Tree Species Recognition With Quantitative Structure Models

A quantitative structure model (QSM) contains the geometric and topological structure of a reconstructed tree. As such, QSMs enable computation of detailed tree properties that have been laborious or impossible to measure before. The computed tree properties can be used as classification features for tree species recognition. The first half of this video illustrates how we define the 15 classification features our research group has used for a species recognition study. An example QSM is used to visualize the relevant tree parts and key steps in the feature computations. The second half shows how the feature values of over a thousand Finnish trees of three different species, Silver birch, Scots pine and Norway Spruce, are distributed, and how well the species separate in the defined feature dimensions. One example QSM of each tree species shown on the right-hand-side with the only the tree parts visible that are related to the current feature. Table of contents: 0:01 Feature illustration 3:46 Viewer guide on screen elements 5:20 Feature value distributions 9:07 Credits The contents of this video link directly to the paper titled "Automatic tree species recognition with quantitative structure models" published in Remote Sensing of Environment (http://dx.doi.org/10.1016/j.rse.2016.12.002). For more information about QSMs, please visit the groups homepage, or watch the other videos on the topic: "3D Forest Information" (https://www.youtube.com/watch?v=wANRdliE1zQ) and "Cylinder reconstruction" (https://www.youtube.com/watch?v=j0Emjwp-fmU). This animation was produced by the Inverse Problems research group in the Department of Mathematics at Tampere University of Technology (http://math.tut.fi/inversegroup). Animation created using Blender 2.77a (http://www.blender.org). Music: "Life of Riley" "Thinking of you" "Jarvic 8" by Kevin MacLeod (http://incompetech.com) Licensed under Creative Commons: By Attribution 3.0 http://creativecommons.org/licenses/by/3.0/