Fuel loadings are important inputs to various fire behavior, consumption, and emissions models. Currently fuel maps provide a point estimate of fuel loading for different fuel types, usually at 30 m - 1 km resolution, with values based on empirical observation, satellite data, and/or expert opinion. Due to measurement uncertainty and temporal and spatial dynamics of fuel loadings these pixel-wise values are unlikely to be strictly "correct." If you were to go and measure fuels on the ground at a location within that pixel the value you observe is not likely to be the same as the value in the map. We are aggregating multiple sources of empirical fuel loading data to estimate distributions of fuel loading for various vegetation types and using those estimates to quantify uncertainty in fuel loading associated with fuel maps. We are also investigating how uncertainty in fuel loading estimates propagate to uncertainty in model-based predictions of emissions.