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世界上几乎所有的生态系统中，并在许多生态系统中占主导地位。野火的类型、强度和频率与植被模式和气候有着千丝万缕的联系，任何一种的变化都会导致其他的变化。这些关系的变化可能导致环境结构和功能在大范围的空间和时间尺度上的深刻变化。从全球变暖导致的火情变化，到为促进生态系统活力而在局部尺度上重新引入火灾，这些问题促使研究人员开发出更有效、更便宜的方法来测量、建模和绘制可能引发火灾的物质。该博士论文研究项目将应用地质统计学技术对科罗拉多州中部地区可能被野火消耗的燃料进行实地测量，以便开发用于燃料负荷生物物理估计的多分辨率遥感技术。该项目的第一阶段将使用传统的实地抽样技术，实证地检查燃料及其成分（凋落物、枯草、草本、灌木、倒下的木质材料和直立的树木燃料）的规模依赖方面。在分析的第二阶段，生物物理方法将使用地球统计工具，对燃料负荷的基本空间分布进行建模，将所需的燃料特性和分布信息与多尺度遥感联系起来。该项目将通过使用遥感图像作为多尺度问题，为估算和绘制生态系统内的火灾燃料负荷提供一种新方法。它将为这种方法的潜力和目前的局限性提供新的见解，这可以为资源管理者提供有价值的新信息，这些资源管理者对监测火灾燃料、管理火灾风险和模拟从小型公园和保护区到区域景观的火灾行为感兴趣。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.