To better understand the role that forested ecosystems plays in mitigating atmospheric CO2, methodologies for quantifying forest carbon pools must be established. To this aim, researchers with BSCSP used Light Detection and Ranging (LiDAR) remote sensing technologies for achieving accurate estimates of aboveground biomass and thereby carbon pools.
In this study, discrete return airborne LiDAR data was periodically collected across ~20,000 hectares (ha) of an actively managed, mixed conifer forest landscape in northern Idaho. Forest inventory plots, established via a random stratified sampling design, were sampled in 2003 and 2009. A computer-based algorithm was used to establish a statistical relationship between inventory data and forest structural metrics derived from the LiDAR acquisitions. Aboveground biomass maps were created for the study area based on statistical relationships developed at the plot level.
Over this 6-year period, scientists with the University of Idaho found that the mean increase in biomass due to forest growth across the non-harvested portions of the study area was 4.8 metric ton/hectare (Mg/ha). Further findings indicated that in these non-harvested areas, there was a higher biomass increase in mature and old forest compared to stand initiation and young forest. Overall, LiDAR data coupled with field reference data offer a powerful method for calculating pools and changes in aboveground carbon in forested systems. The results of this study suggest that multitemporal LiDAR-based approaches are likely to be useful for high quality estimates of aboveground carbon change in conifer forest systems.
To read more about the Forestry Study, click on the links below:
"Quantifying Forest Aboveground Carbon Pools and Fluxes: Final Report” Big Sky Carbon Sequestration Partnership. September 2011. Submitted to Department of Energy (DOE) and National Energy Technology Laboratory (NETL).