Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network
Pölönen, I., Annala, L., Rahkonen, S., Nevalainen, O., Honkavaara, E., Tuominen, S., Viljanen, N., & Hakala, T. (2019). Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network. In WHISPERS 2018 : 9th Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing. IEEE. https://doi.org/10.1109/WHISPERS.2018.8747253
© 2018 IEEE
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.
Parent publication ISBN978-1-7281-1581-8
ConferenceWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Is part of publicationWHISPERS 2018 : 9th Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Publication in research information system
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Funding program(s)Public research networked with companies, TEKES
Additional information about fundingThis research has been co-financed by Finnish Funding Agency for Innovation Tekes (grants 2208/31/2013 and 1711/31/2016)
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