dc.contributor.author | Näsi, R. | |
dc.contributor.author | Honkavaara, E. | |
dc.contributor.author | Tuominen, S. | |
dc.contributor.author | Saari, H. | |
dc.contributor.author | Pölönen, Ilkka | |
dc.contributor.author | Hakala, T. | |
dc.contributor.author | Viljanen, N. | |
dc.contributor.author | Soukkamäki, J. | |
dc.contributor.author | Näkki, I. | |
dc.contributor.author | Ojanen, H. | |
dc.contributor.author | Reinikainen, J. | |
dc.contributor.editor | Halounova, L. | |
dc.contributor.editor | Šaafář, V. | |
dc.contributor.editor | Toth, C. K. | |
dc.contributor.editor | Karas, J. | |
dc.contributor.editor | Huadong, G. | |
dc.contributor.editor | Haala, N. | |
dc.contributor.editor | Habib, A. | |
dc.contributor.editor | Reinartz, P. | |
dc.contributor.editor | Tang, X. | |
dc.contributor.editor | Li, J. | |
dc.contributor.editor | Armenakis, C. | |
dc.contributor.editor | Grenzdörffer, G. | |
dc.contributor.editor | Roux, P. le | |
dc.contributor.editor | Stylianidis, S. | |
dc.contributor.editor | Blasi, R. | |
dc.contributor.editor | Menard, M. | |
dc.contributor.editor | Dufourmount, H. | |
dc.contributor.editor | Li, Z. | |
dc.date.accessioned | 2016-08-29T09:37:59Z | |
dc.date.available | 2016-08-29T09:37:59Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Näsi, R., Honkavaara, E., Tuominen, S., Saari, H., Pölönen, I., Hakala, T., Viljanen, N., Soukkamäki, J., Näkki, I., Ojanen, H., & Reinikainen, J. (2016). UAS based tree species identification using the novel FPI based hyperspectral cameras in visible, NIR and SWIR spectral ranges. In L. Halounova, V. Šaafář, C. K. Toth, J. Karas, G. Huadong, N. Haala, A. Habib, P. Reinartz, X. Tang, J. Li, C. Armenakis, G. Grenzdörffer, P. L. Roux, S. Stylianidis, R. Blasi, M. Menard, H. Dufourmount, & Z. Li (Eds.), <i>Proceedings of the XXIII ISPRS Congress</i> (pp. 1143-1148). International Society for Photogrammetry and Remote Sensing. International archives of the photogrammetry, remote sensing and spatial information sciences, Volume XLI-B1. <a href="https://doi.org/10.5194/isprs-archives-XLI-B1-1149-2016" target="_blank">https://doi.org/10.5194/isprs-archives-XLI-B1-1149-2016</a> | |
dc.identifier.other | CONVID_26131605 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/51112 | |
dc.description.abstract | Unmanned airborne systems (UAS) based remote sensing offers flexible tool for environmental monitoring. Novel lightweight
Fabry-Perot interferometer (FPI) based, frame format, hyperspectral imaging in the spectral range from 400 to 1600 nm was used for
identifying different species of trees in a forest area. To the best of the authors’ knowledge, this was the first research where
stereoscopic, hyperspectral VIS, NIR, SWIR data is collected for tree species identification using UAS. The first results of the
analysis based on fusion of two FPI-based hyperspectral imagers and RGB camera showed that the novel FPI hyperspectral
technology provided accurate geometric, radiometric and spectral information in a forested scene and is operational for
environmental remote sensing applications. | |
dc.language.iso | eng | |
dc.publisher | International Society for Photogrammetry and Remote Sensing | |
dc.relation.ispartof | Proceedings of the XXIII ISPRS Congress | |
dc.relation.ispartofseries | International archives of the photogrammetry, remote sensing and spatial information sciences | |
dc.relation.uri | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B1/1143/2016/isprs-archives-XLI-B1-1143-2016.pdf | |
dc.subject.other | UAS | |
dc.subject.other | hyperspectral | |
dc.subject.other | SWIR | |
dc.title | UAS based tree species identification using the novel FPI based hyperspectral cameras in visible, NIR and SWIR spectral ranges | |
dc.type | conference paper | |
dc.identifier.urn | URN:NBN:fi:jyu-201607263675 | |
dc.contributor.laitos | Tietotekniikan laitos | fi |
dc.contributor.laitos | Department of Mathematical Information Technology | en |
dc.contributor.oppiaine | Tietotekniikka | fi |
dc.contributor.oppiaine | Mathematical Information Technology | en |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | |
dc.date.updated | 2016-07-26T12:15:13Z | |
dc.type.coar | http://purl.org/coar/resource_type/c_5794 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 1143-1148 | |
dc.relation.issn | 1682-1750 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © the Authors, 2016. This is an open access article distributed under the terms of Creative Commons License. | |
dc.rights.accesslevel | openAccess | fi |
dc.type.publication | conferenceObject | |
dc.relation.conference | Congress of the International Society for Photogrammetry and Remote Sensing | |
dc.subject.yso | fotogrammetria | |
dc.subject.yso | puulajit | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2525 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p13848 | |
dc.rights.url | https://creativecommons.org/licenses/by/3.0/ | |
dc.relation.doi | 10.5194/isprs-archives-XLI-B1-1149-2016 | |
dc.type.okm | A4 | |