International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire

Assessing the differenced Normalized Burn Ratio’s ability to map burn severity in the boreal forest and tundra ecosystems of Alaska’s national parks

Jennifer L. Allen A C and Brian Sorbel B

A National Park Service, Fairbanks Administrative Office, 4175 Geist Road, Fairbanks, AK 99709, USA.

B National Park Service, Alaska Regional Office, 240 W 5th Avenue, Anchorage, AK 99501, USA.

C Corresponding author. Email:

International Journal of Wildland Fire 17(4) 463-475
Submitted: 26 February 2008  Accepted: 17 March 2008   Published: 6 August 2008


Burn severity strongly influences post-fire vegetation succession, soil erosion, and wildlife populations in the fire-adapted boreal forest and tundra ecosystems of Alaska. Therefore, satellite-derived maps of burn severity in the remote Alaskan landscape are a useful tool in both fire and resource management practices. To assess satellite-derived measures of burn severity in Alaska we calculated the Normalized Burn Ratio (NBR) from pre- and post-fire Landsat TM/ETM+ data. We established 289 composite burn index (CBI) plots in or near four national park areas between 2001 and 2003 in order to compare ground-based measurements of burn severity with satellite-derived values of burn severity. Within the diverse vegetation types measured, a strong linear relationship between a differenced Normalized Burn Ratio (dNBR) and CBI for eight out of the nine fire assessments was found; R2 values ranged from 0.45 to 0.88. The variations in severity among four pre-fire vegetation types were examined and a significant difference in the average dNBR and average CBI values among the vegetation types was found. Black spruce forests overall had the strongest relationship with dNBR, while the high severity white spruce forests had the poorest fit with dNBR. Deciduous forests and tall shrub plots had the lowest average remotely sensed burn severity (dNBR), but not the lowest ground severity among the vegetation types sampled. The tundra vegetation sampled had the lowest ground severity. Finally, a significant difference was detected between initial and extended assessments of dNBR in tundra vegetation types. The results indicated that the dNBR can be used as an effective means to map burn severity in boreal forest and tundra ecosystems for the climatic conditions and fire types that occurred in our study sites.

Additional keywords: dNBR, Landsat, Picea, remote sensing, wildland fire.


Bureau of Land Management (2006) Alaska large fire history database (AKFIREHIST). Available at [Verified 8 July 2008]

Cocke AEFulé PZCrouse JE2005Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data.International Journal of Wildland Fire14189198doi:10.1071/WF04010

Cumming SG2001Forest type and wildfire in the Alberta boreal mixedwood: What do fires burn?Ecological Applications1197110doi:10.1890/1051-0761(2001)011[0097:FTAWIT]2.0.CO;2

Dissing DVerbyla D2003Spatial patterns of lightning strikes in interior Alaska and other relations to elevation and vegetation.Canadian Journal of Forest Research33770782doi:10.1139/X02-214

Duffy PAEpting JGraham JMRupp TSMcGuire AD2007Analysis of Alaskan burn severity patterns using remotely sensed data.International Journal of Wildland Fire16277284doi:10.1071/WF06034

Dyrness CTNorum RA1983The effects of experimental fires on black spruce forest floors in interior Alaska.Canadian Journal of Forest Research13879893doi:10.1139/X83-118

Epting JVerbyla DSorbel B2005Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+.Remote Sensing of Environment96328339doi:10.1016/J.RSE.2005.03.002

French NHFKasischke ESHall RJMurphy KAVerbyla DLHoy EEAllen JL2008Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results.International Journal of Wildland Fire17443462doi:10.1071/WF08007

Hely CBergeron YFlannigan MD2000Effects of stand composition on fire hazard in mixed-wood Canadian boreal forest.Journal of Vegetation Science11813824doi:10.2307/3236551

Hoy EEFrench NHFTuretsky MRTrigg SNKasischke ES2008Evaluating the potential of Landsat TM/ETM+ imagery for assessing fire severity in Alaskan black spruce forests.International Journal of Wildland Fire17500514doi:10.1071/WF08107

Hudak AT, Robichaud PR, Evans JB, Clark J, Lannom K, Morgan P, Stone C (2004) Field validation of Burned Area Reflectance Classification (BARC) products for post fire assessment. In ‘Remote sensing for field users: proceedings of the 10th Forest Service Remote Sensing Application Conference’, 5–9 April 2004, Salt Lake City, UT. On CD-ROM. (American Society for Photogrammetry and Remote Sensing: Bethesda, MD)

Johnson EA (1992) ‘Fire and vegetation dynamics: studies from North American boreal forest.’ (Cambridge University Press: New York)

Johnson EA, Miyanishi K (Eds) (2001) ‘Forest fires behavior and ecological effects.’ (Academic Press: San Diego, CA)

Johnstone JFChapin FSIII2006Effects of soil burn severity on post-fire tree recruitment in boreal forest.Ecosystems91431doi:10.1007/S10021-004-0042-X

Johnstone JFKasischke ES2005Stand-levels effects of soil burn severity on postfire regeneration in a recently burned black spruce forest.Canadian Journal of Forest Research3521512161doi:10.1139/X05-087

Kasischke ESJohnstone JF2005Variation in postfire organic layer thickness in a black spruce forest complex in interior Alaska and its effects on soil temperature and moisture.Canadian Journal of Forest Research3521642177doi:10.1139/X05-159

Kasischke ES, O’Neill KP, French NHF, Bourgeau-Chavez LL (2000) Controls on patterns of biomass burning in Alaskan boreal forest. In ‘Fire, climate change, and carbon cycling in the North American boreal forest’. (Eds ES Kasischke, BJ Stocks) pp. 173–196. (Springer: New York)

Kasischke ESWilliams DBarry D2002Analysis of the patterns of large fires in the boreal forest region of Alaska.International Journal of Wildland Fire11131144doi:10.1071/WF02023

Kasischke ES, Rupp TS, Verbyla DL (2006) Fire trends in the Alaskan boreal forest. In ‘Alaska’s Changing Boreal Forest’. (Eds FS Chapin III, MW Oswood, K Van Cleve, LA Viereck, DL Verbyla) pp. 285–301. (Oxford University Press: New York)

Key CH (2006) Ecological and sampling constraints on defining landscape fire severity. Fire Ecology 2(2), 34–59. Available at [Verified 8 July 2008]

Key CH, Benson NC (2006) Landscape Assessment (LA). In ‘FIREMON: Fire Effects Monitoring and Inventory System’. (Eds DC Lutes, RE Keane, JF Carati, CH Key, NC Benson, LJ Gangi) USDA Forest Service, Rocky Mountains Research Station General Technical Report RMRS-GTR-164-CD. p. LA-1–55. (Fort Collins, CO)

Lentile LBHolden ZASmith AMSFalkowski MJHudak ATMorgan PLewis SAGessler PEBenson NC2006Remote sensing techniques to assess active fire characteristics and post-fire effects.International Journal of Wildland Fire15319345doi:10.1071/WF05097

Miller JDThode AE2007Quantifying burn severity in a heterogeneous landscape with a relative version of delta Normalized Burn Ratio (dNBR).Remote Sensing of Environment1096680doi:10.1016/J.RSE.2006.12.006

Miller JDYool SR2002Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data.Remote Sensing of Environment82481496doi:10.1016/S0034-4257(02)00071-8

Murphy KAReynolds JHKoltun JM2008Evaluating the ability of the differenced Normalized Burn Ratio (dNBR) to predict ecologically significant burn severity in Alaskan boreal forests.International Journal of Wildland Fire17490499doi:10.1071/WF08050

National Interagency Coordination Center (2007) Fire Information – Wildland Fire Statistics. Available at [Verified 8 July 2008]

Racine CHJohnson LAViereck LA1987Patterns of vegetation recovery after tundra fires in northwestern Alaska, USA.Arctic and Alpine Research19461469doi:10.2307/1551412

Racine CJandt RMeyers CDennis J2004Tundra fire and vegetation change along a hillslope on the Seward Peninsula, Alaska, USA.Arctic and Alpine Research36110doi:10.1657/1523-0430(2004)036[0001:TFAVCA]2.0.CO;2

Roy DPBoschetti LTrigg SN2006Remote Sensing of Fire Severity: Assessing the Performance of the Normalized Burn Ratio.IEEE Geoscience and Remote Sensing Letters3(1)112116doi:10.1109/LGRS.2005.858485

Van Wagner CE (1983) Fire behavior in northern conifer forests and shrublands. In ‘The role of fire in northern circumpolar ecosystems’. (Eds RW Wein, DA MacLean) pp. 65–80. (Wiley: Chichester, UK)

van Wagtendonk JWRoot RRKey CH2004Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity.Remote Sensing of Environment92397408doi:10.1016/J.RSE.2003.12.015

Viereck LA (1983) The effects of fire in a black spruce ecosystem of Alaska and Northern Canada. In ‘The role of fire in northern circumpolar ecosystems’. (Eds RW Wein, DA MacLean) pp. 201–220. (Wiley: Chichester, UK)

Viereck LA, Dyrness CT, Batten AR, Wenzlick KJ (1992) The Alaska vegetation classification. USDA Forest Service, Pacific Northwest Research Station, General Technical Report PNW-GTR-286. (Portland, OR)

Wang GG2002Fire severity in relation to canopy composition within burned boreal mixedwood stands.Forest Ecology and Management1638592doi:10.1016/S0378-1127(01)00529-1

Yoshikawa KBolton WRRomanovsky VEFukuda MHinzman LD2002Impacts of wildfire on the permafrost in the boreal forests of interior Alaska.Journal of Geophysical Research108(NO. D1)8148doi:10.1029/2001JD000438

Zasada J (1986) Natural regeneration of trees and tall shrubs on forest sites in interior Alaska. In ‘Forest ecosystems in the Alaska taiga: a synthesis of structure and function’. (Eds K Van Cleve, FS Chapin, PW Flanagan, LA Viereck, CT Dyrness) pp. 44–73. (Springer Verlag: New York)

Zhu Z, Key C, Ohlen D, Benson N (2006) Evaluate Sensitivities of Burn-Severity Mapping Algorithms for Different Ecosystems and Fire Histories in the United States: Final Report to the Joint Fire Science Program. Available at [Verified 8 July 2008]

Export Citation Cited By (46)