Parameter estimation for the forest fire propagation model: Applied Mathematics ´19

Year, pages: 2020, 1 - 22

This paper first gives a brief overview of the Lagrangian forest fire propagation model [Ambroz, M.—Balažovjech, M.—Medl\kern-0.04cm\char39\kern-0.03cm a, M.—Mikula, K.: \textit{Numerical modeling of wildland surface fire propagation by evolving surface curves}, Adv. Comput. Math. \textbf{45} (2019), no. 2, 1067–1103], which we apply to grassfield areas. Then, we aim to estimate the optimal model parameters. To achieve this goal, we use data assimilation of the measured data. From the data, we are able to estimate the normal velocity of the fire front (rate of spread), dominant wind direction and selected model parameters. In the data assimilation process, we use the Hausdorff distance as well as the Mean Hausdorff distance as a criterion. Moreover, we predict the fire propagation in small time intervals.

Ambroz, M., Mikula, K., Fraštia, M., Marčiš, M. 2020. Parameter estimation for the forest fire propagation model: Applied Mathematics ´19. In Tatra Mountains Mathematical Publications, vol. 75, no.1, pp. 1-22. 1210-3195. DOI: https://doi.org/10.2478/tmmp-2020-0001

Ambroz, M., Mikula, K., Fraštia, M., Marčiš, M. (2020). Parameter estimation for the forest fire propagation model: Applied Mathematics ´19. Tatra Mountains Mathematical Publications, 75(1), 1-22. 1210-3195. DOI: https://doi.org/10.2478/tmmp-2020-0001

Publisher: Mathematical Institute, Slovak Academy of Sciences, Bratislava

Licensed under the Creative Commons Attribution-NC-ND4.0 International Public License.