tech 2021
• Subjects: Alaska; Arctic; ArcticDEM; Drained Lake basins; Lake drainage; Lakes; Landsat; North Slope; Permafrost; Tasseled Cap; Thermokarst; Department of Geological and Mining Engineering and Sciences; Geological Engineering; Mining Engineering; north slope; permafrost
• Online Access: https://digitalcommons.mtu.edu/michigantech-p/15108; https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=34410&context=michigantech-p

Lake formation and drainage are pervasive phenomena in permafrost regions. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. In this study, we present a novel and scalable remote sensing-based approach to identifying DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. We validated this first North Slope-wide DLB data product against several previously published sub-regional scale datasets and manually classified points. The study area covered >71,000 km2, including a >39,000 km2 area not previously covered in existing DLB datasets. Our approach used Landsat-8 multispectral imagery and ArcticDEM data to derive a pixel-by-pixel statistical assessment of likelihood of DLB occurrence in sub-regions with different permafrost and periglacial landscape conditions, as well as to quantify aerial coverage of DLBs on the North Slope of Alaska. The results were consistent with previously published regional DLB datasets (up to 87% agreement) and showed high agreement with manually classified random points (64.4–95.5% for DLB and 83.2– 95.4% for non-DLB areas). Validation of the remote sensing-based statistical approach on the North Slope of Alaska indicated that it may be possible to extend this methodology to conduct a comprehensive assessment of DLBs in pan-Arctic lowland permafrost regions. Better resolution of the spatial distribution of DLBs in lowland permafrost regions is important for quantitative studies on landscape diversity, wildlife habitat, permafrost, hydrology, geotechnical conditions, and high-lat-itude carbon cycling.