Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV

Ilkka Pölönen; Heikki Saari; Jere Kaivosoja; E. Honkavaara; L. Pesonen

doi:10.1117/12.2028624

Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV

Ilkka Pölönen, Heikki Saari, Jere Kaivosoja, E. Honkavaara, L. Pesonen

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

52 Citations (Scopus)

Abstract

Hyperspectral imaging based precise fertilization is challenge in the northern Europe, because of the cloud conditions. In this paper we will introduce schemes for the biomass and nitrogen content estimations from hyperspectral images. In this research we used the Fabry-Perot interferometer based hypespectral imager that enables hyperspectral imaging from lightweight UAVs. During the summers 2011 and 2012 imaging and flight campaigns were carried out on the Finnish test field. Estimation mehtod uses features from linear and non-linear unmixing and vegetation indices. The results showed that the concept of small hyperspectral imager, UAV and data analysis is ready to operational use.

Original language	English
Title of host publication	Remote Sensing for Agriculture, Ecosystems, and Hydrology XV
Editors	Christopher M.U. Neale, Antonino Maltese
Place of Publication	Bellingham
Publisher	International Society for Optics and Photonics SPIE
ISBN (Print)	978-0-8194-9756-7
DOIs	https://doi.org/10.1117/12.2028624
Publication status	Published - 2013
MoE publication type	A4 Article in a conference publication
Event	Remote Sensing for Agriculture, Ecosystems, and Hydrology XV - Dresden, Germany Duration: 24 Sept 2013 → 26 Sept 2013 Conference number: 15

Publication series

Series	Proceedings of SPIE
Volume	8887
ISSN	0277-786X

Conference

Conference	Remote Sensing for Agriculture, Ecosystems, and Hydrology XV
Country/Territory	Germany
City	Dresden
Period	24/09/13 → 26/09/13

Keywords

biomass
hyperspectral imaging
nitrogen
UAV
unmixing

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10.1117/12.2028624

Cite this

Pölönen, I., Saari, H., Kaivosoja, J., Honkavaara, E., & Pesonen, L. (2013). Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV. In C. M. U. Neale, & A. Maltese (Eds.), Remote Sensing for Agriculture, Ecosystems, and Hydrology XV Article 88870J International Society for Optics and Photonics SPIE. https://doi.org/10.1117/12.2028624

Pölönen, Ilkka ; Saari, Heikki ; Kaivosoja, Jere et al. / Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV. Remote Sensing for Agriculture, Ecosystems, and Hydrology XV. editor / Christopher M.U. Neale ; Antonino Maltese. Bellingham : International Society for Optics and Photonics SPIE, 2013. (Proceedings of SPIE, Vol. 8887).

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title = "Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV",

abstract = "Hyperspectral imaging based precise fertilization is challenge in the northern Europe, because of the cloud conditions. In this paper we will introduce schemes for the biomass and nitrogen content estimations from hyperspectral images. In this research we used the Fabry-Perot interferometer based hypespectral imager that enables hyperspectral imaging from lightweight UAVs. During the summers 2011 and 2012 imaging and flight campaigns were carried out on the Finnish test field. Estimation mehtod uses features from linear and non-linear unmixing and vegetation indices. The results showed that the concept of small hyperspectral imager, UAV and data analysis is ready to operational use.",

keywords = "biomass, hyperspectral imaging, nitrogen, UAV, unmixing",

author = "Ilkka P{\"o}l{\"o}nen and Heikki Saari and Jere Kaivosoja and E. Honkavaara and L. Pesonen",

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editor = "Neale, {Christopher M.U.} and Antonino Maltese",

booktitle = "Remote Sensing for Agriculture, Ecosystems, and Hydrology XV",

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note = "Remote Sensing for Agriculture, Ecosystems, and Hydrology XV ; Conference date: 24-09-2013 Through 26-09-2013",

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Pölönen, I, Saari, H, Kaivosoja, J, Honkavaara, E & Pesonen, L 2013, Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV. in CMU Neale & A Maltese (eds), Remote Sensing for Agriculture, Ecosystems, and Hydrology XV., 88870J , International Society for Optics and Photonics SPIE, Bellingham, Proceedings of SPIE, vol. 8887, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV, Dresden, Saxony, Germany, 24/09/13. https://doi.org/10.1117/12.2028624

Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV. / Pölönen, Ilkka; Saari, Heikki; Kaivosoja, Jere et al.
Remote Sensing for Agriculture, Ecosystems, and Hydrology XV. ed. / Christopher M.U. Neale; Antonino Maltese. Bellingham: International Society for Optics and Photonics SPIE, 2013. 88870J (Proceedings of SPIE, Vol. 8887).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AU - Pölönen, Ilkka

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AU - Pesonen, L.

N1 - Conference code: 15

PY - 2013

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N2 - Hyperspectral imaging based precise fertilization is challenge in the northern Europe, because of the cloud conditions. In this paper we will introduce schemes for the biomass and nitrogen content estimations from hyperspectral images. In this research we used the Fabry-Perot interferometer based hypespectral imager that enables hyperspectral imaging from lightweight UAVs. During the summers 2011 and 2012 imaging and flight campaigns were carried out on the Finnish test field. Estimation mehtod uses features from linear and non-linear unmixing and vegetation indices. The results showed that the concept of small hyperspectral imager, UAV and data analysis is ready to operational use.

AB - Hyperspectral imaging based precise fertilization is challenge in the northern Europe, because of the cloud conditions. In this paper we will introduce schemes for the biomass and nitrogen content estimations from hyperspectral images. In this research we used the Fabry-Perot interferometer based hypespectral imager that enables hyperspectral imaging from lightweight UAVs. During the summers 2011 and 2012 imaging and flight campaigns were carried out on the Finnish test field. Estimation mehtod uses features from linear and non-linear unmixing and vegetation indices. The results showed that the concept of small hyperspectral imager, UAV and data analysis is ready to operational use.

KW - biomass

KW - hyperspectral imaging

KW - nitrogen

KW - UAV

KW - unmixing

U2 - 10.1117/12.2028624

DO - 10.1117/12.2028624

M3 - Conference article in proceedings

SN - 978-0-8194-9756-7

T3 - Proceedings of SPIE

BT - Remote Sensing for Agriculture, Ecosystems, and Hydrology XV

A2 - Neale, Christopher M.U.

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Y2 - 24 September 2013 through 26 September 2013

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Pölönen I, Saari H, Kaivosoja J, Honkavaara E, Pesonen L. Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV. In Neale CMU, Maltese A, editors, Remote Sensing for Agriculture, Ecosystems, and Hydrology XV. Bellingham: International Society for Optics and Photonics SPIE. 2013. 88870J . (Proceedings of SPIE, Vol. 8887). doi: 10.1117/12.2028624

Hyperspectral imaging based biomass and nitrogen content estimations from light-weight UAV

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