Forest Biomass Mapping Using Lidar-derived Canopy Height Metrics at Maine in USA

Forest biomass from regional to global level is important for underlying and monitoring the ecosystem responses to natural and human activities. Lidar provides the ability to directly measure canopy height index for aboveground biomass estimation. Our study site is located in Howland, Maine, United States. Data source consists of airborne medium footprint lidar data in 2009 and ground data from DESDynI field campaign in August 2009 and 2010. Canopy vertical structures are captured by the Laser Vegetation Imaging Sensor (LVIS) with entire return signal (i.e. in ~30 cm vertical bins). We first calculated height metrics (i.e. h10 to h100, totally 15 indices) by waveform decomposition using either Gaussian or numeric filter. Then, metrics were compared with RH indices at different levels: footprint of 20m diameter circle, squared plot of 25 x 25m, 50 x 50 m, 50 x 100 m and 50 x 200 m, respectively. At last, the biomass map was created. Height metrics from h50 to h80 show high correlation with biomass. Among them, h65 and h70 are the best, which is consistent with previous perspective that RH50 (or HOME, height of median energy) and RH75 have the best linear relationship with aboveground biomass. Comparison between h metrics and RH indices shows the latter one is better. In addition, both single and multi-variable linear regression model significant improvement with the increasing of field plot size.