Dissertation/Thesis Abstract

Virtualization of Fuelbeds: Building the Next Generation of Fuels Data for Multiple-Scale Fire Modeling and Ecological Analysis
by Rowell, Eric Martin, Ph.D., University of Montana, 2017, 142; 10744641
Abstract (Summary)

The primary goal of this research is to advance methods for deriving fine-grained, scalable, wildland fuels attributes in 3-dimensions using terrestrial and airborne laser scanning technology. It is fundamentally a remote sensing research endeavor applied to the problem of fuels characterization. Advancements in laser scanning are beginning to have significant impacts on a range of modeling frameworks in fire research, especially those utilizing 3-dimensional data and benefiting from efficient data scaling. The pairing of laser scanning and fire modeling is enabling advances in understanding how fuels variability modulates fire behavior and effects.

This dissertation details the development of methods and techniques to characterize and quantify surface fuelbeds using both terrestrial and airborne laser scanning. The primary study site is Eglin Airforce Base, Florida, USA, which provides a range of fuel types and conditions in a fire-adapted landscape along with the multi-disciplinary expertise, logistical support, and prescribed fire necessary for detailed characterization of fire as a physical process. Chapter 1 provides a research overview and discusses the state of fuels science and the related needs for highly resolved fuels data in the southeastern United States. Chapter 2, describes the use of terrestrial laser scanning for sampling fuels at multiple scales and provides analysis of the spatial accuracy of fuelbed models in 3-D. Chapter 3 describes the development of a voxel-based occupied volume method for predicting fuel mass. Results are used to inform prediction of landscape-scale fuel load using airborne laser scanning metrics as well as to predict post-fire fuel consumption. Chapter 4 introduces a novel fuel simulation approach which produces spatially explicit, statistically-defensible estimates of fuel properties and demonstrates a pathway for resampling observed data. This method also can be directly compared to terrestrial laser scanning data to assess how energy interception of the laser pulse affects characterization of the fuelbed. Chapter 5 discusses the contribution of this work to fire science and describes ongoing and future research derived from this work. Chapters 2 and 4 have been published in International Journal of Wildland Fire and Canadian Journal of Remote Sensing, respectively, and Chapter 3 is in preparation for publication.

Indexing (document details)
Advisor: Seielstad, Carl A.
Commitee: Affleck, David, Clow, Richmond, Larson, Andrew, Queen, LLoyd
School: University of Montana
Department: Forestry
School Location: United States -- Montana
Source: DAI-B 79/07(E), Dissertation Abstracts International
Subjects: Forestry, Natural Resource Management, Remote sensing
Keywords: Fire, Fuels, Lidar, Simulation, TLS
Publication Number: 10744641
ISBN: 978-0-355-61757-3
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