SimpleForest - a comprehensive tool for 3d reconstruction of trees from forest plot point clouds
Authors: Jan Hackenberg , Kim Calders , Demol Miro , Raumonen Pasi , Piboule Alexandre , Mathias Disney 
Published: July 2021

The here-on presented SimpleForest is written in C++ and published under GPL v3. As input data SimpleForest utilizes forestry scenes recorded as terrestrial laser scan clouds. SimpleForest provides a fully automated pipeline to model the ground as a digital terrain model, then segment the vegetation and finally build quantitative structure models of trees (QSMs) consisting of up to thousands of topologically ordered cylinders. These QSMs allow us to calculate traditional forestry metrics such as diameter at breast height, but also volume and other structural metrics that are hard to measure in the field. Our volume evaluation on three data sets with destructive volumes show high prediction qualities with concordance correlation coefficientCCCof 0.91 (0.87), 0.94 (0.92) and 0.97 (0.93) for each data set respectively.

We combine two common assumptions in plant modeling “The sum of cross sectional areas after a branch junction equals the one before the branch junction” (Pipe Model Theory) and “Twigs are self-similar” (West, Brown and Enquist model). As even sized twigs correspond to even sized cross sectional areas for twigs we define theReverse Pipe Radius Branchorder(RPRB) as the square root of the number of supported twigs. The prediction modelradius=B0*RPRBrelies only on correct topological information and can be used to detect and correct overestimated cylinders. In QSM building the necessity to handle overestimated cylinders is well known. The RPRB correction performs better with aCCCof 0.97 (0.93) than former published ones 0.80 (0.88) and 0.86 (0.85) in our validation.

We encourage forest ecologists to analyze output parameters such as theGrowthVolumepublished in earlier works, but also other parameters such as theGrowthLength, VesselVolumeandRPRBwhich we define in this manuscript.

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