Terrestrial LiDAR of tropical forests

The Above-Ground Biomass (AGB) stocked in large trees in tropical forests is a crucial component of the global carbon cycle. However, the estimations of tree AGB via allometric models are highly uncertain and often biased for large tropical trees. Conversely, a novel non-destructive method based on Terrestrial Laser Scanner (TLS) data and Quantitative Structure Models (3D tree modeling) automatically reconstructs the complete tree architecture, accounting for specific individual tree biophysical structure, thus providing more accurate AGB estimates. Moreover, this novel method can be further used for testing and generating improved allometric models, and can contribute towards understanding tropical forest morphology. 

Image of Destructive sampling tree AGB data dataset

Destructive sampling tree AGB data

Destructive sampling measurement data of 29 large tropical trees from 3 sites (Indonesia, Peru and Guyana) for estimating tree wood volume and tree AGB.

Image of Forest inventory data dataset

Forest inventory data

Forest inventory data of 29 individual large tropical trees from 3 sites (Indonesia, Peru and Guyana) for estimating tree AGB with allometric equations.

Image of Quantitative Structure Models dataset

Quantitative Structure Models

Quantitative Structural Models (QSM) cylinder model outputs (3D tree architecture models), generated from the individual TLS point cloud data of 29 large tropical trees from 3 sites (Indonesia, Peru and Guyana).

Image of TLS tree point cloud data dataset

TLS tree point cloud data

TLS point cloud data for 29 large tropical trees in 3 study sites: Indonesia (peat swamp forest in Central Kalimantan, Borneo), Peru (lowland tropical moist forest in Madre de Dios) and Guyana (lowland tropical moist forest in Cayuni-Mazaruni).