Spatio-temporal Estimation Of Wildfire Growth Open Access Deposited

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Date Uploaded: 02/08/2017
Date Modified: 04/05/2017

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.

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  • Proceedings of the ASME Dynamic Systems and Control Conference
  • This work was part of a pilot "mediated-deposit model" where library staff found potential works, later submitted for faculty review

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Identifier: 10.1115/DSCC2013-4022

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