We are developing a wildland fire model based on semi-empirical relations that estimate the rate of spread of a surface fire and post-frontal heat release, coupled with WRF, the Weather Research and Forecasting atmospheric model. A level set method identifies the fire front. Data are assimilated using both amplitude and position corrections using a morphing ensemble Kalman filter. We will use thermal images of a fire for observations that will be compared to synthetic image based on the model state. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Beezley, J. D., Chakraborty, S., Coen, J. L., Douglas, C. C., Mandel, J., Vodacek, A., & Wang, Z. (2008). Real-time data driven wildland fire modeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5103 LNCS, pp. 46–53). https://doi.org/10.1007/978-3-540-69389-5_7
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