Remote sensing of 3-D geometry and surface moisture of a peat production area using hyperspectral frame cameras in visible to short-wave infrared spectral ranges onboard a small Unmanned Airborne Vehicle (UAV)

Eija Honkavaara, Matti A. Eskelinen, Ilkka Pölönen, Heikki Saari, Harri Ojanen, Rami Mannila, Christer Holmlund, Teemu Hakala, Paula Litkey, tomi Rosnell, Niko Viljanen, Merja Pulkkanen

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    36 Citations (Scopus)


    Miniaturized hyperspectral imaging sensors are becoming available to small unmanned airborne vehicle (UAV) platforms. Imaging concepts based on frame format offer an attractive alternative to conventional hyperspectral pushbroom scanners because they enable enhanced processing and interpretation potential by allowing for acquisition of the 3-D geometry of the object and multiple object views together with the hyperspectral reflectance signatures. The objective of this investigation was to study the performance of novel visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral frame cameras based on a tunable Fabry-Pérot interferometer (FPI) in measuring a 3-D digital surface model and the surface moisture of a peat production area. UAV image blocks were captured with ground sample distances (GSDs) of 15, 9.5, and 2.5 cm with the SWIR, VNIR, and consumer RGB cameras, respectively. Georeferencing showed consistent behavior, with accuracy levels better than GSD for the FPI cameras. The best accuracy in moisture estimation was obtained when using the reflectance difference of the SWIR band at 1246 nm and of the VNIR band at 859 nm, which gave a root mean square error (rmse) of 5.21 pp (pp is the mass fraction in percentage points) and a normalized rmse of 7.61%. The results are encouraging, indicating that UAV-based remote sensing could significantly improve the efficiency and environmental safety aspects of peat production.
    Original languageEnglish
    Pages (from-to)5440-5454
    JournalIEEE Transactions on Geoscience and Remote Sensing
    Issue number9
    Publication statusPublished - 2016
    MoE publication typeA1 Journal article-refereed



    • calibration
    • geographic information system
    • geometry
    • image classification
    • radiometry
    • remote sensing
    • remotely piloted aircraft
    • spectroscopy
    • stereo vision
    • OtaNano

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