Improving quantitative structure models with an Huxley protocol based filter

Quantitative structure models (QSMs) are topological orderedcylinder models of trees whichdescribe the branching structure up to the tips.

We present unpublished tree describing parameters which can bederived from a single Quantitative Structure Model (QSM). The parameters areused to build two Radius correction filters.

For validation we use QSMs produced from an open point clouddata set of tree clouds with the SimpleForest software. We comparethe QSM volume against the harvested reference data for 65 felledtrees. We also found QSM data of TreeQSM, a competitive andbroadly accepted QSM modeling tool. Our RMSE was less than 40% of the TreeQSM RMSE.

For other error measures, the  r2adj. and the {CCC, the relative improvement looked even better withreaching only 27 % and 21 % of the TreeQSM errors respectively.

In forest ecology we should use the here presented pipelineto build accurate \texttt{QSMs} for reasons of:

Quality - With the invention of the{QSM Radius filter techniques we improve tree volume prediction capabilities utilizing QSMs.\\

Quantity - More data can be collected with QSMs than with traditional methods. Here we use models build on more than ten thousand measurements.