Ground truthing LIDAR data within a successionally diverse piedmont forest

Background/Question/Methods

Light Detection and Ranging (LIDAR) data for select successional forests in North Carolina are currently being compared and correlated with on-site sample data through a cooperative research effort between North Carolina State University, Johnson C. Smith University, Livingstone College, UNC Pembroke, and Western Carolina University. Our Mecklenburg County study is centered on a 150 acre forested county park – Ribbon Walk – consisting of a range of successional and mature forest communities. Ground sampled data sets for tree community structure, age, diameter, height, and leaf area from three successional areas within the forest are currently being compared with LIDAR data to assess the accuracy of the remotely sensed forest data. Three 20m x 20m forest plots determined through on-line LIDAR data to be successionally old, middle, or young were outlined on a computer. The selected areas were located by GPS in Ribbon Walk Park and permanent plots were established.  Community structure data consisting of species, diameter, and the height of the tallest tree were gathered and then relative density, relative dominance, and species importance values (the sum of the relative values) for each plot were calculated. Leaf area indexes (LAI) were determined by electronic meter and compared to litter leaf areas in three 0.25m² plots. Dry mass of litter was also determined in these plots.

Results/Conclusions

First samples of tree cores revealed ages of 70 years for the LIDAR-determined Young Forest, 26 years for the LIDAR-determined Middle-age Forest, and 62 years for the LIDAR-determined Old Forest. The most important species in each plot were determined to be tulip poplar and beech in LIDAR-Young Forest, loblolly pine in the LIDAR-Middle Age Forest and sweetgum, beech, tulip poplar, and maple in the LIDAR-Old Forest. LAI data by electronic instrument was determined to be 4.27 m²/m² in the LIDAR-Young Forest which compared to 4.67 m²/m² in the same plot as determined by collection of total leaf litter in sample plots in December. The LIDAR-Old Forest had a litter-estimated leaf area index value of 5.17 m²/m². Mean LAI over the three plots as estimated by litter sampling was 4.77 (0.374) m²/m². Mean dry litter mass was determined to be 358.0 (151.8) g/m². Further ground-truthing of  LIDAR data will occur throughout 2011-12 and assessments made of the accuracy of that data with respect to actual ground-gathered forest data.