Assimilation of Satellite Active Fires Data
James D. Haley

TL;DR
This paper develops mathematically sound methods to incorporate satellite fire observations into wildfire models, improving their accuracy by accounting for data uncertainties and inferring fire history and fuel information.
Contribution
It introduces new techniques for assimilating satellite wildfire data, constructing fire history, and modifying fire behavior models based on inferred fuel information.
Findings
Improved wildfire modeling capabilities through data assimilation.
Enhanced fire history reconstruction from satellite data.
Better understanding of satellite data limitations in fire modeling.
Abstract
Wildland fires pose an increasingly serious problem in our society. The number and severity of these fires has been rising for many years. Wildfires pose direct threats to life and property as well as threats through ancillary effects like reduced air quality. The aim of this thesis is to develop techniques to help combat the impacts of wildfires by improving wildfire modeling capabilities by using satellite fire observations. Already much work has been done in this direction by other researchers. Our work seeks to expand the body of knowledge using mathematically sound methods to utilize information about wildfires that considers the uncertainties inherent in the satellite data. In this thesis we explore methods for using satellite data to help initialize and steer wildfire simulations. In particular, we develop a method for constructing the history of a fire, a new technique for…
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Taxonomy
TopicsFire effects on ecosystems · Data Management and Algorithms
