Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 5, issue 1
Articles | Volume 5, issue 1
https://doi.org/10.5194/ascmo-5-57-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-5-57-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 5, issue 1
16 Apr 2019
 | 16 Apr 2019

Fitting a stochastic fire spread model to data

X. Joey Wang, John R. J. Thompson, W. John Braun, and Douglas G. Woolford

Viewed

Total article views: 5,256 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
4,660 497 99 5,256 274 87 74
  • HTML: 4,660
  • PDF: 497
  • XML: 99
  • Total: 5,256
  • Supplement: 274
  • BibTeX: 87
  • EndNote: 74
Views and downloads (calculated since 16 Apr 2019)
Cumulative views and downloads (calculated since 16 Apr 2019)

Viewed (geographical distribution)

Total article views: 4,170 (including HTML, PDF, and XML) Thereof 3,985 with geography defined and 185 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Nov 2024
Download
Short summary
This paper presents the analysis of data from small-scale laboratory experimental smouldering fires that were digitally video-recorded. The video images of these fires bear a resemblance to remotely sensed images of wildfires and provide an opportunity to fit and assess a spatial model for fire spread that attempts to account for uncertainty in fire growth. We found that the fitting method is feasible, and the spatial model provides a suitable mathematical for the fire spread process.
Read more