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

Pölönen, Ilkka; Annala, Leevi; Rahkonen, Samuli; Nevalainen, Olli; Honkavaara, Eija; Tuominen, Sakari; Viljanen, Niko; Hakala, Teemu

doi:10.1109/WHISPERS.2018.8747253

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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

Tekijät

Annala, Leevi |

Viljanen, Niko |

Päivämäärä

2019

Oppiaine

Tietotekniikka Mathematical Information Technology

Tekijänoikeudet

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.

Julkaisija

IEEE

Emojulkaisun ISBN

978-1-7281-1581-8

Konferenssi

Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing

Kuuluu julkaisuun

WHISPERS 2018 : 9th Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing

ISSN Hae Julkaisufoorumista

2158-6276

Rahoittaja(t)

TEKES

Rahoitusohjelmat(t)

Elinkeinoelämän kanssa verkottunut tutkimus, TEKES

Lisätietoja rahoituksesta

This research has been co-financed by Finnish Funding Agency for Innovation Tekes (grants 2208/31/2013 and 1711/31/2016)

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