Abseiling for science: integrating mobile and terrestrial laser scanning with arborist methods to improve point clouds

Forests play a central role in biodiversity conservation, nutrient cycles, and climate regulation. At the same time, forests are increasingly affected by biodiversity loss, disruptions of nutrient cycles, and global warming. Forests respond to these pressures through a range of dynamics, including increased tree mortality, shifts in tree allometry, and changes in species composition. Accurate and detailed forest monitoring, which can track changes in these parameters, is therefore essential.

Mobile and terrestrial laser scanning (MLS and TLS) have proven to be among the most precise tools for assessing key forest characteristics such as forest structure, tree architecture, and aboveground biomass. However, these technologies are typically ground-based, and the resulting point clouds are strongly affected by sparse point density in the canopy and occlusion, i.e., when main branches block laser pulses. This leads to systematically vertically biased point densities and data gaps in the canopy.

Here, we present a novel methodological framework that integrates mobile and terrestrial laser scanning with canopy access methods to reduce occlusion and improve point cloud quality. We use modern arborist techniques to access tree crowns using ropes and harnesses. Once in the canopy, we abseil from two sides of the tree while carrying an MLS unit by hand. In addition, we distribute targets on branches and mount the TLS on custom-built platforms installed on lateral branches and along the main stem. This workflow is repeated several times per year to quantify changes in tree morphology, such as tree growth at the millimeter scale, and to derive accurate estimates of forest characteristics.

The resulting point clouds show a more homogeneous point density and substantially reduced occlusion. Consequently, estimates of tree allometry, volume, and biomass are significantly improved. These highly accurate digital forest representations can be extrapolated to larger spatial and temporal scales and used to calibrate and validate airborne and satellite remote sensing products.

This work demonstrates that accurately characterizing the structural complexity of trees and forests requires innovative measurement approaches to enable improved monitoring and sustainable forest management in a changing climate.