Bayesian techniques for surface fuel loading estimation

Abstract

A study by Keane and Gray (2013) compared three sampling techniques for estimating surface fine woody fuels. Known amounts of fine woody fuel were distributed on a parking lot, and researchers estimated the loadings using different sampling techniques. An important result was that precise estimates of biomass required intensive sampling for both the planar intercept and fixed-area plot methods. This study explores Bayesian statistical methods as a means to reduce the sampling effort needed to obtain a desired precision. We found that Bayesian techniques dramatically increased the precision compared to using no prior information from the site.