Fire Technology

, Volume 55, Issue 3, pp 817–836 | Cite as

Particle Tracking and Detection Software for Firebrands Characterization in Wildland Fires

  • Alexander FilkovEmail author
  • Sergey Prohanov


Detection and analysis of the objects in a frame or a sequence of frames (video) can be used to solve a number of problems in various fields, including the field of fire behaviour and risk. A quantitative understanding of the short distance spotting dynamics, namely the firebrand density distribution within a distance from the fire front and how distinct fires coalesce in a highly turbulent environment, is still lacking. To address this, a custom software was developed in order to detect the location and the number of flying firebrands in a thermal image then determine the temperature and sizes of each firebrand. The software consists of two modules, the detector and the tracker. The detector determines the location of the firebrands in the frame, and the tracker compares the firebrand in different frames and determines the identification number of each firebrand. Comparison of the calculated results with the data obtained by the independent experts and experimental data showed that the maximum relative error does not exceed 12% for the low and medium number of firebrands in the frame (less than 30) and software agrees well with experimental observations for firebrands > 20 × 10−5 m. It was found that fireline intensity below 12,590 kW m−1 does not change significantly 2D firebrand flux for firebrands bigger than 20 × 10−5 m, while occasional crowning can increase the firebrand flux in several times. The developed software allowed us to analyse the thermograms obtained during the field experiments and to measure the velocities, sizes and temperatures of the firebrands. It will help to better understand of how the firebrands can ignite the surrounding fuel beds and could be an important tool in investigating fire propagation in communities.


Wildland and structural firebrands Firebrand detection Firebrand tracking 



This work was supported by the Russian Foundation for Basic Research (Project #18-07-00548), the Tomsk State University Academic D.I. Mendeleev Fund Program and the Bushfire and Natural Hazard Cooperative Research Centre.

Supplementary material

Supplementary material 1 (AVI 210 kb)

Supplementary material 2 (AVI 462 kb)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Ecosystem and Forest SciencesUniversity of MelbourneCreswickAustralia
  2. 2.Mechanics and Mathematics FacultyNational Research Tomsk State UniversityTomskRussia

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