Abstract
Abstract Purpose of Review In recent years, the use of 3D point clouds in silviculture and forest ecology has seen a large increase in interest. With the development of novel 3D capture technologies, such as laser scanning, an increasing number of algorithms have been developed in parallel to process 3D point cloud data into more tangible results for forestry applications. From this variety of available algorithms, it can be challenging for users to decide which to apply to fulfil their goals best. Here, we present an extensive overview of point cloud acquisition and processing tools as well as their outputs for precision forestry. We then provide a comprehensive database of 24 algorithms for processing forest point clouds obtained using close-range techniques, specifically ground-based platforms. Recent Findings Of the 24 solutions identified, 20 are open-source, two are free software, and the remaining two are commercial products. The compiled database of solutions, along with the corresponding technical guides on installation and general use, is accessible on a web-based platform as part of the COST Action 3DForEcoTech. The database may serve the community as a single source of information to select a specific software/algorithm that works for their requirements. Summary We conclude that the development of various algorithms for processing point clouds offers powerful tools that can considerably impact forest inventories in the future, although we note the necessity of creating a standardisation paradigm.
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