Escape routes are essential components of wildland firefighter safety, providing pre-defined pathways to a safety zone. Among the many factors that affect travel rates along an escape route, landscape conditions such as slope, lowlying vegetation density, and ground surface roughness are particularly influential, and can be measured using airborne light detection and ranging (LiDAR) data. In order to develop a robust, quantitative understanding of the effects of these landscape conditions on travel rates, we performed an experiment wherein study participants were timed while walking along a series of transects within a study area dominated by grasses, sagebrush and juniper. We compared resultant travel rates to LiDAR-derived estimates of slope, vegetation density and ground surface roughness using linear mixed effects modelling to quantify the relationships between these landscape conditions and travel rates. The best-fit model revealed significant negative relationships between travel rates and each of the three landscape conditions, suggesting that, in order of decreasing magnitude, as density, slope and roughness increase, travel rates decrease. Model coefficients were used to map travel impedance within the study area using LiDAR data, which enabled mapping the most efficient routes from fire crew locations to safety zones and provided an estimate of travel time.