Real-time data driven wildland fire modeling

Jonathan D. Beezley; Soham Chakraborty; Janice L. Coen; Craig C. Douglas; Jan Mandel; Anthony Vodacek; Zhen Wang

doi:10.1007/978-3-540-69389-5_7

Real-time data driven wildland fire modeling

Jonathan D. Beezley, Soham Chakraborty, Janice L. Coen, Craig C. Douglas, Jan Mandel, Anthony Vodacek, Zhen Wang

Mesoscale & Microscale Meteorology Lab

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Computational Science - ICCS 2008 - 8th International Conference, Proceedings
Pages	46-53
Number of pages	8
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-540-69389-5_7
State	Published - 2008
Event	8th International Conference on Computational Science, ICCS 2008 - Krakow, Poland Duration: Jun 23 2008 → Jun 25 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	5103 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Computational Science, ICCS 2008
Country/Territory	Poland
City	Krakow
Period	06/23/08 → 06/25/08

Keywords

Data assimilation
Dynamic data driven application systems
Ensemble Kalman filter
Image registration
Level set methods
Morphing
Remote sensing
WRF
Weather Research and Forecasting model
Wildland fire modeling

Access to Document

10.1007/978-3-540-69389-5_7

Cite this

Beezley, J. D., Chakraborty, S., Coen, J. L., Douglas, C. C., Mandel, J., Vodacek, A., & Wang, Z. (2008). Real-time data driven wildland fire modeling. In Computational Science - ICCS 2008 - 8th International Conference, Proceedings (PART 3 ed., pp. 46-53). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5103 LNCS, No. PART 3). https://doi.org/10.1007/978-3-540-69389-5_7

@inproceedings{190bd34bb55a4d92881b86954f9fac26,

title = "Real-time data driven wildland fire modeling",

abstract = "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.",

keywords = "Data assimilation, Dynamic data driven application systems, Ensemble Kalman filter, Image registration, Level set methods, Morphing, Remote sensing, WRF, Weather Research and Forecasting model, Wildland fire modeling",

author = "Beezley, \{Jonathan D.\} and Soham Chakraborty and Coen, \{Janice L.\} and Douglas, \{Craig C.\} and Jan Mandel and Anthony Vodacek and Zhen Wang",

year = "2008",

doi = "10.1007/978-3-540-69389-5\_7",

language = "English",

isbn = "3540693882",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 3",

pages = "46--53",

booktitle = "Computational Science - ICCS 2008 - 8th International Conference, Proceedings",

edition = "PART 3",

note = "8th International Conference on Computational Science, ICCS 2008 ; Conference date: 23-06-2008 Through 25-06-2008",

}

Beezley, JD, Chakraborty, S, Coen, JL, Douglas, CC, Mandel, J, Vodacek, A & Wang, Z 2008, Real-time data driven wildland fire modeling. in Computational Science - ICCS 2008 - 8th International Conference, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 5103 LNCS, pp. 46-53, 8th International Conference on Computational Science, ICCS 2008, Krakow, Poland, 06/23/08. https://doi.org/10.1007/978-3-540-69389-5_7

Real-time data driven wildland fire modeling. / Beezley, Jonathan D.; Chakraborty, Soham; Coen, Janice L. et al.
Computational Science - ICCS 2008 - 8th International Conference, Proceedings. PART 3. ed. 2008. p. 46-53 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5103 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Real-time data driven wildland fire modeling

AU - Beezley, Jonathan D.

AU - Chakraborty, Soham

AU - Coen, Janice L.

AU - Douglas, Craig C.

AU - Mandel, Jan

AU - Vodacek, Anthony

AU - Wang, Zhen

PY - 2008

Y1 - 2008

N2 - 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.

AB - 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.

KW - Data assimilation

KW - Dynamic data driven application systems

KW - Ensemble Kalman filter

KW - Image registration

KW - Level set methods

KW - Morphing

KW - Remote sensing

KW - WRF

KW - Weather Research and Forecasting model

KW - Wildland fire modeling

UR - https://www.scopus.com/pages/publications/47749151544

U2 - 10.1007/978-3-540-69389-5_7

DO - 10.1007/978-3-540-69389-5_7

M3 - Conference contribution

AN - SCOPUS:47749151544

SN - 3540693882

SN - 9783540693888

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 46

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BT - Computational Science - ICCS 2008 - 8th International Conference, Proceedings

T2 - 8th International Conference on Computational Science, ICCS 2008

Y2 - 23 June 2008 through 25 June 2008

ER -

Beezley JD, Chakraborty S, Coen JL, Douglas CC, Mandel J, Vodacek A et al. Real-time data driven wildland fire modeling. In Computational Science - ICCS 2008 - 8th International Conference, Proceedings. PART 3 ed. 2008. p. 46-53. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-540-69389-5_7

Real-time data driven wildland fire modeling

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