skip to main content


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

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. Here 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-areamore » 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)). Lastly, 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.« less
ORCiD logo [1] ;  [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [2] ;  [1]
  1. Brookhaven National Lab. (BNL), Upton, NY (United States). Environmental and Climate Sciences Dept.
  2. Brookhaven National Lab. (BNL), Upton, NY (United States). Environmental Protection Division
  3. Univ. of Maryland, College Park, MD (United States). Dept. of Geographical Sciences
  4. Univ. of Utah, Salt Lake City, UT (United States). Dept. of Geography
  5. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  6. Brookhaven National Lab. (BNL), Upton, NY (United States). Environmental and Climate Sciences Dept.; State Univ. of New York (SUNY), Brockport, NY (United States). College at Brockport
Publication Date:
Report Number(s):
Journal ID: ISSN 0034-4257; R&D Project: 2016-BNL-EE630EECA-Budg; KP1701000
Grant/Contract Number:
SC0012704; SC00112704
Accepted Manuscript
Journal Name:
Remote Sensing of Environment
Additional Journal Information:
Journal Volume: 191; Journal Issue: C; Journal ID: ISSN 0034-4257
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; Spectral library; Random Forests; Error matrix; Scale effect; Frequency distributions; High spatial resolution
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1396881