Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system

E. Honkavaara, J. Kaivosoja, Jussi Mäkynen, I. Pellikka, L. Pesonen, Heikki Saari, H. Salo, T. Hakala, L. Marklelin, T. Rosnell

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

Abstract

The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, which is based on support vector regression machine. It was concluded that the central factors influencing on the accuracy of the estimation process were the quality of the image data, the quality of the image processing and digital surface model generation, and the performance of the regressor. In the wider perspective, our investigation showed that very low-weight, low-cost, hyperspectral, stereoscopic and spectrodirectional 3D UAV-remote sensing is now possible. This cutting edge technology is powerful and cost efficient in time-critical, repetitive and locally operated remote sensing applications.
Original languageEnglish
Title of host publicationXXII ISPRS Congress 2012
Subtitle of host publicationTechnical Commission VII
PublisherInternational Society for Photogrammetry and Remote Sensing ISPRS
Pages353-358
VolumeI-7
ISBN (Print)978-1-6299-3368-9
DOIs
Publication statusPublished - 2012
MoE publication typeA4 Article in a conference publication
Event2012 XXII ISPRS Congress - Melbourne, Australia
Duration: 25 Aug 20121 Sep 2012

Conference

Conference2012 XXII ISPRS Congress
CountryAustralia
CityMelbourne
Period25/08/121/09/12

Fingerprint

precision agriculture
reflectance
remote sensing
agricultural application
interferometer
cost
image processing
imagery
sensor
biomass
vehicle
cutting (process)
new technology
mosaic

Keywords

  • hyperspectral sensors
  • multispectral image sensors
  • remote sensing
  • Fabry-Perot interferometer
  • piezo actuators
  • imaging spectrometer
  • UAV
  • airborne
  • medical imaging
  • precision agriculture
  • target detection

Cite this

Honkavaara, E., Kaivosoja, J., Mäkynen, J., Pellikka, I., Pesonen, L., Saari, H., ... Rosnell, T. (2012). Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system. In XXII ISPRS Congress 2012: Technical Commission VII (Vol. I-7, pp. 353-358). International Society for Photogrammetry and Remote Sensing ISPRS. https://doi.org/10.5194/isprsannals-I-7-353-2012
Honkavaara, E. ; Kaivosoja, J. ; Mäkynen, Jussi ; Pellikka, I. ; Pesonen, L. ; Saari, Heikki ; Salo, H. ; Hakala, T. ; Marklelin, L. ; Rosnell, T. / Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system. XXII ISPRS Congress 2012: Technical Commission VII. Vol. I-7 International Society for Photogrammetry and Remote Sensing ISPRS, 2012. pp. 353-358
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keywords = "hyperspectral sensors, multispectral image sensors, remote sensing, Fabry-Perot interferometer, piezo actuators, imaging spectrometer, UAV, airborne, medical imaging, precision agriculture, target detection",
author = "E. Honkavaara and J. Kaivosoja and Jussi M{\"a}kynen and I. Pellikka and L. Pesonen and Heikki Saari and H. Salo and T. Hakala and L. Marklelin and T. Rosnell",
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Honkavaara, E, Kaivosoja, J, Mäkynen, J, Pellikka, I, Pesonen, L, Saari, H, Salo, H, Hakala, T, Marklelin, L & Rosnell, T 2012, Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system. in XXII ISPRS Congress 2012: Technical Commission VII. vol. I-7, International Society for Photogrammetry and Remote Sensing ISPRS, pp. 353-358, 2012 XXII ISPRS Congress, Melbourne, Australia, 25/08/12. https://doi.org/10.5194/isprsannals-I-7-353-2012

Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system. / Honkavaara, E.; Kaivosoja, J.; Mäkynen, Jussi; Pellikka, I.; Pesonen, L.; Saari, Heikki; Salo, H.; Hakala, T.; Marklelin, L.; Rosnell, T.

XXII ISPRS Congress 2012: Technical Commission VII. Vol. I-7 International Society for Photogrammetry and Remote Sensing ISPRS, 2012. p. 353-358.

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

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AU - Honkavaara, E.

AU - Kaivosoja, J.

AU - Mäkynen, Jussi

AU - Pellikka, I.

AU - Pesonen, L.

AU - Saari, Heikki

AU - Salo, H.

AU - Hakala, T.

AU - Marklelin, L.

AU - Rosnell, T.

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N2 - The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, which is based on support vector regression machine. It was concluded that the central factors influencing on the accuracy of the estimation process were the quality of the image data, the quality of the image processing and digital surface model generation, and the performance of the regressor. In the wider perspective, our investigation showed that very low-weight, low-cost, hyperspectral, stereoscopic and spectrodirectional 3D UAV-remote sensing is now possible. This cutting edge technology is powerful and cost efficient in time-critical, repetitive and locally operated remote sensing applications.

AB - The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, which is based on support vector regression machine. It was concluded that the central factors influencing on the accuracy of the estimation process were the quality of the image data, the quality of the image processing and digital surface model generation, and the performance of the regressor. In the wider perspective, our investigation showed that very low-weight, low-cost, hyperspectral, stereoscopic and spectrodirectional 3D UAV-remote sensing is now possible. This cutting edge technology is powerful and cost efficient in time-critical, repetitive and locally operated remote sensing applications.

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KW - imaging spectrometer

KW - UAV

KW - airborne

KW - medical imaging

KW - precision agriculture

KW - target detection

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Honkavaara E, Kaivosoja J, Mäkynen J, Pellikka I, Pesonen L, Saari H et al. Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system. In XXII ISPRS Congress 2012: Technical Commission VII. Vol. I-7. International Society for Photogrammetry and Remote Sensing ISPRS. 2012. p. 353-358 https://doi.org/10.5194/isprsannals-I-7-353-2012