Carlos Cabo

TL;DR: The presented research reveals that coherent 3D data and spectral information, as provided by the SfM workflow, promote opportunities to derive both structural and physiological attributes at the individual tree crown (ITC) as well as stand levels.

TL;DR: The algorithm can be used with data from any Mobile Laser Scanning system, as it transforms the original point cloud and fits it into a regular grid, thus avoiding irregularities produced due to point density differences within the point cloud.

TL;DR: Results show that the apparent differences in point density and relative precision between both 3D forest models do not affect tree detection and DBH estimation, Nevertheless, tree height estimation using WLS appears to be affected by the limited scanning range of the WLS used in this study.

TL;DR: An automatic method to identify tree stems, and estimate tree heights and diameters from terrestrial laser scanning (TLS) data based on the isolation and vertical continuity of the stems showed robustness to the presence of steep or irregular terrain, the absence of low vegetation and artifacts at breast height, the indistinct use of individual or multiple scans, and tree density in the plot.

TL;DR: This work is focused on establishing a methodology and developing an algorithm to detect pole-like objects and classify them into several categories using MLS datasets, in order to simplify and reduce the processing time in the segmentation process.