Next Article in Journal
IEA Wind Task 32: Wind Lidar
Identifying and Mitigating Barriers to the Adoption of Wind Lidar
Next Article in Special Issue
Thaw Subsidence of a Yedoma Landscape in Northern Siberia, Measured In Situ and Estimated from TerraSAR-X Interferometry
Previous Article in Journal
A Spectral Mapping Signature for the Rapid Ohia Death (ROD) Pathogen in Hawaiian Forests
Previous Article in Special Issue
Remote Sensing of River Erosion on the Colville River, North Slope Alaska
Article Menu
Issue 3 (March) cover image

Export Article

Open AccessArticle

Modeling Wildfire-Induced Permafrost Deformation in an Alaskan Boreal Forest Using InSAR Observations

1
Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX 75205, USA
2
Earth Resources Observation and Science Center, United States Geological Survey, Sioux Falls, SD 57198, USA
3
United States Geological Survey, Reston, VA 20192, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(3), 405; https://doi.org/10.3390/rs10030405
Received: 22 December 2017 / Revised: 24 February 2018 / Accepted: 2 March 2018 / Published: 6 March 2018
(This article belongs to the Special Issue Remote Sensing of Dynamic Permafrost Regions)
  |  
PDF [18707 KB, uploaded 6 March 2018]
  |  

Abstract

The discontinuous permafrost zone is one of the world’s most sensitive areas to climate change. Alaskan boreal forest is underlain by discontinuous permafrost, and wildfires are one of the most influential agents negatively impacting the condition of permafrost in the arctic region. Using interferometric synthetic aperture radar (InSAR) of Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) images, we mapped extensive permafrost degradation over interior Alaskan boreal forest in Yukon Flats, induced by the 2009 Big Creek wildfire. Our analyses showed that fire-induced permafrost degradation in the second post-fire thawing season contributed up to 20 cm of ground surface subsidence. We generated post-fire deformation time series and introduced a model that exploited the deformation time series to estimate fire-induced permafrost degradation and changes in active layer thickness. The model showed a wildfire-induced increase of up to 80 cm in active layer thickness in the second post-fire year due to pore-ice permafrost thawing. The model also showed up to 15 cm of permafrost degradation due to excess-ice thawing with little or no increase in active layer thickness. The uncertainties of the estimated change in active layer thickness and the thickness of thawed excess ice permafrost are 27.77 and 1.50 cm, respectively. Our results demonstrate that InSAR-derived deformation measurements along with physics models are capable of quantifying fire-induced permafrost degradation in Alaskan boreal forests underlain by discontinuous permafrost. Our results also have illustrated that fire-induced increase of active layer thickness and excess ice thawing contributed to ground surface subsidence. View Full-Text
Keywords: permafrost; wildfire; InSAR; time series; active layer thickness; modeling permafrost; wildfire; InSAR; time series; active layer thickness; modeling
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Eshqi Molan, Y.; Kim, J.-W.; Lu, Z.; Wylie, B.; Zhu, Z. Modeling Wildfire-Induced Permafrost Deformation in an Alaskan Boreal Forest Using InSAR Observations. Remote Sens. 2018, 10, 405.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top