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Proceedings Paper

Fire temperature retrieval using constrained spectral unmixing and emissivity estimation
Author(s): Ambrose E. Ononye; Anthony Vodacek; Robert Kremens
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Paper Abstract

Accurate retrieval of wildland fire temperature from remote imagery would be useful in improving prediction of fire propagation and estimates of fire effects such as burn severity and gas and particle production. The feasibility of estimating temperatures for subpixel fires by spectral unmixing has been established by previous work with the AVIRIS sensor. However, this unmixing approach can also produce optimizations for temperatures that may not be physically related to the fraction of flaming combustion in a pixel. Furthermore, previous techniques have treated fire as a blackbody and have modeled the mixed pixel transmitted radiance as two blackbody sources. This first order approximation can also affect the temperature retrieval. Knowledge of emissivity and use of a more complex radiance model should improve the accuracy of the temperature estimation. We therefore, propose a technique which improves the previous approach by using the potassium emission to pre-determine pixels that actually contain signal from flaming combustion and a modified mixed pixel radiance model. A non-linear, constrained multi-dimensional optimization procedure which estimates flame emissivity was applied to the model to estimate fire temperature and its areal extent. Results are shown for AVIRIS data sets acquired over Cuiaba, Brazil (1995) and the San Bernardino Mountains (1999).

Paper Details

Date Published: 1 June 2005
PDF: 9 pages
Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.603440
Show Author Affiliations
Ambrose E. Ononye, Rochester Institute of Technology (United States)
Anthony Vodacek, Rochester Institute of Technology (United States)
Robert Kremens, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 5806:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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