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Self-organized critical forest-fire model
Abstract
A forest-fire model is introduced which contains a lightning probability f. This leads to a self-organized critical state in the limit f\ensuremath{\rightarrow}0 provided that the time scales of tree growth and burning down of forest clusters are separated. We derive scaling laws and calculate all critical exponents. The values of the critical exponents are confirmed by computer simulations. For a two-dimensional system, we show that the forest density in the critical state assumes its minimum possible value, i.e., that energy dissipation is maximum.
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Citations
Cited by
Newman (2005) · doi:10.1080/00107510500052444 · Cited by 5,749
Characterizing wildfire regimes in the United States
Malamud, B. D., Millington, J. D. A., & Perry, G. L. W. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0500880102 · Cited by 259
Anthropogenic effects on global mean fire size
Hantson, S., Lasslop, G., Kloster, S., & Chuvieco, E. (2015) · International Journal of Wildland Fire · doi:10.1071/wf14208 · Cited by 62
A stochastic Forest Fire Model for future land cover scenarios assessment
D'Andrea, M., Fiorucci, P., & Holmes, T. P. (2010) · Natural Hazards and Earth System Sciences · doi:10.5194/nhess-10-2161-2010 · Cited by 6
Metadata
- Authors
- Drossel, B., & Schwabl, F.
- Venue
- Physical Review Letters
- Publisher
- American Physical Society (APS)
- Published
- 1992-09-14
- Volume
- 69
- Issue
- 11
- Pages
- 1629-1632
- ISSN
- 0031-9007 (ISSN-L)
- OpenAlex
- W2003320658
- Cited by
- 732
- References
- 0
- FWCI
- 8.53
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
