Quantifying Forest Carbon and Structure with Terrestrial LiDAR

Abstract:

Current rising atmospheric CO₂ concentrations are a major concern with significant global ramifications, however, of the carbon (C) fluxes that are known to occur on Earth, the terrestrial sink has the greatest amount of uncertainty. Improved monitoring of forest cover and change is required for reducing emissions from deforestation and forest degradation (REDD). We determine C storage from volume measurements with a high-precision Terrestrial Laser Scanner (TLS), substantially improving current standard ground validation techniques. This technology is utilized on several 30 m x 30 m plots in a Virginia temperate forest. Aboveground C is calculated on each of the study sites with commonly used allometric equations to offer a realistic comparison of field-based estimations to TLS-derived methods. The TLS and aerial LiDAR point cloud data are compared via the development of canopy height models at the plot scale. The novel method of point cloud voxelization is applied to our TLS data in order to produce detailed volumetric calculations in these complex forest ecosystems. Statistical output from the TLS data allows us to resolve and compare forest structure on scales from the individual plot to the entire forest landscape. The estimates produced from this research will be used to inform more widely available remote sensing datasets provided by NASA’s Landsat satellites, significantly reducing the uncertainty of the terrestrial C cycle in temperate forests. Preliminary findings corroborate previous research, suggesting the potential for highly detailed monitoring of forest C storage as defined by the REDD initiative and analysis of complex ecosystem structure.