Pixel-level statistical analyses of prescribed fire spread-Reference-Cited by-同舟云学术

Pixel-level statistical analyses of prescribed fire spread

Published:2019-01 Issue:1 Volume:49 Page:18-26
ISSN:0045-5067
Container-title:Canadian Journal of Forest Research
language:en
Short-container-title:Can. J. For. Res.

Author:

Currie M.¹,Speer K.¹²,Hiers J.K.³,O’Brien J.J.⁴,Goodrick S.⁴,Quaife B.¹⁵

Affiliation:

1. Geophysical Fluid Dynamics Institute, Florida State University, Tallahassee, FL, USA.

2. Department of Earth, Ocean and Atmospheric Sciences, Florida State University, Tallahassee, FL, USA.

3. Tall Timbers Research Station, Tallahassee, FL, USA.

4. U.S. Forest Service, Southern Research Station, Athens, GA, USA.

5. Department of Scientific Computing, Florida State University, Tallahassee, FL, USA.

Abstract

Wildland fire dynamics are a complex three-dimensional turbulent process. Cellular automata (CA) is an efficient tool to predict fire dynamics, but the main parameters of the method are challenging to estimate. To overcome this challenge, we compute statistical distributions of the key parameters of a CA model using infrared images from controlled burns. Moreover, we apply this analysis to different spatial scales and compare the experimental results with a simple statistical model. By performing this analysis and making this comparison, several capabilities and limitations of CA are revealed.

Publisher

Canadian Science Publishing

Subject

Ecology,Forestry,Global and Planetary Change

Link

http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfr-2017-0452

Reference29 articles.

1. Planned Burn-Piedmont. A local operational numerical meteorological model for tracking smoke on the ground at night: model development and sensitivity tests

2. Field validation of a free-agent cellular automata model of fire spread with fire - atmosphere coupling

3. Fire propagation in a 2-D random medium

4. Stochastic cellular automata model for wildland fire spread dynamics

5. Current status and future needs of the BehavePlus Fire Modeling System

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven modeling of wildfire spread with stochastic cellular automata and latent spatio-temporal dynamics;Spatial Statistics;2024-03

2. Deep hierarchical generalized transformation models for spatio-temporal data with discrepancy errors;Spatial Statistics;2023-06

3. Modeling Forest Fire Spread Using Machine Learning-Based Cellular Automata in a GIS Environment;Forests;2022-11-22

4. Fine-Scale Fire Spread in Pine Straw;Fire;2021-10-10

5. A Simple Model for Wildland Fire Vortex–Sink Interactions;Atmosphere;2021-08-07