Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA
Melanie K. Vanderhoof
A B , Clifton Burt A and Todd J. Hawbaker A
+ Author Affiliations
- Author Affiliations
A US Geological Survey, Geosciences and Environmental Change Science Center, PO Box 25046, DFC, MS980, Denver, CO 80225, USA.
B Corresponding author. Email: mvanderhoof@usgs.gov
International Journal of Wildland Fire 27(10) 699-713 https://doi.org/10.1071/WF17177
Submitted: 20 December 2017 Accepted: 21 August 2018 Published: 7 September 2018
Abstract
Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011–2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, Worldview-3 and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery, resprouting vigorously within 1 year, whereas 4 years post-fire, areas previously dominated by conifers were divided approximately equally between being classified as dominated by quaking aspen saplings with herbaceous species in the understorey or minimally recovered. Relative to using a pixel-based Normalised Difference Vegetation Index (NDVI), our object-based approach showed higher rates of revegetation. High-resolution imagery can provide an effective means to monitor post-fire site conditions and complement more prevalent efforts with moderate- and coarse-resolution sensors.
Additional keywords: burned area, GeoEye-1, Landsat, QuickBird-2, revegetation, severity, Wildfire, Worldview-2, Worldview-3.
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