A1 Journal article (refereed)
Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Species in a Forest Area of High Species Diversity (2018)

Tuominen, S., Näsi, R., Honkavaara, E., Balazs, A., Hakala, T., Viljanen, N., Pölönen, I., Saari, H., & Ojanen, H. (2018). Assessment of Classifiers and Remote Sensing Features of Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for Recognition of Tree Species in a Forest Area of High Species Diversity. Remote Sensing, 10(5), Article 714. https://doi.org/10.3390/rs10050714

JYU authors or editors

Publication details

All authors or editors: Tuominen, Sakari; Näsi, Roope; Honkavaara, Eija; Balazs, Andras; Hakala, Teemu; Viljanen, Niko; Pölönen, Ilkka; Saari, Heikki; Ojanen, Harri

Journal or series: Remote Sensing

ISSN: 2072-4292

eISSN: 2072-4292

Publication year: 2018

Volume: 10

Issue number: 5

Article number: 714

Publisher: MDPI

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.3390/rs10050714

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/58309

Keywords: remote sensing; aerial mapping; spectral imaging; tree stand; determination of species; machine learning; genetic algorithms; photogrammetry

Free keywords: hyperspectral imagery; tree species recognition; dense point cloud; reflectance calibration; UAV; random forest; genetic algorithm

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2018

JUFO rating: 1