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  • Spatio-temporal estimation of wildfire growth

    Article thumbnail: Spatio-temporal estimation of wildfire growth
    Type:
    Article
    Description/Abstract:
    This work presents a methodology for real-time estimation of wildland fire growth, utilizing a fire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deployability.
    Creator/Author:
    Sharma, Balaji R.; Cohen, Kelly, and Kumar, Manish
    Submitter:
    Kelly Cohen
    Date Uploaded:
    02/03/2017
    Date Modified:
    04/05/2017
    Date Created:
    2013-10
    License:
    All rights reserved

  • Spatio-temporal Estimation Of Wildfire Growth

    Article thumbnail: Spatio-temporal Estimation Of Wildfire Growth
    Type:
    Article
    Description/Abstract:
    This work presents a methodology for real-time estimation of wildland fire growth, utilizing afire growth model based on a set of partial differential equations for prediction, and harnessing concepts of space-time Kalman filtering and Proper Orthogonal Decomposition techniques towards low dimensional estimation of potentially large spatio-temporal states. The estimation framework is discussed in its criticality towards potential applications such as forest fire surveillance with unmanned systems equipped with onboard sensor suites. The effectiveness of the estimation process is evaluated numerically over fire growth data simulated using a well-established fire growth model described by coupled partial differential equations. The methodology is shown to be fairly accurate in estimating spatio-temporal process states through noise-ridden measurements for real-time deploy ability.
    Creator/Author:
    Sharma, Balaji R.; Cohen, Kelly, and Kumar, Manish
    Submitter:
    Kelly Cohen
    Date Uploaded:
    02/08/2017
    Date Modified:
    04/05/2017
    Date Created:
    2013-10
    License:
    All rights reserved