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

Neal J. Pastick, M. Torre Jorgenson, Bruce K. Wylie, Burke J. Minsley, Lei Ji, Michelle A. Walvoord, Bruce D. Smith, Jared D. Abraham and Joshua R. Rose

Permafrost and Periglacial Processes, 2013, vol. 24, issue 3, 184-199

Abstract: 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) (

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/ppp.1775

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:perpro:v:24:y:2013:i:3:p:184-199

Access Statistics for this article

More articles in Permafrost and Periglacial Processes from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().