Extending Airborne Electromagnetic Surveys for Regional Active Layer and Permafrost Mapping with Remote Sensing and Ancillary Data, Yukon Flats Ecoregion, Central Alaska

Machine‐learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thema...

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Bibliographic Details
Published in:Permafrost and Periglacial Processes
Main Authors: Neal J. Pastick, M. Torre Jorgenson, Bruce K. Wylie, Burke J. Minsley, Lei Ji, Michelle A. Walvoord, Bruce D. Smith, Jared D. Abraham, Joshua R. Rose
Format: Article in Journal/Newspaper
Language:unknown
Subjects:
Yukon
Active layer thickness
permafrost
Alaska
Online Access:https://doi.org/10.1002/ppp.1775
Description
Summary:Machine‐learning regression tree models were used to extrapolate airborne electromagnetic resistivity data collected along flight lines in the Yukon Flats Ecoregion, central Alaska, for regional mapping of permafrost. This method of extrapolation (r = 0.86) used subsurface resistivity, Landsat Thematic Mapper (TM) at‐sensor reflectance, thermal, TM‐derived spectral indices, digital elevation models and other relevant spatial data to estimate near‐surface (0–2.6‐m depth) resistivity at 30‐m resolution. A piecewise regression model (r = 0.82) and a presence/absence decision tree classification (accuracy of 87%) were used to estimate active‐layer thickness (ALT) (

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