Influence of fuel structure on gorse fire behaviour
Andres Valencia
A * , Katharine O. Melnik A , Nick Sanders A , Adam Sew Hoy A , Mozhi Yan A , Marwan Katurji B , Jiawei Zhang B C , Benjamin Schumacher B , Robin Hartley C , Samuel Aguilar-Arguello C , H. Grant Pearce C D , Mark A. Finney E , Veronica Clifford C and Tara Strand C
+ Author Affiliations
- Author Affiliations
A Department of Civil and Natural Resources Engineering, University of Canterbury, Christchurch 8140, New Zealand.
B University Centre for Atmospheric Research, School of Earth and Environment, University of Canterbury, Christchurch, New Zealand.
C New Zealand Forest Research Institute, Scion, Christchurch, New Zealand.
D Fire and Emergency New Zealand, Christchurch, New Zealand.
E USDA Forest Service, Missoula Fire Science Laboratory, Missoula, Montana, USA.
* Correspondence to: andres.valencia@canterbury.ac.nz
International Journal of Wildland Fire 32(6) 927-941 https://doi.org/10.1071/WF22108
Submitted: 1 July 2022 Accepted: 11 April 2023 Published: 15 May 2023
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Background: Complex interactions between fuel structure and fire substantially affect fire spread and spatial variability in fire behaviour. Heterogeneous arrangement of the fuel coupled with variability in fuel characteristics can impact heat transfer efficiency, preheating of unburned fuel and consequent ignition and spread.
Aim: Study the influence of pre-burn fuel structure (canopy height, spatial arrangement) on fire behaviour (rate of spread, flame residence time) derived from high-resolution video of a prescribed gorse fire.
Method: Rate of spread and flame residence time are calculated and mapped from high-resolution overhead visible-spectrum video, and compared with the Canopy Height Model derived from pre-burn Light Detection and Ranging (Lidar) scans.
Results: Geospatial analytics can provide precision observations of fire behaviour metrics. Rates of spread under high wind conditions are influenced by local changes in canopy height and may be more dependent on other fuel characteristics, while flame residence time is better correlated with canopy height.
Conclusions: These observational technology and spatio-temporal analytical techniques highlight how detailed fire behaviour characteristics can be derived from these data.
Implications: The results have implications for wildfire modelling and Wildland–Urban Interface (WUI) building design engineers, as the reported dataset is suitable for model validation and the analysis contributes to further understanding of gorse fire hazard.
Keywords: fire behaviour, gorse, image analysis, image velocimetry, lidar, rate of spread, residence time, UAV, Ulex europaeus, wildfires.
References
Beer T (1991) Bushfire rate‐of‐spread forecasting: Deterministic and statistical approaches to fire modelling. Journal of Forecasting 10, 301–317.| Bushfire rate‐of‐spread forecasting: Deterministic and statistical approaches to fire modelling.Crossref | GoogleScholarGoogle Scholar |
Blender Online Community (2019) ‘Blender - a 3D modelling and rendering package.’ (Stichting Blender Foundation, 508 Blender Institute: Amsterdam) Available at http://www.blender.org
Canfield JM, Linn RR, Sauer JA, Finney M, Forthofer J (2014) A numerical investigation of the interplay between fireline length, geometry, and rate of spread. Agricultural and Forest Meteorology 189–190, 48–59.
| A numerical investigation of the interplay between fireline length, geometry, and rate of spread.Crossref | GoogleScholarGoogle Scholar |
Ciullo V, Rossi L, Pieri A (2020) Experimental fire measurement with UAV multimodal stereovision. Remote Sensing 12, 3546
| Experimental fire measurement with UAV multimodal stereovision.Crossref | GoogleScholarGoogle Scholar |
Clements CB, Zhong S, Goodrick S, Li J, Potter BE, Bian X, Heilman WE, Charney JJ, Perna R, Jang M, Lee D, Patel M, Street S, Aumann G (2007) Observing the dynamics of wildland grass fires. Bulletin of the American Meteorological Society 88, 1369–1382.
| Observing the dynamics of wildland grass fires.Crossref | GoogleScholarGoogle Scholar |
Cruz MG, McCaw WL, Anderson WR, Gould JS (2013) Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia. Environmental Modelling & Software 40, 21–34.
| Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia.Crossref | GoogleScholarGoogle Scholar |
Cruz MG, Alexander ME, Kilinc M (2022) Wildfire rates of spread in grasslands under critical burning conditions. Fire 5, 55
| Wildfire rates of spread in grasslands under critical burning conditions.Crossref | GoogleScholarGoogle Scholar |
Dahale A, Ferguson S, Shotorban B, Mahalingam S (2013) Effects of distribution of bulk density and moisture content on shrub fires. International Journal of Wildland Fire 22, 625–641.
| Effects of distribution of bulk density and moisture content on shrub fires.Crossref | GoogleScholarGoogle Scholar |
Fayad J, Rossi L, Frangieh N, Awad C, Accary G, Chatelon FJ, Morandini F, Marcelli T, Cancellieri V, Cancellieri D, Morvan D, Pieri A, Planelles G, Costantini R, Meradji S, Rossi JL (2022) Numerical study of an experimental high-intensity prescribed fire across Corsican Genista salzmannii vegetation. Fire Safety Journal 131, 103600
| Numerical study of an experimental high-intensity prescribed fire across Corsican Genista salzmannii vegetation.Crossref | GoogleScholarGoogle Scholar |
Finney MA, Cohen JD, Forthofer JM, McAllister SS, Gollner MJ, Gorham DJ, Saito K, Akafuah NK, Adam BA, English JD (2015) Role of buoyant flame dynamics in wildfire spread. Proceedings of the National Academy of Sciences 112, 9833–9838.
| Role of buoyant flame dynamics in wildfire spread.Crossref | GoogleScholarGoogle Scholar |
Finney MA, Pearce G, Strand T, et al. (2018) New Zealand prescribed fire experiments to test convective heat transfer in wildland fires. In Viegas DX (ed) ‘Advances in Forest Fire Research 2018’ 1288–1292.
| New Zealand prescribed fire experiments to test convective heat transfer in wildland fires.Crossref | GoogleScholarGoogle Scholar |
Hartley RJL, Davidson SJ, Watt MS, Massam PD, Aguilar-arguello S, Melnik KO, Pearce HG, Clifford VR (2022) A mixed methods approach for fuel characterisation in gorse (Ulex europaeus L.) scrub from high-density UAV laser scanning point clouds and semantic segmentation of UAV imagery. Remote Sensing 14, 4775
| A mixed methods approach for fuel characterisation in gorse (Ulex europaeus L.) scrub from high-density UAV laser scanning point clouds and semantic segmentation of UAV imagery.Crossref | GoogleScholarGoogle Scholar |
Hoffman CM, Canfield J, Linn RR, Mell W, Sieg CH, Pimont F, Ziegler J (2016) Evaluating crown fire rate of spread predictions from physics-based models. Fire Technology 52, 221–237.
| Evaluating crown fire rate of spread predictions from physics-based models.Crossref | GoogleScholarGoogle Scholar |
Isenburg M (2021) LAStools-efficient LiDAR processing software (version 210418). Available at lastools.github.io [accessed on 10 October 2021]
Johnston JM, Wooster MJ, Paugam R, Wang X, Lynham TJ, Johnston LM (2017) Direct estimation of Byram’s fire intensity from infrared remote sensing imagery. International Journal of Wildland Fire 26, 668–684.
| Direct estimation of Byram’s fire intensity from infrared remote sensing imagery.Crossref | GoogleScholarGoogle Scholar |
Katurji M, Zhang J, Satinsky A, McNair H, Schumacher B, Strand T, Valencia A, Finney M, Pearce G, Kerr J, Seto D, Wallace H, Zawar‐Reza P, Dunker C, Clifford V, Melnik K, Grumstrup T, Forthofer J, Clements C (2021) Turbulent thermal image velocimetry at the immediate fire and atmospheric interface. Journal of Geophysical Research: Atmospheres 126, e2021JD035393
| Turbulent thermal image velocimetry at the immediate fire and atmospheric interface.Crossref | GoogleScholarGoogle Scholar |
Katurji M, Noonan B, Zhang J, Valencia A, Shumacher B, Kerr J, Strand T, Pearce G, Zawar-Reza P (2022) Atmospheric turbulent structures and fire sweeps during shrub fires and implications for flaming zone behaviour. International Journal of Wildland Fire 32, 43–55.
| Atmospheric turbulent structures and fire sweeps during shrub fires and implications for flaming zone behaviour.Crossref | GoogleScholarGoogle Scholar |
Linn RR, Cunningham P (2005) Numerical simulations of grass fires using a coupled atmosphere–fire model: Basic fire behavior and dependence on wind speed. Journal of Geophysical Research: Atmospheres 110, D13107
| Numerical simulations of grass fires using a coupled atmosphere–fire model: Basic fire behavior and dependence on wind speed.Crossref | GoogleScholarGoogle Scholar |
Martins Fernandes PA (2001) Fire spread prediction in shrub fuels in Portugal. Forest Ecology and Management 144, 67–74.
| Fire spread prediction in shrub fuels in Portugal.Crossref | GoogleScholarGoogle Scholar |
Mell W, Jenkins MA, Gould J, Cheney P (2007) A physics-based approach to modelling grassland fires. International Journal of Wildland Fire 16, 1–22.
| A physics-based approach to modelling grassland fires.Crossref | GoogleScholarGoogle Scholar |
Mell W, McNamara D, Maranghides A, McDermott R, Forney G, Hoffman C, Ginder M (2011) Computer modelling of wildland–urban interface fires. In ‘Fire and Materials 2011, 12th International Conference and Exhibition’. (Ed. V Brabauskas) pp. 531–544. (Interscience Communications)
Melnik K (2021) Fire perimeter tracking. Available at https://doi.org/10.5281/zenodo.5138773
Morvan D (2011) Physical phenomena and length scales governing the behaviour of wildfires: a case for physical modelling. Fire Technology 47, 437–460.
| Physical phenomena and length scales governing the behaviour of wildfires: a case for physical modelling.Crossref | GoogleScholarGoogle Scholar |
Morvan D, Méradji S, Accary G (2009) Physical modelling of fire spread in grasslands. Fire Safety Journal 44, 50–61.
| Physical modelling of fire spread in grasslands.Crossref | GoogleScholarGoogle Scholar |
NSW Rural Fire Service (2019) Planning for Bush Fire Protection (PBP). Available at https://www.rfs.nsw.gov.au/__data/assets/pdf_file/0008/4400/Complete-Planning-for-Bush-Fire-Protection-2006.pdf
Page WG, Butler BW (2017) An empirically based approach to defining wildland firefighter safety and survival zone separation distances. International Journal of Wildland Fire 26, 655–667.
| An empirically based approach to defining wildland firefighter safety and survival zone separation distances.Crossref | GoogleScholarGoogle Scholar |
Pearce HG, Anderson WR, Fogarty LG, Todoroki CL, Anderson SAJ (2010) Linear mixed-effects models for estimating biomass and fuel loads in shrublands. Canadian Journal of Forest Research 40, 2015–2026.
| Linear mixed-effects models for estimating biomass and fuel loads in shrublands.Crossref | GoogleScholarGoogle Scholar |
Penney G, Richardson S (2019) Modelling of the radiant heat flux and rate of spread of wildfire within the urban environment. Fire 2, 4
| Modelling of the radiant heat flux and rate of spread of wildfire within the urban environment.Crossref | GoogleScholarGoogle Scholar |
Penney G, Habibi D, Cattani M (2019) Firefighter tenability and its influence on wildfire suppression. Fire Safety Journal 106, 38–51.
| Firefighter tenability and its influence on wildfire suppression.Crossref | GoogleScholarGoogle Scholar |
Penney G, Habibi D, Cattani M (2020) ‘A handbook of wildfire engineering: guidance for wildfire suppression and resilient urban design.’ (Bushfire and Natural Hazards CRC: Melbourne) Available at https://www.bnhcrc.com.au/publications/handbook-of-wildfire-engineering
Penney G, Baker G, Valencia A, Gorham D (2022) The CAED Framework for the development of performance‐based design at the wildland–urban interface. Fire 5, 54
| The CAED Framework for the development of performance‐based design at the wildland–urban interface.Crossref | GoogleScholarGoogle Scholar |
R Core Team (2020) ‘R: A Language and Environment for Statistical Computing.’ (R Foundation for Statistical Computing: Vienna, Austria) Available at https://www.r-project.org/
Rossi L, Molinier T, Akhloufi M, Tison Y, Pieri A (2010) A 3D vision system for the measurement of the rate of spread and the height of fire fronts. Measurement Science and Technology 21, 105501
| A 3D vision system for the measurement of the rate of spread and the height of fire fronts.Crossref | GoogleScholarGoogle Scholar |
Roussel J-R, Auty D, De Boissieu F, Meador AS (2018) lidR: Airborne LiDAR data manipulation and visualization for forestry applications. R package version 1.
SAI-Global (2018) ‘AS3959:2018 Construction of Buildings in Bushfire-Prone Areas.’ (Standards Australia: Sydney, Australia)
Sánchez-Monroy X, Mell W, Torres-Arenas J, Butler BW (2019) Fire spread upslope: Numerical simulation of laboratory experiments. Fire Safety Journal 108, 102844
| Fire spread upslope: Numerical simulation of laboratory experiments.Crossref | GoogleScholarGoogle Scholar |
Santoni PA, Simeoni A, Rossi JL, Bosseur F, Morandini F, Silvani X, Balbi JH, Cancellieri D, Rossi L (2006) Instrumentation of wildland fire: Characterisation of a fire spreading through a Mediterranean shrub. Fire Safety Journal 41, 171–184.
| Instrumentation of wildland fire: Characterisation of a fire spreading through a Mediterranean shrub.Crossref | GoogleScholarGoogle Scholar |
Schumacher B, Melnik KO, Katurji M, Zhang J, Clifford V, Pearce HG (2022) Rate of spread and flaming zone velocities of surface fires from visible and thermal image processing. International Journal of Wildland Fire 31, 759–773.
| Rate of spread and flaming zone velocities of surface fires from visible and thermal image processing.Crossref | GoogleScholarGoogle Scholar |
Sullivan AL (2017) Inside the Inferno: Fundamental Processes of Wildland Fire Behaviour: Part 2: Heat Transfer and Interactions. Current Forestry Reports 3, 150–171.
| Inside the Inferno: Fundamental Processes of Wildland Fire Behaviour: Part 2: Heat Transfer and Interactions.Crossref | GoogleScholarGoogle Scholar |
Vacca P, Caballero D, Pastor E, Planas E (2020) WUI fire risk mitigation in Europe: A performance-based design approach at home-owner level. Journal of Safety Science and Resilience 1, 97–105.
| WUI fire risk mitigation in Europe: A performance-based design approach at home-owner level.Crossref | GoogleScholarGoogle Scholar |
WAPC (2017) Guidelines for Planning in Bushfire Prone Areas. (Western Australian Planning Commission: Perth, Western Australia) Available at https://apo.org.au/node/102666
