Improving Geostationary Satellite-Based Prediction of Wildfire Spread by Directional Rate of Spread Adjustment Factor

Author:

Yoo Seungmin12,Song Junho12

Affiliation:

1. Institute of Construction and Environmental Engineering, Seoul National Univ., Seoul, Republic of Korea.

2. Dept. of Civil and Environmental Engineering, Seoul National Univ., Seoul, Republic of Korea.

Publisher

American Society of Civil Engineers

Reference13 articles.

1. Data Assimilation

2. Calculation of fire spread rates across random landscapes.;Finney M. A.;International Journal of Wildland Fire,2003

3. Fire spread through porous fuels from the conservation of energy.;Frandsen W. H.;Combustion and Flame,1971

4. LANDFIRE. (2016). 40 Fire Behavior Fuel Models-Scott/Burgan LANDFIRE 2.0.0 U.S. Department of the Interior Geological Survey. https://www.landfire.gov/viewer/ (accessed 20 April 2023).

5. Mandel, J., Chen, M., Franca, L. P., Johns, C., Puhalskii, A., Coen, J. L., Douglas, C. C., Kremens, R., Vodacek, A., and Zhao, W. (2004). A note on dynamic data driven wildfire modeling. In International Conference on Computational Science (pp. 725–731). Springer, Berlin, Heidelberg.

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