Investigating the agreement between global canopy height maps and airborne Lidar derived height estimates over Canada

Carbon storage in forest aboveground biomass is a critical, yet difficult, component of the global carbon cycle to estimate. Canopy height, a key indicator of carbon storage, can be estimated from Light Detection and Ranging (Lidar) waveforms collected by the Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud, and land Elevation Satellite (ICESat). Although globally distributed, GLAS does not provide spatially exhaustive coverage. Therefore, accurate methods of extrapolation are necessary to produce wall-to-wall global canopy height maps from these data. In this analysis, we compare two of these global GLAS-derived height products to canopy height estimates derived from 25000 km of discrete return airborne Lidar data over Canada's boreal forests. We selected the 95th percentile of first return height from airborne Lidar as a measure of canopy height to relate against estimates from the global GLAS-derived products. The agreement between the global GLAS-derived products and airborne Lidar-derived height estimates varied between the two products (average ecozone RMSE = 3.9 and 7.4 m), demonstrating that differences in data selection, processing, and extrapolation can influence height estimates derived from GLAS data. Where large differences existed between the global GLAS-derived products and the airborne Lidar-derived height estimates, the GLAS-derived products tended to predict taller canopies. Removing GLAS waveforms on steep terrain appeared to be a superior approach to reducing errors in height estimates, as the global GLAS-derived product that filtered these waveforms was in closer agreement with airborne Lidar-derived height estimates in regions of rough terrain (RMSE = 3.2–8.5 m compared with 8.1–13.8 m). Differences in the spatial resolution of canopy height estimates, coupled with varying definitions of canopy height within each product, should be considered when interpreting the results of this analysis. Investigating the relationship between small-footprint Lidar data and published canopy height products can identify the approaches that lead to the most accurate estimates of aboveground biomass and can help determine why discrepancies in height estimates exist between various model approaches, data and underlying environmental conditions.

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