Estimating live fuel moisture content in Oklahoma plants

Live fuel moisture content (LFM) is an important variable in fire danger rating systems. LFM collection is time and resource intensive and plant water relations vary within and between species. Consequently, the best approach for estimating LFM is unknown. Few studies have investigated LFM in the state of Oklahoma, and current estimates of LFM have not been validated. The objectives of this study were to evaluate the use of environmental and remote sensing proxies for estimating LFM in Oklahoma plants. I found that LFM can be accurately estimated using either hyperspectral leaf-level reflectance or environmental proxies. My analysis of several remote sensing vegetation indices identified the Water Index and VIgreen as the best suited indices for approximating LFM. Using functional group, photoperiod, vapor pressure deficit, and rainfall I was able to estimate LFM in Oklahoma plant communities. In addition to these findings, I identified a need to reevaluate current methods for estimating LFM. By advancing our understanding of LFM and how best to predict it, my results can be used in fire danger rating systems to protect lives and preserve natural resources