Articles | Volume 15, issue 8
https://doi.org/10.5194/nhess-15-1721-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/nhess-15-1721-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Aug 2015
Research article |
| 04 Aug 2015
Towards predictive data-driven simulations of wildfire spread – Part II: Ensemble Kalman Filter for the state estimation of a front-tracking simulator of wildfire spread
M. C. Rochoux
CORRESPONDING AUTHOR
CERFACS, 42 avenue Gaspard Coriolis, 31057 Toulouse, CEDEX 01, France
SUC/CNRS-URA1875, 42 avenue Gaspard Coriolis, 31057 Toulouse, CEDEX 01, France
Ecole Centrale Paris, Grande Voie des Vignes, 92295 Châtenay-Malabry, France
EM2C/CNRS-UPR288, Grande Voie des Vignes, 92295 Châtenay-Malabry, France
C. Emery
CERFACS, 42 avenue Gaspard Coriolis, 31057 Toulouse, CEDEX 01, France
SUC/CNRS-URA1875, 42 avenue Gaspard Coriolis, 31057 Toulouse, CEDEX 01, France
Dept. of Fire Protection Engineering, University of Maryland, College Park, Maryland, MD 20742, USA
S. Ricci
CERFACS, 42 avenue Gaspard Coriolis, 31057 Toulouse, CEDEX 01, France
SUC/CNRS-URA1875, 42 avenue Gaspard Coriolis, 31057 Toulouse, CEDEX 01, France
B. Cuenot
CERFACS, 42 avenue Gaspard Coriolis, 31057 Toulouse, CEDEX 01, France
A. Trouvé
Dept. of Fire Protection Engineering, University of Maryland, College Park, Maryland, MD 20742, USA
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Cited
37 citations as recorded by crossref.
- Data Assimilation of Wildfires with Fuel Adjustment Factors in farsite using Ensemble Kalman Filtering * *This work is funded by NSF 1331615 under CI, Information Technology Research and SEES Hazards programs T. Srivas et al. 10.1016/j.procs.2017.05.197
- Inferring energy incident on sensors in low-intensity surface fires from remotely sensed radiation and using it to predict tree stem injury M. Dickinson et al. 10.1071/WF18164
- Experimental study of krone burning parameters of the most common trees in Vietnam S. Puzach & L. Tuan 10.18322/PVB.2019.28.06.10-17
- Dynamic correction of forest fire spread prediction using observation error covariance matrix estimation technique based on FLC-GRU T. Wu et al. 10.1186/s42408-024-00329-0
- A Data-Driven Fire Spread Simulator: Validation in Vall-llobrega's Fire O. Rios et al. 10.3389/fmech.2019.00008
- Mapping wildfire ignition probability and predictor sensitivity with ensemble-based machine learning Q. Tong & T. Gernay 10.1007/s11069-023-06172-x
- Wildland Fire Detection and Monitoring Using a Drone-Collected RGB/IR Image Dataset X. Chen et al. 10.1109/ACCESS.2022.3222805
- Application of the EnKF method for real-time forecasting of smoke movement during tunnel fires J. Ji et al. 10.1016/j.advengsoft.2017.10.007
- Topological data assimilation using Wasserstein distance L. Li et al. 10.1088/1361-6420/aae993
- Developing a geospatial data-driven solution for rapid natural wildfire risk assessment B. Adhikari et al. 10.1016/j.apgeog.2020.102382
- Combined estimation of fire perimeters and fuel adjustment factors in FARSITE for forecasting wildland fire propagation T. Zhou et al. 10.1016/j.firesaf.2020.103167
- Thermal Infrared Video Stabilization for Aerial Monitoring of Active Wildfires M. Valero et al. 10.1109/JSTARS.2021.3059054
- Subgrid-scale fire front reconstruction for ensemble coupled atmosphere-fire simulations of the FireFlux I experiment A. Costes et al. 10.1016/j.firesaf.2021.103475
- Wildland Fire Spread Modeling Using Convolutional Neural Networks J. Hodges & B. Lattimer 10.1007/s10694-019-00846-4
- State-parameter estimation approach for data-driven wildland fire spread modeling: Application to the 2012 RxCADRE S5 field-scale experiment C. Zhang et al. 10.1016/j.firesaf.2019.03.009
- A Multi-observable Approach to Address the Ill-Posed Nature of Inverse Fire Modeling Problems M. Price et al. 10.1007/s10694-015-0541-7
- VWETKF for wildfire propagation prediction employing observations with missing values and/or spatial variations of error variance T. Zhou et al. 10.1016/j.proci.2020.05.028
- Selection justification of the wood pulp and crown combustion parameters for the calculation of the crown forest fires impact on Vietnamese energy facilities L. Tuan et al. 10.1051/e3sconf/202342004022
- The distributed strategy for asynchronous observations in data-driven wildland fire spread prediction M. Zha et al. 10.1071/WF23165
- Orthorectification of Helicopter-Borne High Resolution Experimental Burn Observation from Infra Red Handheld Imagers R. Paugam et al. 10.3390/rs13234913
- Automated location of active fire perimeters in aerial infrared imaging using unsupervised edge detectors M. Valero et al. 10.1071/WF17093
- On the merits of sparse surrogates for global sensitivity analysis of multi-scale nonlinear problems: Application to turbulence and fire-spotting model in wildland fire simulators A. Trucchia et al. 10.1016/j.cnsns.2019.02.002
- Rate of spread and flaming zone velocities of surface fires from visible and thermal image processing B. Schumacher et al. 10.1071/WF21122
- A power series formulation for two-dimensional wildfire shapes J. Hilton et al. 10.1071/WF15191
- Numerical study of fire spread using the level-set method with large eddy simulation incorporating detailed chemical kinetics gas-phase combustion model T. Chen et al. 10.1016/j.jocs.2017.10.022
- Front shape similarity measure for data-driven simulations of wildland fire spread based on state estimation: Application to the RxCADRE field-scale experiment C. Zhang et al. 10.1016/j.proci.2018.07.112
- Wildfire Spread Prediction and Assimilation for FARSITE Using Ensemble Kalman Filtering 1 T. Srivas et al. 10.1016/j.procs.2016.05.328
- A Deep Learning Approach to Downscale Geostationary Satellite Imagery for Decision Support in High Impact Wildfires N. McCarthy et al. 10.3390/f12030294
- An Historical Review of the Simplified Physical Fire Spread Model PhyFire: Model and Numerical Methods M. Asensio et al. 10.3390/app13042035
- Kalman Filter-Based Large-Scale Wildfire Monitoring With a System of UAVs Z. Lin et al. 10.1109/TIE.2018.2823658
- Ensemble transform Kalman filter (ETKF) for large-scale wildland fire spread simulation using FARSITE tool and state estimation method T. Zhou et al. 10.1016/j.firesaf.2019.02.009
- Application of a CA-based model to predict the fire front in Hyrcanian forests of Iran S. Eskandari 10.1007/s12517-016-2717-y
- Short-term fire front spread prediction using inverse modelling and airborne infrared images O. Rios et al. 10.1071/WF16031
- Evaluation of a data-driven wildland fire spread forecast model with spatially-distributed parameter estimation in simulations of the FireFlux I field-scale experiment C. Zhang et al. 10.1016/j.firesaf.2017.03.057
- Modelling wildland fire propagation by tracking random fronts G. Pagnini & A. Mentrelli 10.5194/nhess-14-2249-2014
- Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires I. Altintas et al. 10.1016/j.procs.2015.05.296
- Towards predictive data-driven simulations of wildfire spread – Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation M. Rochoux et al. 10.5194/nhess-14-2951-2014
34 citations as recorded by crossref.
- Data Assimilation of Wildfires with Fuel Adjustment Factors in farsite using Ensemble Kalman Filtering * *This work is funded by NSF 1331615 under CI, Information Technology Research and SEES Hazards programs T. Srivas et al. 10.1016/j.procs.2017.05.197
- Inferring energy incident on sensors in low-intensity surface fires from remotely sensed radiation and using it to predict tree stem injury M. Dickinson et al. 10.1071/WF18164
- Experimental study of krone burning parameters of the most common trees in Vietnam S. Puzach & L. Tuan 10.18322/PVB.2019.28.06.10-17
- Dynamic correction of forest fire spread prediction using observation error covariance matrix estimation technique based on FLC-GRU T. Wu et al. 10.1186/s42408-024-00329-0
- A Data-Driven Fire Spread Simulator: Validation in Vall-llobrega's Fire O. Rios et al. 10.3389/fmech.2019.00008
- Mapping wildfire ignition probability and predictor sensitivity with ensemble-based machine learning Q. Tong & T. Gernay 10.1007/s11069-023-06172-x
- Wildland Fire Detection and Monitoring Using a Drone-Collected RGB/IR Image Dataset X. Chen et al. 10.1109/ACCESS.2022.3222805
- Application of the EnKF method for real-time forecasting of smoke movement during tunnel fires J. Ji et al. 10.1016/j.advengsoft.2017.10.007
- Topological data assimilation using Wasserstein distance L. Li et al. 10.1088/1361-6420/aae993
- Developing a geospatial data-driven solution for rapid natural wildfire risk assessment B. Adhikari et al. 10.1016/j.apgeog.2020.102382
- Combined estimation of fire perimeters and fuel adjustment factors in FARSITE for forecasting wildland fire propagation T. Zhou et al. 10.1016/j.firesaf.2020.103167
- Thermal Infrared Video Stabilization for Aerial Monitoring of Active Wildfires M. Valero et al. 10.1109/JSTARS.2021.3059054
- Subgrid-scale fire front reconstruction for ensemble coupled atmosphere-fire simulations of the FireFlux I experiment A. Costes et al. 10.1016/j.firesaf.2021.103475
- Wildland Fire Spread Modeling Using Convolutional Neural Networks J. Hodges & B. Lattimer 10.1007/s10694-019-00846-4
- State-parameter estimation approach for data-driven wildland fire spread modeling: Application to the 2012 RxCADRE S5 field-scale experiment C. Zhang et al. 10.1016/j.firesaf.2019.03.009
- A Multi-observable Approach to Address the Ill-Posed Nature of Inverse Fire Modeling Problems M. Price et al. 10.1007/s10694-015-0541-7
- VWETKF for wildfire propagation prediction employing observations with missing values and/or spatial variations of error variance T. Zhou et al. 10.1016/j.proci.2020.05.028
- Selection justification of the wood pulp and crown combustion parameters for the calculation of the crown forest fires impact on Vietnamese energy facilities L. Tuan et al. 10.1051/e3sconf/202342004022
- The distributed strategy for asynchronous observations in data-driven wildland fire spread prediction M. Zha et al. 10.1071/WF23165
- Orthorectification of Helicopter-Borne High Resolution Experimental Burn Observation from Infra Red Handheld Imagers R. Paugam et al. 10.3390/rs13234913
- Automated location of active fire perimeters in aerial infrared imaging using unsupervised edge detectors M. Valero et al. 10.1071/WF17093
- On the merits of sparse surrogates for global sensitivity analysis of multi-scale nonlinear problems: Application to turbulence and fire-spotting model in wildland fire simulators A. Trucchia et al. 10.1016/j.cnsns.2019.02.002
- Rate of spread and flaming zone velocities of surface fires from visible and thermal image processing B. Schumacher et al. 10.1071/WF21122
- A power series formulation for two-dimensional wildfire shapes J. Hilton et al. 10.1071/WF15191
- Numerical study of fire spread using the level-set method with large eddy simulation incorporating detailed chemical kinetics gas-phase combustion model T. Chen et al. 10.1016/j.jocs.2017.10.022
- Front shape similarity measure for data-driven simulations of wildland fire spread based on state estimation: Application to the RxCADRE field-scale experiment C. Zhang et al. 10.1016/j.proci.2018.07.112
- Wildfire Spread Prediction and Assimilation for FARSITE Using Ensemble Kalman Filtering 1 T. Srivas et al. 10.1016/j.procs.2016.05.328
- A Deep Learning Approach to Downscale Geostationary Satellite Imagery for Decision Support in High Impact Wildfires N. McCarthy et al. 10.3390/f12030294
- An Historical Review of the Simplified Physical Fire Spread Model PhyFire: Model and Numerical Methods M. Asensio et al. 10.3390/app13042035
- Kalman Filter-Based Large-Scale Wildfire Monitoring With a System of UAVs Z. Lin et al. 10.1109/TIE.2018.2823658
- Ensemble transform Kalman filter (ETKF) for large-scale wildland fire spread simulation using FARSITE tool and state estimation method T. Zhou et al. 10.1016/j.firesaf.2019.02.009
- Application of a CA-based model to predict the fire front in Hyrcanian forests of Iran S. Eskandari 10.1007/s12517-016-2717-y
- Short-term fire front spread prediction using inverse modelling and airborne infrared images O. Rios et al. 10.1071/WF16031
- Evaluation of a data-driven wildland fire spread forecast model with spatially-distributed parameter estimation in simulations of the FireFlux I field-scale experiment C. Zhang et al. 10.1016/j.firesaf.2017.03.057
3 citations as recorded by crossref.
- Modelling wildland fire propagation by tracking random fronts G. Pagnini & A. Mentrelli 10.5194/nhess-14-2249-2014
- Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires I. Altintas et al. 10.1016/j.procs.2015.05.296
- Towards predictive data-driven simulations of wildfire spread – Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation M. Rochoux et al. 10.5194/nhess-14-2951-2014
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Latest update: 21 Nov 2024
Short summary
This paper, the second part in a series of two articles, aims at presenting a data-driven modeling strategy for forecasting
wildfire spread scenarios based on the assimilation of the observed
fire front location and on the sequential correction of model parameters
or model state. The objective here is to sequentially update the fire front location in order to provide a more reliable initial condition for further model integration and forecast.
This paper, the second part in a series of two articles, aims at presenting a data-driven...
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