Uas based tree species identification using the novel fpi based hyperspectral cameras in visible, nir and swir spectral ranges

R. Näsi, E. Honkavaara, S. Tuominen, H. Saari, I. Pölönen, T. Hakala, N. Viljanen, J. Soukkamäki, I. Näkki, H. Ojanen, J. Reinikainen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

6 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationXXIII ISPRS Congress, Commission I
PublisherInternational Society for Photogrammetry and Remote Sensing ISPRS
Pages1143-1148
DOIs
Publication statusPublished - 1 Jan 2016
MoE publication typeA4 Article in a conference publication
Event23rd International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Congress, ISPRS 2016 - Prague, Czech Republic
Duration: 12 Jul 201619 Jul 2016

Publication series

NameInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
ISSN (Print)1682-1750

Conference

Conference23rd International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Congress, ISPRS 2016
CountryCzech Republic
CityPrague
Period12/07/1619/07/16

Fingerprint

Fabry-Perot interferometers
interferometer
Cameras
remote sensing
Environmental engineering
monitoring
environmental monitoring
Image sensors
Remote sensing
Fusion reactions
Monitoring

Keywords

  • Hyperspectral
  • Photogrammetry
  • SWIR
  • Tree species
  • UAS

Cite this

Näsi, R., Honkavaara, E., Tuominen, S., Saari, H., Pölönen, I., Hakala, T., ... Reinikainen, J. (2016). Uas based tree species identification using the novel fpi based hyperspectral cameras in visible, nir and swir spectral ranges. In XXIII ISPRS Congress, Commission I (pp. 1143-1148). International Society for Photogrammetry and Remote Sensing ISPRS. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.. XLI-B1 https://doi.org/10.5194/isprsarchives-XLI-B1-1143-2016
Näsi, R. ; Honkavaara, E. ; Tuominen, S. ; Saari, H. ; Pölönen, I. ; Hakala, T. ; Viljanen, N. ; Soukkamäki, J. ; Näkki, I. ; Ojanen, H. ; Reinikainen, J. / Uas based tree species identification using the novel fpi based hyperspectral cameras in visible, nir and swir spectral ranges. XXIII ISPRS Congress, Commission I. International Society for Photogrammetry and Remote Sensing ISPRS, 2016. pp. 1143-1148 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B1).
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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.",
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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 XXIII ISPRS Congress, Commission I. International Society for Photogrammetry and Remote Sensing ISPRS, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLI-B1, pp. 1143-1148, 23rd International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Congress, ISPRS 2016, Prague, Czech Republic, 12/07/16. https://doi.org/10.5194/isprsarchives-XLI-B1-1143-2016

Uas based tree species identification using the novel fpi based hyperspectral cameras in visible, nir and swir spectral ranges. / Näsi, R.; Honkavaara, E.; Tuominen, S.; Saari, H.; Pölönen, I.; Hakala, T.; Viljanen, N.; Soukkamäki, J.; Näkki, I.; Ojanen, H.; Reinikainen, J.

XXIII ISPRS Congress, Commission I. International Society for Photogrammetry and Remote Sensing ISPRS, 2016. p. 1143-1148 (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B1).

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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T1 - Uas based tree species identification using the novel fpi based hyperspectral cameras in visible, nir and swir spectral ranges

AU - Näsi, R.

AU - Honkavaara, E.

AU - Tuominen, S.

AU - Saari, H.

AU - Pölönen, I.

AU - Hakala, T.

AU - Viljanen, N.

AU - Soukkamäki, J.

AU - Näkki, I.

AU - Ojanen, H.

AU - Reinikainen, J.

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N2 - 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.

AB - 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.

KW - Hyperspectral

KW - Photogrammetry

KW - SWIR

KW - Tree species

KW - UAS

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DO - 10.5194/isprsarchives-XLI-B1-1143-2016

M3 - Conference article in proceedings

T3 - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

SP - 1143

EP - 1148

BT - XXIII ISPRS Congress, Commission I

PB - International Society for Photogrammetry and Remote Sensing ISPRS

ER -

Näsi R, Honkavaara E, Tuominen S, Saari H, Pölönen I, Hakala T et al. Uas based tree species identification using the novel fpi based hyperspectral cameras in visible, nir and swir spectral ranges. In XXIII ISPRS Congress, Commission I. International Society for Photogrammetry and Remote Sensing ISPRS. 2016. p. 1143-1148. (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B1). https://doi.org/10.5194/isprsarchives-XLI-B1-1143-2016