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![Fire in the landscape. Photo credit: Fire and Emergency New Zealand. Fire in the landscape. Photo credit: Fire and Emergency New Zealand.](https://www.bnhcrc.com.au/sites/default/files/styles/panopoly_image_full/public/managed/images/biblio/partner_-_nz_-_dscf9281.jpg?itok=lto3wUsr)
Quantifying dynamic fire behaviour phenomena using Unmanned Aerial Vehicle technology
Title | Quantifying dynamic fire behaviour phenomena using Unmanned Aerial Vehicle technology |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Filkov, A, Cirulis, B, Penman, T |
Conference Name | 23rd International Congress on Modelling and Simulation |
Date Published | 12/2019 |
Conference Location | Canberra |
Keywords | fire front propagation, merging fire fronts, Remote measurements, UAS |
Abstract | Catastrophic wildfires are often a result of dynamic fire behaviours. Although some of these behaviours have been described and investigated, others require further study. Fire coalescence and junction fires are particular cases of merging fire fronts and are common phenomena observed during bushfires. They are important as they can cause rapid escalation of fire behaviour and be dangerous for ground-based emergency personnel. There are a few studies devoted to investigation of merging fires in field conditions. There is a need for high temporal and spatial measurements of fire behaviour in field conditions in order to better understand this phenomenon and evaluate risks during bushfires and prescribed burning. The aim of this study was to test emerging technologies for better quantification of fire behaviour at field scales and evaluate their potential as an operational tool. Several small and medium scale field experiments were conducted during April 2019 on farmland in Victoria, Australia. Harvested wheat fields were used as experimental plots, as they form relatively homogeneous fuel beds. Fuel height varied from 18 to 40 cm with fuel load and moisture content at 1.1 t/ha and 11.9 % respectively. Wind speed varied in the range of 1.5-6.5 m/s. An Unmanned Aerial Vehicle (UAV) was used to capture high definition video imagery of fire propagation in synchronisation with sensor data from the on-board Global Positioning System (GPS) and Inertial Measurement Unit (IMU). These sensors enabled the platform/camera orientation and position in space to be aligned with the video footage of fire propagation and to be georeferenced in GIS software. Twenty-one junction fires and five inward parallel fire fronts (parts of the fire lines approaching each other) were identified during the experiments. The rate of spread (ROS) of merging fire fronts was found to be at least two times higher than for the basic fire fronts (the rate of spread of a linear fire front in the same fuel bed in no-slope conditions) and for junction fires with acute angles (< 14°) it increased 6 times and more. Inward parallel fire fronts spread much slower, varying between 0.05 and 0.25 m/s. Forty-six percent of junction fires had increase of the ROS at the final stage of the merging process in contrast to Thomas et al. (2017) and Viegas et al. (2012). Also, it was observed that the angle between two oblique fire fronts did not change significantly in time for the initial angles smaller than 34°. It can be assumed that the main fire front influences on the shape and ROS respectively of junction fires and laboratory experiments cannot fully replicate these conditions. Although the initial experimental conditions were very different in relation to scale, fuel and wind conditions, similar ROS to that shown in numerical simulations by Thomas et al. (2017) were observed in our field experiments. Further investigation is required to explain the similarities as the relationship between fuel load, wind speed and scale is not known. The comparison of corrected values of dimensionless ROS for different angles between fire fronts with laboratory experiments of Viegas et al. (2012) showed reasonable quantitative agreement. These experiments have shown that the method of using UAV's to capture georeferenced video footage can be used reliably to quantify fire behaviour phenomena for research, operation and management purposes. Catastrophic wildfires are often a result of dynamic fire behaviours. Although some of these behaviours have been described and investigated, others require further study. Fire coalescence and junction fires are particular cases of merging fire fronts and are common phenomena observed during bushfires. They are important as they can cause rapid escalation of fire behaviour and be dangerous for ground-based emergency personnel. There are a few studies devoted to investigation of merging fires in field conditions. There is a need for high temporal and spatial measurements of fire behaviour in field conditions in order to better understand this phenomenon and evaluate risks during bushfires and prescribed burning. The aim of this study was to test emerging technologies for better quantification of fire behaviour at field scales and evaluate their potential as an operational tool. Several small and medium scale field experiments were conducted during April 2019 on farmland in Victoria, Australia. Harvested wheat fields were used as experimental plots, as they form relatively homogeneous fuel beds. Fuel height varied from 18 to 40 cm with fuel load and moisture content at 1.1 t/ha and 11.9 % respectively. Wind speed varied in the range of 1.5-6.5 m/s. An Unmanned Aerial Vehicle (UAV) was used to capture high definition video imagery of fire propagation in synchronisation with sensor data from the on-board Global Positioning System (GPS) and Inertial Measurement Unit (IMU). These sensors enabled the platform/camera orientation and position in space to be aligned with the video footage of fire propagation and to be georeferenced in GIS software. Twenty-one junction fires and five inward parallel fire fronts (parts of the fire lines approaching each other) were identified during the experiments. The rate of spread (ROS) of merging fire fronts was found to be at least two times higher than for the basic fire fronts (the rate of spread of a linear fire front in the same fuel bed in no-slope conditions) and for junction fires with acute angles (< 14°) it increased 6 times and more. Inward parallel fire fronts spread much slower, varying between 0.05 and 0.25 m/s. Forty-six percent of junction fires had increase of the ROS at the final stage of the merging process in contrast to Thomas et al. (2017) and Viegas et al. (2012). Also, it was observed that the angle between two oblique fire fronts did not change significantly in time for the initial angles smaller than 34°. It can be assumed that the main fire front influences on the shape and ROS respectively of junction fires and laboratory experiments cannot fully replicate these conditions. Although the initial experimental conditions were very different in relation to scale, fuel and wind conditions, similar ROS to that shown in numerical simulations by Thomas et al. (2017) were observed in our field experiments. Further investigation is required to explain the similarities as the relationship between fuel load, wind speed and scale is not known. The comparison of corrected values of dimensionless ROS for different angles between fire fronts with laboratory experiments of Viegas et al. (2012) showed reasonable quantitative agreement. These experiments have shown that the method of using UAV's to capture georeferenced video footage can be used reliably to quantify fire behaviour phenomena for research, operation and management purposes. |
URL | https://www.researchgate.net/publication/338412609_Quantifying_dynamic_fire_behaviour_phenomena_using_Unmanned_Aerial_Vehicle_technology |
Refereed Designation | Refereed |
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