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

Direct estimation of Byram’s fire intensity from infrared remote sensing imagery

Joshua M. Johnston A B E , Martin J. Wooster B C , Ronan Paugam B D , Xianli Wang A , Timothy J. Lynham A and Lynn M. Johnston A
+ Author Affiliations
- Author Affiliations

A Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen Street E, Sault Ste Marie, ON, P6A 2E5, Canada.

B King’s College London, Department of Geography, Strand, London WC2R 2LS, UK.

C Natural Environmental Research Council (NERC), National Centre for Earth Observation (NCEO), UK.

D College of Forest Resources, University of Washington, Mailbox 352100, Seattle, WA, 98195, USA.

E Corresponding author. Email: joshua.johnston@canada.ca

International Journal of Wildland Fire 26(8) 668-684 https://doi.org/10.1071/WF16178
Submitted: 20 September 2016  Accepted: 10 May 2017   Published: 29 June 2017

Abstract

Byram’s fire intensity (IB,tot; kW m–1) is one the most important and widely accepted metrics for quantifying wildfire behaviour. Calculation of IB,tot requires measurement of fuel consumption, heat of combustion and rate of spread; existing methods for obtaining these measurements are either inexact or at times impossible to obtain in the field. This paper presents and evaluates a series of remote sensing methods for directly deriving radiative fire intensity (IB,rad; kW m–1) using the Fire Radiative Power (FRP) approach applied to thermal infrared imagery of spreading vegetation fires. Comparisons between the remote sensing data and ground-sampled measurements were used to evaluate the various estimates of IB,tot, and to determine the radiative fraction (radF) of a fire’s emitted energy. Results indicate that the IB,tot along an advancing flame front can be reasonably estimated (and agrees with traditional methods of estimation (R2 = 0.34–0.73)) from appropriately collected time-series of remote sensing imagery without the need for ground sampling or ancillary data. We further estimate that the radF of the fire’s emitted energy varies between 0.15 and 0.20 depending on the method of calculation, which is similar to previous estimates.


References

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

Alexander ME (2013) Fire management applications of wildland fire behaviour knowledge. In ‘Fire on Earth: an Introduction’. (Eds AC Scott, DMJS Bowman, WJ Bond, SJ Pyne, ME Alexander) pp. 373–391. (Wiley–Blackwell: Hoboken, NJ, USA)

Alexander ME, Lanoville RA (1987) Wildfires as a source of fire behavior data: a case study from Northwest Territories, Canada. In ‘Proceedings of the 9th Conference on Fire and Forest Meteorology’, 21–24 April 1987, San Diego, CA, USA. pp. 86–93. (American Meteorological Society: Boston, MA, USA)

Alexander ME, Stocks BJ, Lawson BD (1991) Fire behavior in black spruce–lichen woodland: the Porter Lake project. Forestry Canada, Northwest Region, Northern Forestry Centre, Information Report NOR-X-310. (Edmonton, AB, Canada)

Butler B (2014) Wildland fire fighter safety zones: a review of past science and summary of future needs. International Journal of Wildland Fire 23, 295–308.
Wildland fire fighter safety zones: a review of past science and summary of future needs.Crossref | GoogleScholarGoogle Scholar |

Butler B, Finney M, Andrews P, Albini F (2004) A radiation-driven model for crown fire spread. Canadian Journal of Forest Research 34, 1588–1599.
A radiation-driven model for crown fire spread.Crossref | GoogleScholarGoogle Scholar |

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

Dickinson MB, Hudak AT, Zajkowski T, Loudermilk EL, Schroeder W, Ellison L, Kremens RL, Holley W, Martinez O, Paxton A, Bright BC, O’Brien JJ, Hornsby B, Ichoku C, Faulring J, Gerace A, Peterson D, Mauceri J (2016) Measuring radiant emissions from entire prescribed fires with ground, airborne and satellite sensors – RxCADRE 2012. International Journal of Wildland Fire 25, 48–61.
Measuring radiant emissions from entire prescribed fires with ground, airborne and satellite sensors – RxCADRE 2012.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC28Xmslegtw%3D%3D&md5=40749ca0cdde26f250e4fb1d68050742CAS |

Dold JW (2010) Vegetation engagement in unsteady fire spread. In ‘Proceedings of the VI International Conference on Forest Fire Research’, 15–18 November 2010, Coimbra, Portugal. (Ed. DX Viegas) (ADAI Press: Coimbra, Portugal)

Dold JW, Zinoviev A, Leslie E (2009) Fire intensity accumulation in unsteady fireline modelling. In ‘Proceedings of the Sixth Mediterranean Combustion Symposium’, 7 June–12 June 2009, Ajaccio, Corsica. (Eds A Simeoni, E Leoni, P-A Santoni) MCS 6. (Università di Corsica: Corte, Corsica, France)

Dozier J (1981) A method for satellite identification of surface temperature fields of subpixel resolution. Remote Sensing of Environment 11, 221–229.
A method for satellite identification of surface temperature fields of subpixel resolution.Crossref | GoogleScholarGoogle Scholar |

Flannigan MD, Krawchuk MA, de Groot WJ, Wotton BM, Gowman LM (2009) Impacts of changing climate for global wildland fire. International Journal of Wildland Fire 18, 483–507.
Impacts of changing climate for global wildland fire.Crossref | GoogleScholarGoogle Scholar |

Forestry Canada Fire Danger Group (1992) Development and structure of the Canadian Forest Fire Behavior Prediction System. Forestry Canada, Science and Sustainable Development Directorate, Information Report ST-X-3. (Ottawa, ON, Canada)

Frankman D, Webb BW, Butler BW, Jimenez D, Forthofer JM, Sopko P, Shannon KS, Hiers JK, Ottmar RD (2013) Measurements of convective and radiative heating in wildland fires. International Journal of Wildland Fire 22, 157–167.
Measurements of convective and radiative heating in wildland fires.Crossref | GoogleScholarGoogle Scholar |

Freeborn P, Wooster MJ, Hao WM, Ryan CA, Nordgren BL, Baker SP, 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 fires.Crossref | GoogleScholarGoogle Scholar |

Giglio L, Kendall JD (2001) Application of the Dozier retrieval to wildfire characterization: a sensitivity analysis. Remote Sensing of Environment 77, 34–49.
Application of the Dozier retrieval to wildfire characterization: a sensitivity analysis.Crossref | GoogleScholarGoogle Scholar |

Hudak AT, Dickinson MB, Kremens RL, Bright BC, Loudermilk EL, O’Brien JJ, Hornsby B, Ottmar RD (2016) Measurements relating fire radiative energy density and surface fuel consumption – RxCADRE 2011 and 2012. International Journal of Wildland Fire 25, 25–37.
Measurements relating fire radiative energy density and surface fuel consumption – RxCADRE 2011 and 2012.Crossref | GoogleScholarGoogle Scholar |

Ichoku C, Giglio L, Wooster MJ, Remer LA (2008) Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy. Remote Sensing of Environment 112, 2950–2962.
Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy.Crossref | GoogleScholarGoogle Scholar |

Johnston JM (2016) Infrared remote sensing of fire behaviour in Canadian wildland forest fuels. PhD thesis, King’s College London.

Johnston JM, Wooster MJ, Lynham TJ (2014) Experimental confirmation of the MWIR and LWIR greybody assumption for vegetation fire flame emissivity. International Journal of Wildland Fire 23, 463–479.
Experimental confirmation of the MWIR and LWIR greybody assumption for vegetation fire flame emissivity.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC2cXhtVentb3N&md5=926e6e91d60defa235c12b5595618179CAS |

Kaufman Y, Kleidman R, King M (1998) SCAR-B fires in the tropics: properties and remote sensing from EOS-MODIS. Journal of Geophysical Research 103, 31955–31968.
SCAR-B fires in the tropics: properties and remote sensing from EOS-MODIS.Crossref | GoogleScholarGoogle Scholar |

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 | GoogleScholarGoogle Scholar |

Legg C, Davies M, Kitchen K, Marno P (2007) A fire danger rating system for vegetation fires in the UK: the FireBeaters Project Phase 1 Final Report. The University of Edinburgh and The Met Office. (Edinburgh, UK).

McArthur AG (1967) Fire behaviour in eucalypt forests. Commonwealth of Australia, Forestry and Timber Bureau Leaflet 107. (Canberra, ACT)

McRae DJ, Alexander ME, Stocks BJ (1979) ‘Measurement and Description of Fuels and Fire Behavior on Prescribed Burns: a Handbook.’ (Great Lakes Forest Research Centre: Sault Ste Marie, ON, Canada).

McRae DJ, Jin J-Z, Conard SG, Sukhinin AI, Ivanova GA, Blake TW (2005) Infrared characterization of fine-scale variability in behaviour of boreal forest fires. Canadian Journal of Forest Research 35, 2194–2206.
Infrared characterization of fine-scale variability in behaviour of boreal forest fires.Crossref | GoogleScholarGoogle Scholar |

Pastor E, Àgueda A, Andrade-Cetto J, Muñoz M, Pérez Y, Planas E (2006) Computing the rate of spread of linear flame fronts by thermal image processing. Fire Safety Journal 41, 569–579.
Computing the rate of spread of linear flame fronts by thermal image processing.Crossref | GoogleScholarGoogle Scholar |

Paugam R, Wooster MJ, Roberts G (2013) Use of handheld thermal imager data for airborne mapping of fire radiative power and energy and flame front rate of spread. IEEE Transactions on Geoscience and Remote Sensing 99, 1–15.

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

Rothermel R, Deeming J (1980) Measuring and interpreting fire behavior for correlation with fire effects. USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report INT-93. (Ogden, UT, USA)

Simard A, Eenigenburg J, Adams K, Nissen R, Deacon A (1984) A general procedure for sampling and analyzing wildland fire spread. Forest Science 30, 51–64.

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 | GoogleScholarGoogle Scholar |

Smith AMS, Tinkham WT, Roy DP, Boschetti L, Kremens RL, Kumar SS, Sparks AM, Falkowski MJ (2013) Quantification of fuel moisture effects on biomass consumed derived from fire radiative energy retrievals. Geophysical Research Letters 40, 6298–6302.
Quantification of fuel moisture effects on biomass consumed derived from fire radiative energy retrievals.Crossref | GoogleScholarGoogle Scholar |

Stocks BJ (1987) Fire behaviour in immature jack pine. Canadian Journal of Forest Research 17, 80–86.
Fire behaviour in immature jack pine.Crossref | GoogleScholarGoogle Scholar |

Stocks BJ (1989) Fire behaviour in mature jack pine. Canadian Journal of Forest Research 19, 783–790.
Fire behaviour in mature jack pine.Crossref | GoogleScholarGoogle Scholar |

Stocks BJ, Alexander ME, Wotton BM, Stefner CN, Flannigan MD, Taylor SW, Lavoie N, Mason JA, Hartley GR, Maffey ME, Dalrymple TW, Blake TW, Cruz MG, Lanoville RA (2004) Crown fire behaviour in a northern jack pine–black spruce forest. Canadian Journal of Forest Research 34, 1548–1560.
Crown fire behaviour in a northern jack pine–black spruce forest.Crossref | GoogleScholarGoogle Scholar |

Taylor SW, Pike RG, Alexander ME (1997) Field guide to the Canadian Forest Fire Behavior Prediction (FBP) System. Northern Forestry Centre, Special Report 11. (Edmonton, AB, Canada)

Van Wagner C (1962) On the value of a numerical concept of fire intensity. Pulp & Paper Magazine of Canada, Woodland Review 63, 458–459.

Van Wagner CE (1965) Describing forest fires – old ways and new. Forestry Chronicle 41, 301–305.
Describing forest fires – old ways and new.Crossref | GoogleScholarGoogle Scholar |

Van Wagner CE (1974) Structure of the Canadian Forest Fire Weather Index. Department of the Environment, Canadian Forestry Service, Publication number 1333. (Ottawa, ON, Canada)

Van Wagner CE (1977) In readers’ forum. Fire Technology 13, 349–350.
In readers’ forum.Crossref | GoogleScholarGoogle Scholar |

Wooster MJ, Zhukov B, Oertel D (2003) Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products. Remote Sensing of Environment 86, 83–107.
Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products.Crossref | GoogleScholarGoogle Scholar |

Wooster MJ, Perry G, Zhukov B, Oertel D (2004) Estimation of energy emissions, fireline intensity and biomass consumption in wildland fires: a potential approach using remotely sensed fire radiative energy. In ‘Spatial Modelling of the Terrestrial Environment’. (Eds R Kelly, N Drake, S Barr) pp. 177–198 (Wiley: London, UK)

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 | GoogleScholarGoogle Scholar |

Wotton B, Gould J, McCaw W, Cheney N, Taylor S (2012) Flame temperature and residence time of fires in dry eucalypt forest. International Journal of Wildland Fire 21, 270–281.
Flame temperature and residence time of fires in dry eucalypt forest.Crossref | GoogleScholarGoogle Scholar |

Zhukov B, Oertel D, Lorenz E, Ziman Y, Csiszar I (2005) Comparison of fire detection and quantitative characterization by MODIS and BIRD. In ‘Proceedings of the 31st International Symposium on Remote Sensing of Environment: Global Monitoring for Sustainability and Security’, 20–24 June 2005, Saint Petersburg, Russia. (International Center for Remote Sensing of Environment)