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

Is burn severity related to fire intensity? Observations from landscape scale remote sensing

Heather Heward A , Alistair M. S. Smith A D , David P. Roy B , Wade T. Tinkham A , Chad M. Hoffman C , Penelope Morgan A and Karen O. Lannom A
+ Author Affiliations
- Author Affiliations

A Department of Forest, Rangeland, and Fire Sciences, University of Idaho, Moscow, ID 83844, USA.

B Geographic Information Science Center of Excellence, South Dakota State University, Brookings, SD 57007, USA.

C Department of Forest and Rangeland Stewardship, Colorado State University, Fort Collins, CO 80523, USA.

D Corresponding author. Email: alistair@uidaho.edu

International Journal of Wildland Fire 22(7) 910-918 https://doi.org/10.1071/WF12087
Submitted: 2 June 2012  Accepted: 19 March 2013   Published: 23 July 2013

Abstract

Biomass burning by wildland fires has significant ecological, social and economic impacts. Satellite remote sensing provides direct measurements of radiative energy released by the fire (i.e. fire intensity) and surrogate measures of ecological change due to the fire (i.e. fire or burn severity). Despite anecdotal observations causally linking fire intensity with severity, the nature of any relationship has not been examined over extended spatial scales. We compare fire intensities defined by Moderate Resolution Imaging Spectroradiometer Fire Radiative Power (MODIS FRP) products with Landsat-derived spectral burn severity indices for 16 fires across a vegetation structure continuum in the western United States. Per-pixel comparison of MODIS FRP data within individual fires with burn severity indices is not reliable because of known satellite temporal and spatial FRP undersampling. Across the fires, 69% of the variation in relative differenced normalized burn ratio was explained by the 90th percentile of MODIS FRP. Therefore, distributional MODIS FRP measures (median and 90th-percentile FRP) derived from multiple MODIS overpasses of the actively burning fire event may be used to predict potential long-term negative ecological effects for individual fires.


References

Adams HD, Luce CD, Breshears DD, Allen CD, Weiler M, Hale VC, Smith AMS, Huxman TE (2012) Ecohydrological consequences of drought- and infestation-triggered tree die-off: insights and hypotheses. Ecohydrology 5, 145–159.
Ecohydrological consequences of drought- and infestation-triggered tree die-off: insights and hypotheses.CrossRef |

Alexander ME (1982) Calculating and interpreting forest fire intensities. Canadian Journal of Botany 60, 349–357.
Calculating and interpreting forest fire intensities.CrossRef |

Archibald S, Scholes RJ, Roy DP, Roberts G, Boschetti L (2010) Southern African fire regimes as revealed by remote sensing. International Journal of Wildland Fire 19, 861–878.
Southern African fire regimes as revealed by remote sensing.CrossRef |

Borchert MI, Odion DC (1995) Fire intensity and vegetation recovery in chaparral: a review. In ‘Bushfire in California Wildlands: Ecology and Resource Management’. (Eds JE Keeley, T Scott) pp. 91–100. (International Association of Wildland Fire: Fairfield, WA)

Boschetti L, Roy DP (2009) Strategies for the fusion of satellite fire radiative power with burned area data for fire radiative energy derivation. Journal of Geophysical Research 114, D20302
Strategies for the fusion of satellite fire radiative power with burned area data for fire radiative energy derivation.CrossRef |

Byram GM (1959) Combustion of forest fuels. In ‘Fire: Control and Use’. (Ed. KP Davis) pp. 61–89. (McGraw Hill: New York)

Cocke AE, Fule PZ, Crouse JE (2005) Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data. International Journal of Wildland Fire 14, 189–198.
Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data.CrossRef |

Conard SG, Sukhinin AI, Stocks BJ, Cahoon DR, Davidenko EP, Ivanova GA (2002) Determining effects of area burned and fire severity on carbon cycling and emissions in Siberia. Climatic Change 55, 197–211.
Determining effects of area burned and fire severity on carbon cycling and emissions in Siberia.CrossRef | 1:CAS:528:DC%2BD38XntVKqt7o%3D&md5=1bff48c006825ab887336aadd29696d2CAS |

Daniel TC, Carroll MS, Moseley C, Raish C (Eds) (2007) ‘People, Fire and Forests: a Synthesis of Wildfire Social Science’. (Oregon State University Press: Corvallis, OR)

De Santis A, Chuvieco E (2009) GeoCBI: a modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data. Remote Sensing of Environment 113, 554–562.
GeoCBI: a modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data.CrossRef |

Disney MI, Lewis P, Gomez-Dans J, Roy D, Wooster MJ, Lajas D (2011) 3D radiative transfer modelling of fire impacts on a two-layer savanna system. Remote Sensing of Environment 115, 1866–1881.
3D radiative transfer modelling of fire impacts on a two-layer savanna system.CrossRef |

Drewa PB (2003) Effects of fire season and intensity on Prosopis glandulosa Torr. var. glandulosa. International Journal of Wildland Fire 12, 147–157.
Effects of fire season and intensity on Prosopis glandulosa Torr. var. glandulosa.CrossRef |

Eidenshink J, Schwind B, Brewer K, Zhu Z, Quayle B, Howard S (2007) A project for monitoring trends in burn severity. Journal of Fire Ecology 3, 3–21.
A project for monitoring trends in burn severity.CrossRef |

Freeborn PH, Wooster MJ, Min Hao W, Ryan CA, Nordgren BL, Baker AP, Ichoku C (2008) Relationships between energy release, fuel mass loss, and trace gas and aerosol emissions during laboratory biomass fires Journal of Geophysical Research 113, D01301
Relationships between energy release, fuel mass loss, and trace gas and aerosol emissions during laboratory biomass firesCrossRef |

Freeborn PH, Wooster MJ, Roberts G (2011) Addressing the spatiotemporal sampling design of MODIS to provide estimates of the fire radiative energy emitted from Africa. Remote Sensing of Environment 115, 475–489.
Addressing the spatiotemporal sampling design of MODIS to provide estimates of the fire radiative energy emitted from Africa.CrossRef |

French NHF, Kasischke ES, Hall RJ, Murphy KA, Verbyla DL, Hoy EE, Allen JL (2008) Using 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 Fire 17, 443–462.
Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results.CrossRef |

Giglio L (2010) ‘MODIS Collection 5 Active Fire product User’s Guide Version 2.4’. (University of Maryland: College Park, MD)

Giglio L, Kendall JD, Justice CO (1999) Evaluation of global fire detection algorithms using simulated AVHRR infrared data. International Journal of Remote Sensing 20, 1947–1985.
Evaluation of global fire detection algorithms using simulated AVHRR infrared data.CrossRef |

Giglio L, Descloitres J, Justice CO, Kaufman YJ (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment 87, 273–282.
An enhanced contextual fire detection algorithm for MODIS.CrossRef |

Giglio L, Randerson JT, van der Werf GR, Kasibhatla PS, Collatz GJ, Morton DC, DeFries RS (2010) Assessing variability and long-term trends in burned area by merging multiple satellite fire products. Biogeosciences 7, 1171–1186.
Assessing variability and long-term trends in burned area by merging multiple satellite fire products.CrossRef |

Goetz SJ, Mack MC, Gurney KR, Randerson JT, Houghton RA (2007) Ecosystem responses to recent climate change and fire disturbance at northern high latitudes: observations and model results contrasting northern Eurasia and North America. Environmental Research Letters 2, 045031
Ecosystem responses to recent climate change and fire disturbance at northern high latitudes: observations and model results contrasting northern Eurasia and North America.CrossRef |

Hartford RA, Frandsen WH (1992) When it’s hot, it’s hot- or maybe it’s not! (Surface flaming may not portend extensive soil heating) International Journal of Wildland Fire 2, 139–144.
When it’s hot, it’s hot- or maybe it’s not! (Surface flaming may not portend extensive soil heating)CrossRef |

Ichoku C, Kaufman YK (2005) A method to derive smoke emission rates from MODIS fire radiative energy measurements. IEEE Transactions on Geoscience and Remote Sensing 43, 2636–2649.
A method to derive smoke emission rates from MODIS fire radiative energy measurements.CrossRef |

Ju J, Roy DP, Vermote E, Masek J, Kovalskyy V (2012) Continental-scale validation of MODIS-based and LEDAPS Landsat ETM+ atmospheric correction methods. Remote Sensing of Environment 122, 175–184.
Continental-scale validation of MODIS-based and LEDAPS Landsat ETM+ atmospheric correction methods.CrossRef |

Kaufman YJ, Remer LA, Ottmar RD, Ward DE, Li RR, Kleidman R, Fraser RA, Flynn L, McDougal D, Shelton G (1996) Relationship between remotely sensed fire intensity and rate of emission of smoke: SCAR-C experiment. In ‘Global Biomass Burning’. (Ed. JS Levine) pp. 685–696. (MIT Press: Cambridge, MA)

Kaufman YJ, Justice CO, Flynn LP, Kendall JD, Prins EM, Giglio L, Ward DE, Menzel WP, Setzer AW (1998) Potential global fire monitoring from EOS-MODIS. Journal of Geophysical Research 103, 32215–32238.
Potential global fire monitoring from EOS-MODIS.CrossRef | 1:CAS:528:DyaK1MXovVWitA%3D%3D&md5=84de4cc987ee4058d9c3d4c021350407CAS |

Keeley JE (2009) Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire 18, 116–126.
Fire intensity, fire severity and burn severity: a brief review and suggested usage.CrossRef |

Keeley JE, Brennan T, Pfaff AH (2008) Fire severity and ecosystem responses following crown fires in California shrublands. Ecological Applications 18, 1530–1546.
Fire severity and ecosystem responses following crown fires in California shrublands.CrossRef | 18767627PubMed |

Key CH, Benson NC (2006) Landscape assessment: Ground measure of severity, the Composite Burn Index; and remote sensing of severity, the Normalized Burn Ratio. In ‘FIREMON: Fire Effects Monitoring and Inventory System’. (Eds. DC Lutes, RE Keane, JF Caratti, CH Key, NC Benson, S Sutherland, LJ Gangi) USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-164-CD: LA, pp. 1–51. (Ogden, UT)

Kremens RL, Smith AMS, Dickinson MB (2010) Fire metrology: current and future directions in physics-based measurements. Fire Ecology 6, 13–35.
Fire metrology: current and future directions in physics-based measurements.CrossRef |

Kremens RL, Dickinson MB, Bova AS (2012) Radiant flux density, energy density and fuel consumption in mixed-oak forest surface fires. International Journal of Wildland Fire 21, 722–730.
Radiant flux density, energy density and fuel consumption in mixed-oak forest surface fires.CrossRef |

Kumar SS, Roy DP, Boschetti L, Kremens R (2011) Exploiting the power law distribution properties of satellite fire radiative power retrievals – a method to estimate fire radiative energy and biomass burned from sparse satellite observations. Journal of Geophysical Research 116, D19303
Exploiting the power law distribution properties of satellite fire radiative power retrievals – a method to estimate fire radiative energy and biomass burned from sparse satellite observations.CrossRef |

Lee DS, Storey JC, Choate MJ, Hayes R (2004) Four years of Landsat-7 on-orbit geometric calibration and performance. IEEE Transactions on Geoscience and Remote Sensing 42, 2786–2795.
Four years of Landsat-7 on-orbit geometric calibration and performance.CrossRef |

Lentile LB, Holden ZA, Smith AMS, Falkowski MJ, Hudak AT, Morgan P, Lewis SA, Gessler PE, Benson NC (2006) Remote sensing techniques to assess active fire and post-fire effects. International Journal of Wildland Fire 15, 319–345.
Remote sensing techniques to assess active fire and post-fire effects.CrossRef |

Lentile LB, Smith AMS, Hudak AT, Morgan P, Bobbitt MJ, Lewis SA, Robichaud PR (2009) Remote sensing for prediction of 1-year post-fire ecosystem condition. International Journal of Wildland Fire 18, 594–608.
Remote sensing for prediction of 1-year post-fire ecosystem condition.CrossRef |

Littell JS, McKenzie D, Peterson DL, Westerling AL (2009) Climatic influences on twentieth-century area burned in ecoprovinces of the western U.S. Ecological Applications 19, 1003–1021.
Climatic influences on twentieth-century area burned in ecoprovinces of the western U.S.CrossRef | 19544740PubMed |

López Garcia MJ, Caselles V (1991) Mapping burns and natural reforestation using Thematic Mapper data. Geocarto International 6, 31–37.
Mapping burns and natural reforestation using Thematic Mapper data.CrossRef |

McCool SF, Burchfield JA, Carroll MS (2006) An event-based approach for examining the effects of wildland fire decisions on communities. Environmental Management 37, 437–450.
An event-based approach for examining the effects of wildland fire decisions on communities.CrossRef | 16465562PubMed |

Miller JD, Thode AE (2007) Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment 109, 66–80.
Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR).CrossRef |

Miller JD, Yool SR (2002) Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data. Remote Sensing of Environment 82, 481–496.
Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data.CrossRef |

Miller JD, Safford HD, Crimmins M, Thode AE (2008) Quantitative evidence for increasing forest fire severity in the Sierra Nevada and Southern Cascade Mountains, California and Nevada, USA Ecosystems
Quantitative evidence for increasing forest fire severity in the Sierra Nevada and Southern Cascade Mountains, California and Nevada, USACrossRef |

Morgan P, Hardy CC, Swetnam TW, Rollins MG, Long DG (2001) Mapping fire regimes across time and space: understanding coarse and fine-scale fire patterns. International Journal of Wildland Fire 10, 329–342.
Mapping fire regimes across time and space: understanding coarse and fine-scale fire patterns.CrossRef |

Paveglio TB, Jakes PJ, Carroll MS, Williams DR (2009) Understanding social complexity within the wildland–urban interface: a new species of human habitation? Environmental Management 43, 1085–1095.
Understanding social complexity within the wildland–urban interface: a new species of human habitation?CrossRef | 19238478PubMed |

Roberts G, Wooster MJ, Lagoudakis E (2009) Annual and diurnal African biomass burning temporal dynamics. Biogeosciences 6, 849–866.
Annual and diurnal African biomass burning temporal dynamics.CrossRef |

Robichaud PR (2004) Postfire rehabilitation treatments: are we learning what works? Southwest Hyrdology 5, 20–21.

Robichaud PR (2009) Post-fire Stabilization and Rehabilitation. In ‘Fire Effects on Soils and Restoration Strategies’. (Eds A. Cerda and P. R. Robichaud.) pp. 299–320. (Science Publishers: Enfield, NH)

Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. USDA Forest Service, Research Paper INT-115. (Ogden, UT)

Roy DP, Landmann T (2005) Characterizing the surface heterogeneity of fire effects using multi-temporal reflective wavelength data. International Journal of Remote Sensing 26, 4197–4218.
Characterizing the surface heterogeneity of fire effects using multi-temporal reflective wavelength data.CrossRef |

Roy DP, Boschetti L, Trigg S (2006) Remote sensing of fire severity: assessing the performance of the normalized burn ratio. IEEE Geoscience and Remote Sensing Letters 3, 112–116.
Remote sensing of fire severity: assessing the performance of the normalized burn ratio.CrossRef |

Roy DP, Boschetti L, Justice CO, Ju J (2008) The collection 5 MODIS burned area product – global evaluation by comparison with the MODIS active fire product. Remote Sensing of Environment 112, 3690–3707.
The collection 5 MODIS burned area product – global evaluation by comparison with the MODIS active fire product.CrossRef |

Roy DP, Boschetti L, Maier SW, Smith AMS (2010) Field estimation of ash and char colour-lightness using a standard gray scale. International Journal of Wildland Fire 19, 698–704.
Field estimation of ash and char colour-lightness using a standard gray scale.CrossRef |

Ryan KC (2002) Dynamic interactions between forest structure and fire behavior in boreal ecosystems. Silva Fennica 36, 13–39.

Ryan KC, Noste NV (1985) Evaluating prescribed fires. In ‘Proceedings of the symposium and workshop on wilderness fire’, 15–18 November 1983, Missoula, MT. (Eds. JE Lotan, BM Kilgore, WC Fischer, RW Mutch) USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report INT-GTR-182, pp. 230–238. (Ogden, UT)

Schroeder W, Csiszar I, Giglio L, Schmidt CC (2010) On the use of fire radiative power, area, and temperature estimates to characterize biomass burning via moderate to coarse spatial resolution remote sensing data in the Brazilian Amazon. Journal of Geophysical Research 115, D21121
On the use of fire radiative power, area, and temperature estimates to characterize biomass burning via moderate to coarse spatial resolution remote sensing data in the Brazilian Amazon.CrossRef |

Smith AMS, Wooster MJ (2005) Remote classification of head and backfire types from MODIS fire radiative power and smoke plume observations. International Journal of Wildland Fire 14, 249–254.
Remote classification of head and backfire types from MODIS fire radiative power and smoke plume observations.CrossRef |

Smith AMS, Wooster MJ, Drake NA, Dipotso FM, Falkowski MJ, Hudak AT (2005) Testing the potential of multi-spectral remote sensing for retrospectively estimating fire severity in African Savannahs. Remote Sensing of Environment 97, 92–115.
Testing the potential of multi-spectral remote sensing for retrospectively estimating fire severity in African Savannahs.CrossRef |

Smith AMS, Lentile LB, Hudak AT, Morgan P (2007) Evaluation of linear spectral unmixing and dNBR for predicting post-fire recovery in a North American ponderosa pine forest. International Journal of Remote Sensing 28, 5159–5166.
Evaluation of linear spectral unmixing and dNBR for predicting post-fire recovery in a North American ponderosa pine forest.CrossRef |

Smith AMS, Eitel JUH, Hudak AT (2010) Spectral analysis of charcoal on soils: implications for wildland fire severity mapping methods. International Journal of Wildland Fire 19, 976–983.
Spectral analysis of charcoal on soils: implications for wildland fire severity mapping methods.CrossRef | 1:CAS:528:DC%2BC3cXhtlyjsL3M&md5=177dc54d286e786b840bb8115a3b5d3fCAS |

Sullivan AL (2009a) Wildland surface fire spread modelling, 1990–2007. 1. Physical and quasi-physical models. International Journal of Wildland Fire 18, 349–368.
Wildland surface fire spread modelling, 1990–2007. 1. Physical and quasi-physical models.CrossRef |

Sullivan AL (2009b) Wildland surface fire spread modelling, 1990–2007. 2. Empirical and quasi-empirical models. International Journal of Wildland Fire 18, 369–386.
Wildland surface fire spread modelling, 1990–2007. 2. Empirical and quasi-empirical models.CrossRef |

Sullivan AL (2009c) Wildland surface fire spread modelling, 1990–2007. 3. Simulation and mathematical analogue models. International Journal of Wildland Fire 18, 387–403.
Wildland surface fire spread modelling, 1990–2007. 3. Simulation and mathematical analogue models.CrossRef |

Trollope WSW, Tainton NM (1986) Effect of fire intensity on the grass and bush components of the Eastern Cape thornveld. African Journal of Range and Forage Science 3, 37–42.

van der Werf GR, Randerson JT, Giglio L, Collatz GJ, Mu M, Kasibhatla PS, Morton DS, DeFries RS, Jin Y, van Leeuwen TT (2010) Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009) Atmospheric Chemistry and Physics Discussion 10, 16153–16230.
Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009)CrossRef |

Westerling AL, Hidalgo HG, Cayan DR, Swetnam TW (2006) Warming and earlier spring increase western US forest wildfire activity. Science 313, 940–943.
Warming and earlier spring increase western US forest wildfire activity.CrossRef | 1:CAS:528:DC%2BD28XotFCitbo%3D&md5=308417c344ec067b31725c73724340afCAS | 16825536PubMed |

Wolfe RE, Roy DP, Vermote E (1998) MODIS land data storage, gridding, and compositing methodology: level 2 grid, Geoscience and Remote Sensing. IEEE Transactions on Geoscience and Remote Sensing 36, 1324–1338.
MODIS land data storage, gridding, and compositing methodology: level 2 grid, Geoscience and Remote Sensing.CrossRef |

Wolfe RE, Nishihama M, Fleig A, Kuyper J, Roy DP, Storey J, Patt F (2002) Achieving sub-pixel geolocation accuracy in support of MODIS land science. Remote Sensing of Environment 83, 31–49.
Achieving sub-pixel geolocation accuracy in support of MODIS land science.CrossRef |

Wooster MJ (2002) Small-scale experimental testing of fire radiative energy for quantifying mass combusted in natural vegetation fires. Geophysical Research Letters 29, 2027
Small-scale experimental testing of fire radiative energy for quantifying mass combusted in natural vegetation fires.CrossRef |

Wooster MJ, Zhang YH (2004) Boreal forest fires burn less intensely in Russia than in North America. Geophysical Research Letters 31, L20505
Boreal forest fires burn less intensely in Russia than in North America.CrossRef |

Wooster MJ, Roberts G, Perry GLW, Kaufman YJ (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release. Journal of Geophysical Research 110, D24311
Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release.CrossRef |



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