providing an affordable, safe, and responsive on-demand tool for monitoring fire effects 5 at a much finer spatial resolution than is possible with current technology. Using 6 spectroscopic analysis of a variety of live as well as combusted vegetation samples to 7 identify the spectral separability of vegetation classes, an optimal set of spectra was 8 selected to be utilized by machine learning classifiers. This approach allows high 9 resolution mapping of wildland fire severity and extent. 10