Fig. 2
From: Multitemporal lidar captures heterogeneity in fuel loads and consumption on the Kaibab Plateau
Observed versus predicted available canopy (N = 69) and surface (N = 153) fuel loads. Fuel loads were predicted from airborne lidar and fire history metrics at field plot locations with random forest (RF) models. Mean bias error (MBE) is the mean of the predicted values minus the mean of the observed values. Root mean square error (RMSE) is the square root of the mean of the squared residuals, where residuals are observed minus predicted values. 1:1 lines are shown in black, and fit lines are shown in gray. MBE and RMSE are in units of Mg ha− 1