Abstract
Small footprint LiDAR data were used to detect and characterize vegetation in a semi-arid sagebrush steppe environment in southeastern Idaho. Processing the raw data in individual flightlines maintained the high relative accuracy of the data set and allowed for the detection of sub-meter vegetation. First return LiDAR pulse data were used to both determine the ground surface as well as calculate vegetation heights. Surface roughness maps based on vegetation heights were found to best capture the variability of the canopy and accurately distinguish burned and unburned areas. Field validation of a sagebrush presence and absence classification based on a single roughness threshold value indicates an overall accuracy of 86%. The LiDAR-determined vegetation heights are moderately well correlated to those measured in the field, although the LiDAR heights uniformly underestimate the field heights. This underestimation is believed to be due to signal threshold limits within the LiDAR sensor, producing heights corresponding to the interior of the shrub canopy rather than the top.
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