A Comparison of Remote Sensing Methods for Estimating Above-Ground Carbon Biomass at a Wetland Restoration Area in the Southeastern Coastal Plain

Abstract

Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented. Previous studies have shown that full-waveform LiDAR (light detection and ranging) is well suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of discrete-return LiDAR to model above-ground biomass in areas with relatively sparse vegetation. This study compared the abilities of discrete-return LiDAR and high-resolution optical imagery to model above-ground carbon biomass at a wetland restoration area in eastern North Carolina. The optical imagery model explained more of the overall variation in biomass at the study site than the LiDAR model did (R2 values of 0.36 and 0.19 respectively). Moreover, the optical imagery model was better able to detect high and low biomass areas than the LiDAR model. These results suggest that the ability of discrete-return LiDAR to model above-ground biomass is rather limited in areas with relatively small trees and that high spatial resolution optical imagery may be the better tool in such areas.