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

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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.