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Modeling and Mapping Permafrost Active Layer Thickness Using Field Measurements and Remote Sensing Techniques
Topics: Remote Sensing
, Quantitative Methods
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Keywords: Permafrost, Remote Sensing, Alaska Session Type: Virtual Paper Abstract Day: Tuesday Session Start / End Time: 3/1/2022 08:00 AM (Eastern Time (US & Canada)) - 3/1/2022 09:20 AM (Eastern Time (US & Canada)) Room: Virtual 1
Authors:
Caiyun Zhang, Florida Atlantic University
Thomas A. Douglas, U.S. Army Cold Regions Research & Engineering Laboratory
John E. Anderson, U.S. Army Geospatial Research Laboratory
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Abstract
We modeled multi-year ALT field measurements between 2014-2019 at a site in Interior Alaska using 1-m hyperspectral imaging data and an object-based ensemble approach at a local scale (1 km2), examined the efficacy of the multispectral sensor WorldView (WV)-2 for ALT estimation, and explored the potential of integrating single-date imaging data with multi-year in-situ measurements for mapping the spatial and temporal variation of ALT. Modeling results showed hyperspectral imaging was accurate for estimating ALT with a correlation coefficient (r) larger than 0.7, while application of WV-2 data produced an r around 0.4. Reasonable ALT patterns were generated, and the spatial and temporal variation of ALT was delineated between the shallowest (2015) and deepest (2019) years using hyperspectral data.
Modeling and Mapping Permafrost Active Layer Thickness Using Field Measurements and Remote Sensing Techniques
