B3 Non-refereed conference proceedings
Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network (2019)
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
JYU authors or editors
Publication details
All authors or editors: Pölönen, Ilkka; Annala, Leevi; Rahkonen, Samuli; Nevalainen, Olli; Honkavaara, Eija; Tuominen, Sakari; Viljanen, Niko; Hakala, Teemu
Parent publication: WHISPERS 2018 : 9th Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
ISBN: 978-1-7281-1581-8
ISSN: 2158-6276
Publication year: 2019
Publisher: IEEE
Publication country: United States
Publication language: English
DOI: https://doi.org/10.1109/WHISPERS.2018.8747253
Publication open access: Not open
Publication channel open access:
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/73412
Additional information: 2018 9th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). 23-26 Sept. 2018, Amsterdam, Netherlands.
Abstract
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.
Keywords: tree species; spectral imaging; Three-dimensional imaging; automated pattern recognition; neural networks (information technology)
Free keywords: 3D; convolutional neural network; UAV
Contributing organizations
Related projects
- DroneKnowledge – Towards knowledge based export of small UAS remote sensing technology
- Pölönen, Ilkka
- TEKES
Ministry reporting: Yes
Reporting Year: 2019