Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network

Abstract

In this study we apply 3D convolutional neural network (CNN) for tree species identification. Study includes the three most common Finnish tree species. Study uses a relatively large high-resolution spectral data set, which contains also a digital surface model for the trees. Data has been gathered using an unmanned aerial vehicle, a framing hyperspectral imager and a regular RGB camera. Achieved classification results are promising by with overall accuracy of 96.2 % for the classification of the validation data set.