Generation of synthetic infrared remote-sensing scenes of wildland fire

Zhen Wang; Anthony Vodacek; Janice Coen

doi:10.1071/WF08089

RESEARCH ARTICLE

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Generation of synthetic infrared remote-sensing scenes of wildland fire

Zhen Wang ^A , Anthony Vodacek ^A ^C and Janice Coen ^B

+ Author Affiliations

- Author Affiliations

^A Center for Imaging Science, Rochester Institute of Technology, 54 Lomb Memorial Drive, Rochester, NY 14623, USA.

^B National Center for Atmospheric Research, PO Box 3000, Boulder, CO 80307, USA.

^C Corresponding author. Email: vodacek@cis.rit.edu

International Journal of Wildland Fire 18(3) 302-309 https://doi.org/10.1071/WF08089
Submitted: 29 May 2007 Accepted: 16 May 2008 Published: 28 May 2009

Abstract

We describe a method for generating synthetic infrared remote-sensing scenes of wildland fire. These synthetic scenes are an important step in data assimilation, which is defined as the process of incorporating new data into an executing model. In our case, this is a fire propagation model. The scenes are built using the surface output of fire position from a fire propagation code and prior knowledge of fire physics and behavior to estimate the shape of the flame. The scene radiance is then estimated by employing a physics-based ray-tracing model called DIRSIG to render the radiation that would reach a sensor on an airborne platform. Values of the Fire Radiated Energy calculated from the synthetic radiance scene compare well with previously published values, providing validation of the method.

Additional keywords: DIRSIG, fire propagation models, fire radiative energy, flame height, heat flux.

Acknowledgements

The present material is based on work supported by the National Science Foundation under grant numbers CNS-0324989 and CNS-0324910 and by the National Aeronautics and Space Administration under grant number NAG5–10051.

References

Ambrosia V, Wegener S, Sullivan D, Buechel S, Dunagan S, Brass J, Stoneburner J , Schoenung S (2003) Demonstrating UAV-acquired real-time thermal data over fires. Photogrammetric Engineering and Remote Sensing 69, 391–402.
Anderson GP, Berk A, Acharya PK, Matthew MW, Bernstein LS, Chetwynd JH, Dothe H, Adler-Golden SM, Ratkowski AJ, Felde GW, Gardner JA, Hoke ML, Richtsmeier SC, Pukall B, Mello J, Jeong LS (2000) MODTRAN4: Radiative transfer modeling for remote sensing. In ‘Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VI’. (Eds SS Chen, MR Descour) Proceedings of SPIE, Vol. 4049, pp. 176–183. (SPIE: Bellingham, WA)

Anderson JL (1996) A method of producing and evaluating probabilistic forecasts from ensemble model integrations. Journal of Climate 9, 1518–1530.
| Crossref | GoogleScholarGoogle Scholar | Brown AA, Davis KP (1973) ‘Forest fire control and use.’ 2nd edn. (McGraw-Hill: New York)

Clark TL, Jenkins MA, Coen J , Packham D (1996) A coupled atmosphere–fire model: convective feedback on fire-line dynamics. Journal of Applied Meteorology 35, 875–901.
| Crossref | GoogleScholarGoogle Scholar | Digital Imaging and Remote Sensing Laboratory (2006) ‘The DIRSIG User’s Manual.’ (Rochester Institute of Technology: Rochester, NY) Available at http://www.dirsig.org/docs/manual-2006-11.pdf [Verified 30 April 2009]

Douglas CC, Beezley JD, Coen J, Li D, Li W, Mandel AK, Mandel J, Qin G , Vodacek A (2006) Demonstrating the validity of a wildfire DDDAS. Lecture Notes in Computer Science 3993, 522–529.
| Crossref | GoogleScholarGoogle Scholar | Drysdale D (1998) ‘An Introduction to Fire Dynamics.’ 2nd edn. (Wiley: Chichester, UK)

Finney MA (1998) FARSITE: Fire Area Simulator-Model, development and evaluation. USDA Forest Service, Rocky Mountain Research Station Paper, RMRS-RP-4. (Ogden, UT)

Greenfield PH, Smith W, Chamberlain DC (2003) Phoenix – the new Forest Service airborne infrared fire detection and mapping system. In ‘5th Symposium on Fire and Forest Meteorology and the 2nd International Wildland Fire Ecology and Fire Management Congress’, 16–20 November 2003, Orlando, FL. Paper J1G.3. (American Meteorological Society: Boston, MA)

Kaufman Y, Remer L, Ottmar R, Ward D, Li R-R, Kleidman R, Fraser R, Flynn L, McDougal D, Shelton G (1996) Relationship between remotely sensed fire intensity and rate of emission of smoke: SCAR-C experiment. In ‘Global Biomass Burning’. (Ed. J Levine) pp. 685–696. (MIT Press: Cambridge, MA)

Knight IK , Sullivan AL (2004) A semi-transparent model of bushfire flames to predict radiant heat flux. International Journal of Wildland Fire 13, 201–207.
| Crossref | GoogleScholarGoogle Scholar | Kremens R, Faulring J, Hardy C (2003) Measurement of the time–temperature and emissivity history of the burn scar for remote sensing applications. In ‘5th Symposium on Fire and Forest Meteorology and the 2nd International Wildland Fire Ecology and Fire Management Congress’, 16–20 November 2003, Orlando, FL. Paper J1G.5. (American Meteorological Society: Boston, MA)

Lentile LB, Holden ZA, Smith AMS, Falkowski MJ, Hudak AT, Morgan P, Lewis SA, Gessler PE , Benson NC (2006) Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire 15, 319–345.
| Crossref | GoogleScholarGoogle Scholar | Linn RR (1997) Transport model for prediction of wildfire behavior. Los Alamos National Laboratory, Scientific Report LA13334-T. (Los Alamos, NM)

Malanotte-Rizzoli P, Tziperman E (1996) The oceanographic data assimilation problem: overview, motivation and purposes. In ‘Modern Approaches to Data Assimilation in Ocean Modeling’. (Ed. P Malanotte-Rizzoli) pp. 3–17. (Elsevier: Amsterdam)

Mandel J, Bennethum LS, Beezley JD, Coen JL, Douglas CC, Kim M , Vodacek A (2008) A wildland fire model with data assimilation. Mathematics and Computers in Simulation 79, 584–606.
| Crossref | GoogleScholarGoogle Scholar | McGrattan K, Klein B, Hostikka S, Floyd J (2007) Fire Dynamics Simulator (Version 5) User’s Guide. NIST Building and Fire Research Laboratory. NIST Special Publication 1019-5. (Washington, DC)

McKeown D, Cockburn J, Faulring J, Kremens R, Morse D, Rhody H, Richardson M (2005) Wildfire Airborne Sensor Program (WASP): a new wildland fire detection and mapping system. In ‘Proceedings of the Tenth Forest Service Remote Sensing Applications Conference’, 5–9 April 2004, Salt Lake City, UT. (Ed. JD Greer) (CD-ROM) (American Society for Photogrammetry and Remote Sensing: Bethesda, MD)

Mell W, Jenkins MA, Gould J , Cheney P (2007) A physics-based approach to modeling grassland fires. International Journal of Wildland Fire 16, 1–22.
| Crossref | GoogleScholarGoogle Scholar | Press WH, Teukolsky SA, Vetterling WT, Floannery BP (2007) ‘Numerical Recipes 3rd edn: the Art of Scientific Computing.’ (Cambridge University Press: Cambridge, MA)

Radke L, Clark TL, Coen JL, Walther CA, Lockwood R, Riggan PJ, Brass J , Higgins RW (2000) The WildFire experiment: observations with airborne remote sensors. Canadian Journal of Remote Sensing 26, 406–417.
Rothermel RC (1972) A mathematical model for predicting fire spread in wildland fuels. USDA Forest Service, Forest Service Intermountain Forest and Range Experiment Station, Research Paper INT-115. (Ogden, UT)

Schott JR, Brown SD, Raqueño RV, Gross HN , Robinson G (1999) An advanced synthetic image generation model and its application to multi/hyperspectral algorithm development. Canadian Journal of Remote Sensing 25, 99–111.

Vodacek A, Kremens RL, Fordham AJ, VanGorden SC, Luisi D, Schott JR , Latham DJ (2002) Remote optical detection of biomass burning using a potassium emission signature. International Journal of Remote Sensing 23, 2721–2726.
| Crossref | GoogleScholarGoogle Scholar |

Weber RO (1991) Toward a comprehensive wildfire spread model. International Journal of Wildland Fire 1, 245–248.
| Crossref | GoogleScholarGoogle Scholar |

Wooster MJ, Zhukov B , Oertel D (2003) Fire radiative energy for quantitative study of biomass burning: derivation from the BIRD experimental satellite and comparison to MODIS fire products. Remote Sensing of Environment 86, 83–107.
| Crossref | GoogleScholarGoogle Scholar |

Generation of synthetic infrared remote-sensing scenes of wildland fire

Abstract

Acknowledgements

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