Articles | Volume 19, issue 1
https://doi.org/10.5194/nhess-19-169-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-19-169-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Jan 2019
Research article |
| 22 Jan 2019
| 22 Jan 2019
Using cellular automata to simulate wildfire propagation and to assist in fire management
Instituto Dom Luiz (IDL), Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
Carlos Castro DaCamara
Instituto Dom Luiz (IDL), Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisbon, Portugal
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Cited
33 citations as recorded by crossref.
- Efficient simulation execution of cellular automata on GPU D. Cagigas-Muñiz et al. 10.1016/j.simpat.2022.102519
- A Generative Model for Surrogates of Spatial-Temporal Wildfire Nowcasting S. Cheng et al. 10.1109/TETCI.2023.3298535
- Using cellular automata in modelling of the fire front propagation through rough terrain A. Pavlova et al. 10.1088/1755-1315/579/1/012104
- Spatially extended radiant heat fire model J. McDanold & N. Malik 10.1103/PhysRevE.107.034133
- Resilient multipath routing protocol to enable hazardous event monitoring with wireless sensor network B. Üveges et al. 10.5937/telfor2301020Q
- An environmental modelling framework based on asynchronous many-tasks: Scalability and usability K. de Jong et al. 10.1016/j.envsoft.2021.104998
- Multi-Scale 3d Cellular Automata Modeling: Application to Wildland Fire Spread m. byari et al. 10.2139/ssrn.4046576
- Simulating forest fire spread and fire-fighting using cellular automata K. Mutthulakshmi et al. 10.1016/j.cjph.2020.04.001
- Modeling Forest Fire Spread Using Machine Learning-Based Cellular Automata in a GIS Environment Y. Xu et al. 10.3390/f13121974
- Engineering ethical behaviors in autonomous industrial cyber-physical human systems D. Trentesaux & S. Karnouskos 10.1007/s10111-020-00657-6
- AutoST-Net: A Spatiotemporal Feature-Driven Approach for Accurate Forest Fire Spread Prediction from Remote Sensing Data X. Chen et al. 10.3390/f15040705
- Ex Post Project Risk Assessment: Method and Empirical Study A. Erfani et al. 10.1061/JCEMD4.COENG-12588
- Drone Swarms in Fire Suppression Activities: A Conceptual Framework E. Ausonio et al. 10.3390/drones5010017
- A Novel Hybrid Approach Based on Cellular Automata and a Digital Elevation Model for Rapid Flood Assessment O. Wijaya & T. Yang 10.3390/w13091311
- Fire-spotting modelling in operational wildfire simulators based on Cellular Automata: A comparison study M. López-De-Castro et al. 10.1016/j.agrformet.2024.109989
- Operational Application of Mathematical Modeling for Enhanced Wildfire Risk Management in Liguria F. Baghino et al. 10.1016/j.ifacol.2024.07.092
- A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images M. Pinto et al. 10.1016/j.isprsjprs.2019.12.014
- Parameter Flexible Wildfire Prediction Using Machine Learning Techniques: Forward and Inverse Modelling S. Cheng et al. 10.3390/rs14133228
- Cellular automata modeling of processes on landscape surfaces using triangulation meshes M. Domasevich et al. 10.1088/1755-1315/867/1/012017
- Pyros: a raster–vector spatial simulation model for predicting wildland surface fire spread and growth D. Voltolina et al. 10.1071/WF22142
- The Signature of Climate in Annual Burned Area in Portugal C. DaCamara 10.3390/cli12090143
- Forest fire spreading: A nonlinear stochastic model continuous in space and time R. Beneduci & G. Mascali 10.1111/sapm.12696
- The process of complex societies: dynamic models beyond site-size hierarchies M. Smith 10.1080/00438243.2021.1965015
- A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management S. Boroujeni et al. 10.1016/j.inffus.2024.102369
- PROPAGATOR: An Operational Cellular-Automata Based Wildfire Simulator A. Trucchia et al. 10.3390/fire3030026
- Modeling and simulation analysis of crowd evacuation behavior under terrorist attack J. Liu et al. 10.1016/j.physa.2022.127891
- Peculiarities of Computer Modeling of Thought Dissemination in Society on the Example of Student Society V. Shevchenko et al. 10.15407/pp2021.04.070
- Multi-scale 3D cellular automata modeling: Application to wildland fire spread M. Byari et al. 10.1016/j.chaos.2022.112653
- Multi-Period Power System Risk Minimization Under Wildfire Disruptions H. Yang et al. 10.1109/TPWRS.2023.3339147
- Discrete Wildfire Simulation Case Study M. Schuster 10.1109/MCSE.2023.3329413
- A comprehensive taxonomy of cellular automata M. Rollier et al. 10.1016/j.cnsns.2024.108362
- A Practical Method for High-Resolution Burned Area Monitoring Using Sentinel-2 and VIIRS M. Pinto et al. 10.3390/rs13091608
- Performance Analysis of ConvLSTM, FlamMap, and CA Algorithms to Predict Wildfire Spread in Golestan National Park, NE Iran M. Khalaf et al. 10.1007/s10666-024-09956-y
32 citations as recorded by crossref.
- Efficient simulation execution of cellular automata on GPU D. Cagigas-Muñiz et al. 10.1016/j.simpat.2022.102519
- A Generative Model for Surrogates of Spatial-Temporal Wildfire Nowcasting S. Cheng et al. 10.1109/TETCI.2023.3298535
- Using cellular automata in modelling of the fire front propagation through rough terrain A. Pavlova et al. 10.1088/1755-1315/579/1/012104
- Spatially extended radiant heat fire model J. McDanold & N. Malik 10.1103/PhysRevE.107.034133
- Resilient multipath routing protocol to enable hazardous event monitoring with wireless sensor network B. Üveges et al. 10.5937/telfor2301020Q
- An environmental modelling framework based on asynchronous many-tasks: Scalability and usability K. de Jong et al. 10.1016/j.envsoft.2021.104998
- Multi-Scale 3d Cellular Automata Modeling: Application to Wildland Fire Spread m. byari et al. 10.2139/ssrn.4046576
- Simulating forest fire spread and fire-fighting using cellular automata K. Mutthulakshmi et al. 10.1016/j.cjph.2020.04.001
- Modeling Forest Fire Spread Using Machine Learning-Based Cellular Automata in a GIS Environment Y. Xu et al. 10.3390/f13121974
- Engineering ethical behaviors in autonomous industrial cyber-physical human systems D. Trentesaux & S. Karnouskos 10.1007/s10111-020-00657-6
- AutoST-Net: A Spatiotemporal Feature-Driven Approach for Accurate Forest Fire Spread Prediction from Remote Sensing Data X. Chen et al. 10.3390/f15040705
- Ex Post Project Risk Assessment: Method and Empirical Study A. Erfani et al. 10.1061/JCEMD4.COENG-12588
- Drone Swarms in Fire Suppression Activities: A Conceptual Framework E. Ausonio et al. 10.3390/drones5010017
- A Novel Hybrid Approach Based on Cellular Automata and a Digital Elevation Model for Rapid Flood Assessment O. Wijaya & T. Yang 10.3390/w13091311
- Fire-spotting modelling in operational wildfire simulators based on Cellular Automata: A comparison study M. López-De-Castro et al. 10.1016/j.agrformet.2024.109989
- Operational Application of Mathematical Modeling for Enhanced Wildfire Risk Management in Liguria F. Baghino et al. 10.1016/j.ifacol.2024.07.092
- A deep learning approach for mapping and dating burned areas using temporal sequences of satellite images M. Pinto et al. 10.1016/j.isprsjprs.2019.12.014
- Parameter Flexible Wildfire Prediction Using Machine Learning Techniques: Forward and Inverse Modelling S. Cheng et al. 10.3390/rs14133228
- Cellular automata modeling of processes on landscape surfaces using triangulation meshes M. Domasevich et al. 10.1088/1755-1315/867/1/012017
- Pyros: a raster–vector spatial simulation model for predicting wildland surface fire spread and growth D. Voltolina et al. 10.1071/WF22142
- The Signature of Climate in Annual Burned Area in Portugal C. DaCamara 10.3390/cli12090143
- Forest fire spreading: A nonlinear stochastic model continuous in space and time R. Beneduci & G. Mascali 10.1111/sapm.12696
- The process of complex societies: dynamic models beyond site-size hierarchies M. Smith 10.1080/00438243.2021.1965015
- A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management S. Boroujeni et al. 10.1016/j.inffus.2024.102369
- PROPAGATOR: An Operational Cellular-Automata Based Wildfire Simulator A. Trucchia et al. 10.3390/fire3030026
- Modeling and simulation analysis of crowd evacuation behavior under terrorist attack J. Liu et al. 10.1016/j.physa.2022.127891
- Peculiarities of Computer Modeling of Thought Dissemination in Society on the Example of Student Society V. Shevchenko et al. 10.15407/pp2021.04.070
- Multi-scale 3D cellular automata modeling: Application to wildland fire spread M. Byari et al. 10.1016/j.chaos.2022.112653
- Multi-Period Power System Risk Minimization Under Wildfire Disruptions H. Yang et al. 10.1109/TPWRS.2023.3339147
- Discrete Wildfire Simulation Case Study M. Schuster 10.1109/MCSE.2023.3329413
- A comprehensive taxonomy of cellular automata M. Rollier et al. 10.1016/j.cnsns.2024.108362
- A Practical Method for High-Resolution Burned Area Monitoring Using Sentinel-2 and VIIRS M. Pinto et al. 10.3390/rs13091608
Latest update: 20 Nov 2024
Short summary
Cellular automata are useful tools to simulate wildfire propagation. We design a cellular automaton to simulate a severe wildfire that took place in Portugal in 2012 and resulted in almost 25 000 ha burned. The explosive stage is adequately modeled when refining the role played by the wind in fire spreading. Results show a probability of ignition out of the limits of the observed scar, information that may help choose where to allocate resources for firefighting.
Cellular automata are useful tools to simulate wildfire propagation. We design a cellular...
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