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Virtualization of Fuelbeds: Building the Next Generation of Fuels Data for Multiple-Scale Fire Modeling and Ecological Analysis

机译:燃料床虚拟化:构建用于多尺度火灾建模和生态分析的下一代燃料数据

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摘要

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.
机译:这项研究的主要目的是使用地面和机载激光扫描技术,改进在3维中导出细粒度,可扩展的荒地燃料属性的方法。从根本上说,这是一种应用于燃料表征问题的遥感研究工作。激光扫描技术的进步开始对消防研究中的各种建模框架产生重大影响,尤其是那些利用3维数据并受益于有效数据缩放的框架。激光扫描和火场建模的结合使人们能够进一步了解燃料的可变性如何调制火场行为和影响。本文详细介绍了利用地面和机载激光扫描来表征和量化地表燃料床的方法和技术的发展。主要研究地点是美国佛罗里达州的Eglin空军基地,该基地在适应火灾的环境中提供了多种燃料类型和条件,以及多学科专业知识,后勤支持和明火的详细描述所必需的处方火。物理过程。第1章提供研究概述,并讨论了美国东南部燃料科学的现状以及对高度解析的燃料数据的相关需求。第2章介绍了使用地面激光扫描在多个尺度上对燃料进行采样的方法,并提供了在3-D模式下对燃料床模型空间精度的分析。第3章介绍了用于预测燃料质量的基于体素的占用体积方法的开发。结果可用于通过机载激光扫描指标预测风景名胜燃料负荷以及预测火灾后的燃料消耗。第4章介绍了一种新颖的燃料模拟方法,该方法可产生空间明确的,可统计防御的燃料特性估计,并演示了对观测数据进行重采样的途径。该方法也可以直接与地面激光扫描数据进行比较,以评估激光脉冲的能量拦截如何影响燃料床的特性。第5章讨论了这项工作对消防科学的贡献,并描述了这项工作正在进行的和将来的研究。第2章和第4章分别在《国际荒地火灾杂志》和《加拿大遥感杂志》上发表,第3章正在准备出版。

著录项

  • 作者

    Rowell, Eric Martin.;

  • 作者单位

    University of Montana.;

  • 授予单位 University of Montana.;
  • 学科 Remote sensing.;Forestry.;Natural resource management.
  • 学位 Ph.D.
  • 年度 2017
  • 页码 142 p.
  • 总页数 142
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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