Doctoral Dissertation Research: A Multiresolution Approach to Remote Sensing of Fire Fuels

野火作为一种自然干扰过程发生在几乎世界上所有的生态系统中，并在许多生态系统中占主导地位。 野火的类型、强度和频率与植被格局和气候密不可分，任何一个方面的变化都会导致其他方面的变化。 这些关系的变化可能导致环境结构和功能的深刻变化，跨越很大的空间和时间尺度。 从全球变暖引起的火灾制度变化到在局部范围内重新引入火灾以促进生态系统活力等问题，都促使研究人员开发更有效、更便宜的测量、建模和绘制可助长火灾的物质。 这个博士论文研究项目将应用地质统计技术，以开发多分辨率遥感技术的燃料负荷的生物物理估计的野外火灾在中央科罗拉多的站点可以被消费的燃料的实地测量。 使用传统的现场采样技术，该项目的第一阶段将实证研究的规模依赖方面的火燃料及其成分（枯枝落叶，达夫，草本植物，灌木，倒下的木质材料，和立木燃料）。 在分析的第二阶段，将采用生物物理方法，利用地质统计学工具模拟燃料负荷的基本空间分布，以便将所需的关于火灾燃料特性和分布的信息与多尺度遥感联系起来。 该项目将构成一种新的方法，通过使用遥感图像作为一个多尺度问题来估计和测绘生态系统内的火灾燃料负荷。 它将为这种方法的潜力和当前局限性提供新的见解，这可以为有兴趣监测火灾燃料，管理火灾风险，并在从小型公园和保护区到区域景观的尺度上模拟火灾行为的资源管理者提供有价值的新信息。 作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立的研究生涯。

Wildfires occur as a natural disturbance process in virtually all the world's ecosystems and dominate in many. The type, intensity, and frequency of wildfire regimes are so inextricably entangled with vegetation pattern and climate that any change in one will invariably lead to changes in the others. Profound changes in environmental structure and function spanning a great range of spatial and temporal scales can result from changes in these relationships. Issues ranging from changes in fire regimes as a result of global warming to reintroduction of fire at local scales to promote ecosystem vitality have led researchers to develop more effective and less expensive for measuring, modeling, and mapping substances that can fuel fires. This doctoral dissertation research project will apply geostatistical techniques to field measurements of fuels that can be consumer by wild fires at sites in central Colorado in order to develop multi-resolution remote-sensing techniques for biophysical estimation of fuel loads. Using traditional field sampling techniques, the first stage of this project will empirically examine the scale-dependent aspects of fire fuels and their constituents (litter, duff, herbs, shrubs, downed woody material, and standing tree fuels). In the second phase of the analysis, a biophysical approach will use geostatistical tools that model the fundamental spatial distribution of fuels loads to link the information needed on fire fuel characteristics and distribution to multi-scale remote sensing. This project will constitute a new approach for estimating and mapping fire fuel loads within ecosystems through the use of remotely sensed imagery as a multi-scale problem. It will provide new insights into the potential and current limitations of this approach, which could offer valuable new information for resource managers interested in monitoring fire fuels, managing fire risk, and modeling fire behavior at scales ranging from small parks and preserves to regional landscapes. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.