Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem
Abstract
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 »
- Authors:
-
- Brookhaven National Lab. (BNL), Upton, NY (United States). Environmental and Climate Sciences Dept.
- Brookhaven National Lab. (BNL), Upton, NY (United States). Environmental Protection Division
- Univ. of Maryland, College Park, MD (United States). Dept. of Geographical Sciences
- Univ. of Utah, Salt Lake City, UT (United States). Dept. of Geography
- NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
- 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:
- Research Org.:
- Brookhaven National Lab. (BNL), Upton, NY (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1344231
- Alternate Identifier(s):
- OSTI ID: 1396881
- Report Number(s):
- BNL-113515-2017-JA
Journal ID: ISSN 0034-4257; R&D Project: 2016-BNL-EE630EECA-Budg; KP1701000
- Grant/Contract Number:
- SC0012704; SC00112704
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- Remote Sensing of Environment
- Additional Journal Information:
- Journal Volume: 191; Journal Issue: C; Journal ID: ISSN 0034-4257
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Spectral library; Random Forests; Error matrix; Scale effect; Frequency distributions; High spatial resolution
Citation Formats
Meng, Ran, Wu, Jin, Schwager, Kathy L., Zhao, Feng, Dennison, Philip E., Cook, Bruce D., Brewster, Kristen, Green, Timothy M., and Serbin, Shawn P. Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem. United States: N. p., 2017.
Web. doi:10.1016/j.rse.2017.01.016.
Meng, Ran, Wu, Jin, Schwager, Kathy L., Zhao, Feng, Dennison, Philip E., Cook, Bruce D., Brewster, Kristen, Green, Timothy M., & Serbin, Shawn P. Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem. United States. https://doi.org/10.1016/j.rse.2017.01.016
Meng, Ran, Wu, Jin, Schwager, Kathy L., Zhao, Feng, Dennison, Philip E., Cook, Bruce D., Brewster, Kristen, Green, Timothy M., and Serbin, Shawn P. 2017.
"Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem". United States. https://doi.org/10.1016/j.rse.2017.01.016. https://www.osti.gov/servlets/purl/1344231.
@article{osti_1344231,
title = {Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem},
author = {Meng, Ran and Wu, Jin and Schwager, Kathy L. and Zhao, Feng and Dennison, Philip E. and Cook, Bruce D. and Brewster, Kristen and Green, Timothy M. and Serbin, Shawn P.},
abstractNote = {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-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)). 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.},
doi = {10.1016/j.rse.2017.01.016},
url = {https://www.osti.gov/biblio/1344231},
journal = {Remote Sensing of Environment},
issn = {0034-4257},
number = C,
volume = 191,
place = {United States},
year = {Sat Jan 21 00:00:00 EST 2017},
month = {Sat Jan 21 00:00:00 EST 2017}
}
Web of Science
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