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    Dionysus: a stochastic fire growth scenario generator

    Neue Suche nach: Han, Lengyi
    Neue Suche nach: John Braun, W.

    The Prometheus Fire Growth Model is a deterministic wildfire simulator. Given weather, topographical and fuel information, the simulated fire front is plotted at equally spaced times. Unpredictability of fire behavior makes deterministic predictions inaccurate. By statistically modeling the data to which the model equations are fit, it is possible to obtain a distribution of fire front predictions. If the weather forecast is reliable, repeated stochastic simulation is not required, so probability contours require no more computing time than what is required for a single deterministic contour. Copyright © 2013 John Wiley & Sons, Ltd.

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    Dionysus: a stochastic fire growth scenario generator

    Neue Suche nach: Han, Lengyi
    Neue Suche nach: John Braun, W.

    The Prometheus Fire Growth Model is a deterministic wildfire simulator. Given weather, topographical and fuel information, the simulated fire front is plotted at equally spaced times. Unpredictability of fire behavior makes deterministic predictions inaccurate. By statistically modeling the data to which the model equations are fit, it is possible to obtain a distribution of fire front predictions. If the weather forecast is reliable, repeated stochastic simulation is not required, so probability contours require no more computing time than what is required for a single deterministic contour. Copyright © 2013 John Wiley & Sons, Ltd.

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    Zugriff prüfen
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    Bestellung bei Subito €

    Dionysus: a stochastic fire growth scenario generator

    Neue Suche nach: Han, Lengyi
    Neue Suche nach: John Braun, W.

    The Prometheus Fire Growth Model is a deterministic wildfire simulator. Given weather, topographical and fuel information, the simulated fire front is plotted at equally spaced times. Unpredictability of fire behavior makes deterministic predictions inaccurate. By statistically modeling the data to which the model equations are fit, it is possible to obtain a distribution of fire front predictions. If the weather forecast is reliable, repeated stochastic simulation is not required, so probability contours require no more computing time than what is required for a single deterministic contour. Copyright © 2013 John Wiley & Sons, Ltd.

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    Titel:

    Dionysus: a stochastic fire growth scenario generator

    Beteiligte:

    Han, Lengyi (Autor:in) / John Braun, W. (Autor:in)

    Erschienen in:

    Environmetrics ; 25 ; 431-442

    Erscheinungsdatum:

    01.09.2014

    Format / Umfang:

    12 pages

    ISSN:

    1099-095X , 1180-4009

    DOI:

    https://doi.org/10.1002/env.2236

    Medientyp:

    Aufsatz (Zeitschrift)

    Format:

    Elektronische Ressource

    Sprache:

    Englisch

    Schlagwörter:

    burn probability maps , deterministic process model , rate of spread , wildfire growth , Monte Carlo , power transformation , ensemble methods

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