The Potential of Combined Lidar and SAR Data in Retrieving Forest Parameters using Model Analysis

Abstract

3D Lidar waveform and 3D radar backscatter models based on Radiative Transfer theory were used to simulate waveform and backscattering of various plots with different stand ages and structures, which were generated using forest growth model. The inversion models for estimating forest Above Ground Biomass (AGB) and Average Stand Height (ASH) were derived from the combined simulated database of large footprint Lidar waveforms and L-band polarimetric SAR backscattering using stepwise analysis method. The inversion procedures were then applied to NASA LVIS and ALOS PALSAR data to retrieve forest parameters for the study area. The study area is a 10km by 10km area located at International Paper's Northern Experiments Forest, Maine, USA, where field measurements that include stem coordinate, DBH, species and canopy position were recorded within a 200m by 150 m stand. Heights and AGB of total 7956 trees were estimated by applying species-specific allometric equations to stand measurements. AGB and height were then scaled up to the area according to the LVIS footprint size and location at 149 20m*20m plots, which were used to verify the inversion model developed using simulated database. The study concludes that Lidar waveform indices and SAR backscattering are complementary for forest parameters retrieving, which improved the limitation of signature saturation for regional biomass mapping using SAR data only. The comparison between inversed forest parameters and field measurements shows good consistency.