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GPU-accelerated Optimization of Fuel Treatments for Mitigating Wildfire Hazard

Bachisio Arca, Tiziano Ghisu, William Spataro, Giuseppe A. Trunfio
2013 Procedia Computer Science  
Fuel treatment is considered a suitable way to mitigate the hazard related to potential wildfires on a landscape.  ...  Using an application example, we also show that the proposed methodology can provide high-quality design solutions in low computing time.  ...  For such purpose, we use the wildfire simulation model based on the Cellular Automata approach described in [13] .  ... 
doi:10.1016/j.procs.2013.05.262 fatcat:a6btpd5fm5cytnvjnaf75eeasy

A stochastic Forest Fire Model for future land cover scenarios assessment

M. D'Andrea, P. Fiorucci, T. P. Holmes
2010 Natural Hazards and Earth System Sciences  
In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency.  ...  The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM) produces simulations which reproduce this observed pattern.  ...  Finally, we would also like to thank Mike Wotton and the two anonymous referees whose comments greatly improved the quality of this work.  ... 
doi:10.5194/nhess-10-2161-2010 fatcat:jifdzqb24ffctdkojhubfig5ky

HexFire: A Flexible and Accessible Wildfire Simulator

Nathan H. Schumaker, Sydney M. Watkins, Julie A. Heinrichs
2022 Land  
Here we introduce a parsimonious wildfire simulator named HexFire that has been designed for rapid uptake by investigators who do not specialize in the mechanics of fire spread.  ...  HexFire can be used as a proxy for more detailed fire simulators and to assess the implications of wildfire for local ecological systems.  ...  Model Overview HexFire is an individual-based model (IBM) that functions in part as a cellular automaton [36] .  ... 
doi:10.3390/land11081288 fatcat:l7kwen6iyjdvhptf4e22h2cce4

Emergence of bottom-up models as a tool for landscape simulation and planning

Xia Li
2011 Landscape and Urban Planning  
Instead of using traditional top-down models, recent studies have shown that these complex natural systems can be effectively simulated by using a number of bottom-up models, such as cellular automaton  ...  Recently, a number of bottom-up models, such as cellular automaton models (CAs), agent-based models (ABMs), and swarm intelligence models (SIMs), have emerged as an important tool for assisting complex  ...  His recent research interests are to develop a theoretical framework that integrated cellular automata (CA), multi-agent systems (MAS) and swarm intelligence (SI) for simulating geographical processes  ... 
doi:10.1016/j.landurbplan.2010.11.016 fatcat:dad2xsesxjhivde5ih3z76ujcy

A review of recent advances in risk analysis for wildfire management

Carol Miller, Alan A. Ager
2013 International journal of wildland fire  
We also review recent advances in addressing temporal dynamics of fire risk and spatial optimisation of fuels management activities.  ...  We suggest several necessary and fruitful directions for future research and development in wildfire risk analysis.  ...  A cellular automaton fire spread model was used to generate burn probabilities that were used by a simulated annealing optimisation algorithm to locate forest treatments.  ... 
doi:10.1071/wf11114 fatcat:ptdad3wzy5b5rmufyhv3zzpxwu

Local and global pyrogeographic evidence that indigenous fire management creates pyrodiversity

Clay Trauernicht, Barry W. Brook, Brett P. Murphy, Grant J. Williamson, David M. J. S. Bowman
2015 Ecology and Evolution  
Acknowledgments The authors would like to thank the Rostron and Campion families and the Djelk Rangers in Arnhem Land, and  ...  We constructed a simple cellular automaton (CA), or lattice model, driven as a stochastic simulation, to examine the effects of fire size on the spatial and temporal heterogeneity of different 'aged' cells  ...  We then deployed a simple cellular automaton simulation model to explore how altering fire size, and therefore the spatial grain of fire occurrence, affects both spatial and temporal aspects of pyrodiversity  ... 
doi:10.1002/ece3.1494 pmid:26140206 pmcid:PMC4485971 fatcat:6xi2ol37zzarrfhrsy6rwvweki

Integrating cellular automata and discrete global grid systems: a case study into wildfire modelling

Majid Hojati, Colin Robertson
2020 AGILE: GIScience Series  
To do so, a case study into wildfire spread modelling is developed.  ...  a DGGS data model and (iii) evaluate an in-database approach for CA modelling.  ...  Chiranjib Chaudhuri for assistance with the model accuracy assessment and his comments that greatly improved the manuscript.  ... 
doi:10.5194/agile-giss-1-6-2020 fatcat:6knqqnoywbgvnafaidw5t5rjgy

PROPAGATOR: An Operational Cellular-Automata Based Wildfire Simulator

Andrea Trucchia, Mirko D'Andrea, Francesco Baghino, Paolo Fiorucci, Luca Ferraris, Dario Negro, Andrea Gollini, Massimiliano Severino
2020 Fire  
PROPAGATOR is a stochastic cellular automaton model for forest fire spread simulation, conceived as a rapid method for fire risk assessment.  ...  The fire-propagation speed is determined through the adoption of a Rate of Spread model.  ...  CA models for wildfire simulation model discretize spatial interactions by adopting a square or hexagonal [26] grid.  ... 
doi:10.3390/fire3030026 fatcat:curvixy7lbecdbgdsjof72edpi

Review of forest landscape models: Types, methods, development and applications

Weimin Xi, Robert N. Coulson, Andrew G. Birt, Zong-Bo Shang, John D. Waldron, Charles W. Lafon, David M. Cairns, Maria D. Tchakerian, Kier D. Klepzig
2009 Acta Ecologica Sinica  
Forest landscape models simulate forest change through time using spatially referenced data across a broad spatial scale (i.e. landscape scale) generally larger than a single forest stand.  ...  In this paper, we define forest landscape models and discuss development, components, and types of the models.  ...  David Mladenoff, Eric Gustason, Dean Urban, Robert Scheller, Brian Sturtevant, and Hong He for providing useful discussion, Ms.  ... 
doi:10.1016/j.chnaes.2009.01.001 fatcat:z5g2zohzsvfyjkzbh2u2nfckse

First steps towards a dynamical model for forest fire behaviour in Argentinian landscapes

Monica Denham, Karina Laneri, Viviana Zimmerman, Sigfrido Waidelich
2020 Journal of Computer Science and Technology  
We developed a Reaction Diffusion Convection (RDC) model for forest fire propagation coupled to a visualization platform with several functionalities requested by local firefighters.  ...  We'll show in this work the first tests considering combustion and diffusion in artificial landscapes.  ...  We thank A. B. Kolton for fruitful discussions about the model. M. Denham and K. Laneri are members of Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). M. Denham, K. Laneri, V.  ... 
doi:10.24215/16666038.20.e09 fatcat:2vjd5hofhnau5ghabl2kim7wqm

Using Spatial Reinforcement Learning to Build Forest Wildfire Dynamics Models From Satellite Images

Sriram Ganapathi Subramanian, Mark Crowley
2018 Frontiers in ICT  
Meanwhile, we learn an agent policy for a predictive model of the dynamics of a complex spatial process.  ...  One thing these domains have in common is that they contain dynamics that can be characterized as a spatially spreading process (SSP), which requires many parameters to be set precisely to model the dynamics  ...  Cellular automaton models are also widely used to predict wildfire spread (Yongzhong et al., 2004) . Our approach is easier to apply than these methods and is shown to perform better than the same.  ... 
doi:10.3389/fict.2018.00006 fatcat:yidh2lgm2bcrvol3a5hpbrkmlm

Forest Economics, Natural Disturbances and the New Ecology [chapter]

Thomas P. Holmes, Robert J. Huggett, John M. Pye
2008 Forestry sciences  
A cellular automaton uses a d-dimensional lattice with L d regularly spaced cells to represent the spatial organization of the ecosystem.  ...  Rather, we focus our attention on a recent innovation in spatial modeling, cellular automata, that utilizes Monte Carlo simulation to analyze spatial pattern.  ... 
doi:10.1007/978-1-4020-4370-3_2 fatcat:eqxgqm2gpzgnldiizunmpadyte

Using cellular automata to simulate wildfire propagation and to assist in fire management

Joana Gouveia Freire, Carlos Castro DaCamara
2019 Natural Hazards and Earth System Sciences  
We present a cellular automaton designed to simulate a severe wildfire episode that took place in Algarve (southern Portugal) in July 2012.  ...  Cellular automata have been successfully applied to simulate the propagation of wildfires with the aim of assisting fire managers in defining fire suppression tactics and in planning fire risk management  ...  DaCamara: Using cellular automata to simulate wildfire propagation  ... 
doi:10.5194/nhess-19-169-2019 fatcat:lkkdtnr6kfa2tcu6zm7wpekuy4

A hierarchical cellular automaton model of distributed traffic signal control [article]

Bartłomiej Płaczek
2018 arXiv   pre-print
This paper introduces a hierarchical cellular automaton (HCA)model for simulation of distributed self-organizing control of traffic signals at intersections in road network.  ...  Simulation experiments were conducted for a wide range of traffic conditions - from free flow to saturated traffic in two scenarios: anhattan-like grid road network, and arterial road.  ...  This approach was used to develop models of wildfire spread [7] and invasive plant spread [8] .  ... 
arXiv:1809.10892v1 fatcat:y7qzzyuam5gqvl3qy77a2py5y4

A review of machine learning applications in wildfire science and management [article]

Piyush Jain, Sean C P Coogan, Sriram Ganapathi Subramanian, Mark Crowley, Steve Taylor, Mike D Flannigan
2020 arXiv   pre-print
We first present an overview of popular ML approaches used in wildfire science to date, and then review their use in wildfire science within six problem domains: 1) fuels characterization, fire detection  ...  However, despite the ability of ML models to learn on their own, expertise in wildfire science is necessary to ensure realistic modelling of fire processes across multiple scales, while the complexity  ...  Acknowledgments The motivation for this paper arose from the "Not the New Normal" BC AI Wildfire Symposium held in Vancouver, BC, on 12 October 2018.  ... 
arXiv:2003.00646v1 fatcat:5ufhtbwlsvd2rdk3ogbmqpnxuu
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