TREE SPECIES IDENTIFICATION USING 3D SPECTRAL DATA AND 3D CONVOLUTIONAL NEURAL NETWORK

被引：0

作者：

Polonen, Ilkka ^{[1
]}

Annala, Leevi ^{[1
]}

Rahkonen, Samuli ^{[1
]}

Nevalainen, Olli ^{[2
]}

Honkavaara, Eija ^{[2
]}

Tuominen, Sakari ^{[3
]}

Viljanen, Niko ^{[2
]}

Hakala, Teemu ^{[2
]}

机构：

[1] Univ Jyvaskyla, Fac Informat Technol, POB 35, FI-40014 Jyvaskyla, Finland

[2] Natl Land Survey Finland, Finnish Geospatial Res Insititute, Geodeetinrinne 2, Masala 02430, Finland

[3] Nat Resources Inst Finland, PL 2, Helsinki 00791, Finland

来源：

2018 9TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS) | 2018年

关键词：

Tree species; spectral imaging; 3D; convolutional neural network; UAV;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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 RUB camera, Achieved classification results arc promising by with overall accuracy of 96.2 % for the classification of the validation data set.

引用

页数：5

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