Validation of the ICEsat vegetation product using crown-area-weighted mean height derived using crown delineation with discrete return lidar data

The Geoscience Laser Altimeter System (GLAS), a spaceborne light detection and ranging (lidar) sensor, has acquired over 250 million lidar observations over forests globally, an unprecedented dataset of vegetation height information. To be useful, GLAS must be calibrated to measurements of height used in forestry inventory and ecology. Airborne discrete return lidar (DRL) can characterize vegetation and terrain surfaces in detail, but its utility as calibration data for GLAS is limited by the lack of a direct relationship between the canopy height measurements collected by airborne and spaceborne lidar systems and coincident field data. We demonstrate that it is possible to use DRL to directly estimate the crown-area-weighted mean height (Hcw), which is conceptually and quantitatively similar to the Lorey’s height, which is calculated from forest inventory data, and can be used to calibrate GLAS without the use of field data. For a dataset from five sites in western North America, the two indices of height (Hcw from DRL and Lorey’s from forest inventory) are directly related (r2 = 0.76; RMSE of 3.8 m; intercept and slope of 0.8 m and 0.98, respectively). We derived a relationship between the DRL-derived Hcw and height information from coincident GLAS waveforms; the resulting equation explained 69% of variance, with an RMSE of 6.2 m.