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    Crop height monitoring using a consumer-grade camera and UAV Technology

    80284.pdf (1.722Mb)
    Access Status
    Open access
    Authors
    Belton, David
    Helmholz, Petra
    Long, John
    Zerihun, Ayalsew
    Date
    2019
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Belton, D. and Helmholz, P. and Long, J. and Zerihun, A. 2019. Crop height monitoring using a consumer-grade camera and UAV Technology. Journal of Photogrammetry, Remote Sensing and Geoinformation Science. 87 (5-6): pp. 249-262.
    Source Title
    Journal of Photogrammetry, Remote Sensing and Geoinformation Science
    DOI
    10.1007/s41064-019-00087-8
    ISSN
    2512-2789
    Faculty
    Faculty of Science and Engineering
    School
    School of Earth and Planetary Sciences (EPS)
    School of Molecular and Life Sciences (MLS)
    Remarks

    This is a post-peer-review, pre-copyedit version of an article published in Journal of Photogrammetry, Remote Sensing and Geoinformation Science. The final authenticated version is available online at: https://doi.org/10.1007/s41064-019-00087-8.

    URI
    http://hdl.handle.net/20.500.11937/80202
    Collection
    • Curtin Research Publications
    Abstract

    Recent advances in the ability to capture high spatial resolution images by unmanned aerial vehicles (UAVs) have shown the potential of this technology for a wide range of application including exploring the effects of different external stimuli when monitoring environmental and structural variables. In this paper, we show the application of UAV technology for crop height monitoring and modelling to provide quantitative crop growth data and demonstrate the remote sensing and photogrammetric capabilities of the technology to the farming industry. This study was carried out in a field trial involving a combination of six wheat varieties and three different fungicide treatments. The UAV imagery of the field trial site was captured on five occasions throughout crop development. These were used to create digital surface models from which crop surface models (CSMs) were extracted for the cropped areas. Crop heights are estimated from the photogrammetric derived CSMs and are compared against the reference heights captured using Real-Time Kinematic Global Navigation Satellite System (GNSS) to validate the CSMs. Furthermore, crop growth differences among varieties are analysed; and crop height correlations with grain yield as well as with independently estimated vegetation indices are evaluated. These evaluations show that the technology is suitable (with average bias range 2–10 cm depending on wind conditions relative to GNSS height) and has potential for quantitative and qualitative monitoring of canopy and/or crop height and growth.

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