Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

REMOTE SENSING OF ENVIRONMENT

卷:191

Article

Meng, Ran¹  Wu, Jin¹  Schwager, Kathy L.²  Zhao, Feng³  Dennison, Philip E.⁴  Cook, Bruce D.⁵  Brewster, Kristen^1,6  Green, Timothy M.²  Serbin, Shawn P.¹ 

[1] Brookhaven Natl Lab, Environm & Climate Sci Dept, Bldg 490A, Upton, NY 11973 USA

[2] Brookhaven Natl Lab, Environm Protect Div, Bldg 860, Upton, NY 11973 USA

[3] Univ Maryland, Dept Geog Sci, 1165 Lefrak Hall, College Pk, MD 20742 USA

[4] Univ Utah, Dept Geog, 332 S 1400 E,Rm 217, Salt Lake City, UT 84112 USA

[5] NASA, Biospher Sci Branch, Goddard Space Flight Ctr, Code 618, Greenbelt, MD 20742 USA

[6] SUNY Coll Brockport, Dept Environm Sci & Biol, Brockport, NY 14420 USA

关键词: Spectral library;    Random Forests;    Error matrix;    Scale effect;    Frequency distributions;    High spatial resolution;   

DOI  :  10.1016/j.rse.2017.01.016

来源: Elsevier

【 摘 要 】

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the <30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems. (C) 2017 Elsevier Inc. All rights reserved.

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