The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Prediction of Fire Spread in Grasslands
Abstract
This pager describes a model to predict fire spread in grasslands from wind speed at 10 m, dead fuel moisture, and degree of grass curing in three defined pasture types, The model was developed from spread measurements of experimental fins that were adjusted to their potential rate of spread at wide fronts. Extrapolations of the model were compared with spread data from 20 major wildfires in Australia. This model uses different functions to describe the relationship between rate of spread and wind speed above and below a critical wind speed of 5 km h-1. A linear relationship is used below 5 km h-1; above 5 km h-1 rate of spread is described by a power function of wind speed with an exponent of less than 1.
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Cites
Classical and Modern Regression With Applications.
Steinhorst, R. K., & Myers, R. H. (1988) · Journal of the American Statistical Association · doi:10.2307/2288958 · Cited by 3,690
Norussis, H. (1993) · Medical Entomology and Zoology · Cited by 2,704
A mathematical model for predicting fire spread in wildland fuels
Rothermel, R. C. (1972) · doi:10.2737/int-rp-115 · Cited by 2,247
McArthur's fire‐danger meters expressed as equations
NOBLE, I. R., GILL, A. M., & BARY, G. A. V. (1980) · Australian Journal of Ecology · doi:10.1111/j.1442-9993.1980.tb01243.x · Cited by 725
SPSS for Windows: Advanced Statistics Release 5
Norušis, M. J. (1992) · Medical Entomology and Zoology · Cited by 636
The Influence of Fuel, Weather and Fire Shape Variables on Fire-Spread in Grasslands
Cheney, N., Gould, J., & Catchpole, W. (1993) · International Journal of Wildland Fire · doi:10.1071/wf9930031 · Cited by 391
Self-citationAnalysis of Fire Spread in Light Forest Fuels
Fons, W. L. (1946) · Journal of Agricultural Research · Cited by 241
The interaction of wind and fire
Beer, T. (1991) · Boundary-Layer Meteorology · doi:10.1007/bf00183958 · Cited by 183
Wind-Aided Firespread Across Arrays of Discrete Fuel Elements. II. Experiment
WOLFF, M. F., CARRIER, G. F., & FENDELL, F. E. (1991) · Combustion Science and Technology · doi:10.1080/00102209108951731 · Cited by 87
Influence of moisture and wind upon the characteristics of free-burning fires
Anderson, H. E., & Rothermel, R. C. (1965) · Symposium (International) on Combustion · doi:10.1016/s0082-0784(65)80243-0 · Cited by 85
Cited by
Wildland surface fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models
Sullivan, A. L. (2009) · International Journal of Wildland Fire · doi:10.1071/wf06142 · Cited by 408
Mathematical models and calculation systems for the study of wildland fire behaviour
Pastor, E. (2003) · Progress in Energy and Combustion Science · doi:10.1016/s0360-1285(03)00017-0 · Cited by 362
Combustion machine learning: Principles, progress and prospects
Ihme, M., Chung, W. T., & Mishra, A. A. (2022) · Progress in Energy and Combustion Science · doi:10.1016/j.pecs.2022.101010 · Cited by 265
Metadata
- Authors
- Cheney, N., Gould, J., & Catchpole, W.
- Venue
- International Journal of Wildland Fire
- Publisher
- CSIRO Publishing
- Published
- 1998-03-01
- Volume
- 8
- Issue
- 1
- Pages
- 1-13
- ISSN
- 1049-8001 (ISSN-L)
- 1448-5516
- OpenAlex
- W1990049406
- Cited by
- 390
- References
- 14
- FWCI
- 3.13
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
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.