Bridging the Research-Application Divide by Utilizing Low-Density LiDAR Data to Estimate the Aboveground Biomass of Short Rotation Coppice American Sycamore trees (Platanus occidentalis L.) in the Piedmont Region of North Carolina.

Short rotation coppice culture of trees (SRC) provides a sustainable form of renewable biomass energy that is important for carbon storage and cycling and can be integrated into combined energy-food production systems. If properly integrated, it can enhance the environmental quality, and socio-economic development of communities. Estimating aboveground biomass (AGB) through field inventory and selective destructive sampling of trees is time-consuming and spatially limited. The use of aerial Light Detection and Ranging (LiDAR) data to estimate AGB is less time intensive and covers broad spatial extents. However, high-density data points from dedicated airborne flights can be costly and complex to analyze, limiting the practical application of observational data for societal benefit. We address this research-application divide by examining the utility of existing public low-density LiDAR data from the North Carolina Floodplain Mapping Program (NCFMP).We used the data to quantify aboveground biomass and develop a LiDAR derived height-AGB relationship of an American sycamore SRC in the piedmont region of North Carolina. The primary purpose of the NCFMP flights is to derive bare earth digital elevation models to determine flood risk to properties. However, the data can also be used to evaluate the three-dimensional structure of vegetation on the landscape. To examine its utility for estimating AGB in short rotation woody crops, we compared AGB derived from 2015 NCFMP data to field estimates from 2015. We estimated the height-AGB relationship of two sycamore planting densities (10,000 and 5,000 trees per hectare (tph)). Results from the LiDAR data showed the 10,000 tph had a significantly lower estimated canopy height of 200.6 cm compared to the 5,000 tph of 362.0 (p<0.01). However, the resulting AGB value from the 10,000 tph of 17.5 Mg ha-1 (S.E 0.9) was higher than the 5,000 tph of 10.0 Mg ha-1 (S.E 0.02). Like the LiDAR derived estimates, field estimates indicated that 10,000 tph produced 16.0 Mg ha-1 (S.E 0.6) while 5,000 tph produced 14.2 Mg ha-1 (S.E 0.08). This study demonstrates that the lidar-derived estimates are within the acceptable level of error for biomass estimation compared to precise field estimates, thereby increasing the use of publicly available data in estimating carbon storage in SRC plantations.