Integrating arborist Canopy Access techniques with Mobile and Terrestrial Laser Scanning: retrieving key ecological indicators from improved tree and forest plot 3D point clouds

Climate change is impacting forests, resulting in a myriad of ecological changes. New digital tools are increasingly being used to help monitor trees in forest plots and provide high spatial resolution information on the status of key ecological indicators such as biomass. Terrestrial Laser Scanning (TLS) is one such tool; however, in tall, dense forest canopies, it is limited by occlusion which results in less accurate indicators. To overcome this limitation, we integrated arborist Canopy Access techniques with Terrestrial Laser Scanning (TLS), Mobile Laser Scanning (MLS) and Canopy Laser Scanning (CLS), and made a detailed comparison of the different methods. We delineated a 50 x 50 m plot and raised a TLS into all trees with a Diameter at Brest Height (BDH) ≥ 60 cm (n=8) using arborist methods, resulting in the CLS dataset.  Then, an MLS was used to retrieve point clouds of all trees which were deemed safely climbable with a DBH ≥ 40 cm (n=12). Each tree was scanned twice for its whole length (once non each side) using the MSL and an arborist abseiling approach. This resulted in a complete tree characterization and a novel method to rapidly scan trees – which has not been implemented before. From the resulting 3D point clouds, and array of ecological indicators were computed, including stem volume and biomass, tree height, canopy volume, branch length and total volume. Estimates of ecological indicators from TLS+CLS and MLS, were found to be comparable. However, the approach to sample trees using MSL was by far the least time consuming – allowing for more rapid characterization of trees in plots – the amount of time required to hoist a TSL in the canopy being relatively long and the process complex. This study provides a novel approach which can be applied to monitor safely climbable trees with forest plots, in a more rapid manner than CLS, and resulting in comparable ecological indicators. This method also overcomes the issue of occlusion in dense canopies inherent in TLS. Such information is essential to understanding how climate change is impacting forests and can help inform adaptation.