Real-Time Data Driven Wildland Fire Modeling

We are developing a wildland fire model based on semi-empirical relations that estimate the rate of spread of a surface fire and post-frontal heat release, coupled with WRF, the Weather Research and Forecasting atmospheric model. A level set method identifies the fire front. Data are assimilated using both amplitude and position corrections using a morphing ensemble Kalman filter. We will use thermal images of a fire for observations that will be compared to synthetic image based on the model state.

• Publication year

  2008

• Venue

  International Conference on Conceptual Structures

• Publication date

  2008-02-12

• Fields of study

  Physics, Computer Science, Environmental Science

• Identifiers
  DOI 10.1007/978-3-540-69389-5_7arXiv 0802.1615
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• DATA ASSIMILATION AND VISUALIZATION FOR ENSEMBLE WILDLAND FIRE MODELS

  2008cited by this paper
• A two-stage ensemble Kalman filter for smooth data assimilation

  2008cited by this paper
• Modeling wildland fire propagation with level set methods

  2007cited by this paper
• A Dynamic Data Driven Wildland Fire Model

  2007cited by this paper
• Modeling Wildland Fire Radiance in Synthetic Remote Sensing Scenes

  2007cited by this paper
• Data assimilation for wildland fires

  2007cited by this paper
• A wildland fire model with data assimilation

  2007cited by this paper
• A Wildfire Model with Data Assimilation

  2007cited by this paper
• Data assimilation by field alignment

  2007cited by this paper
• Morphing ensemble Kalman filters

  2007cited by this paper
• Simulation of the Big Elk Fire using coupled atmosphere–fire modeling

  2005cited by this paper
• Description of a coupled atmosphere–fire model

  2004cited by this paper
• Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products.

  2003cited by this paper
• The Ensemble Kalman Filter: theoretical formulation and practical implementation

  2003influential reference
• Level set methods and dynamic implicit surfaces

  2002cited by this paper
• Atmospheric Modeling, Data Assimilation and Predictability

  2002cited by this paper
• An Advanced Synthetic Image Generation Model and its Application to Multi/Hyperspectral Algorithm Development

  1999cited by this paper

• Other Positions

  2021cites this paper
• Étude numérique et asymptotique d'une approche couplée pour la simulation de la propagation de feux de forêt avec l'effet du vent en terrain complexe

  2018influential citation
• Introduction to Dynamic Data Driven Applications Systems

  2018cites this paper
• Fire Spotting Effects in Wildland Fire Propagation

  2014cites this paper
• Modelling turbulence effects in wildland fire propagation by the randomized level-set method

  2014cites this paper
• Modelling wildland fire propagation by tracking random fronts

  2013cites this paper
• Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling

  2013cites this paper
• Assimilation of Perimeter Data and Coupling with Fuel Moisture in a Wildland Fire-Atmosphere DDDAS

  2012cites this paper