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
    @inproceedings{72476037d4e34f37bc6af7fe7c49519e,
    title = "Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system",
    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.",
    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",
    year = "2012",
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    language = "English",
    isbn = "978-1-6299-3368-9",
    volume = "I-7",
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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

    TY - GEN

    T1 - Hyperspectral reflectance signatures and point clouds for precision agriculture by light weight UAV imaging system

    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.

    PY - 2012

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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 - multispectral image sensors

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    KW - Fabry-Perot interferometer

    KW - piezo actuators

    KW - imaging spectrometer

    KW - UAV

    KW - airborne

    KW - medical imaging

    KW - precision agriculture

    KW - target detection

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    ER -

    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