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    Optimising drone flight planning for measuring horticultural tree crop structure

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    pagination_PHOTO_3226.pdf
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    1.684Mb
    Format:
    PDF
    Description:
    Accepted manuscript
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    Type
    Article
    Authors
    Tu, Yu Hsuan cc
    Phinn, Stuart
    Phinn, Stuart cc
    Robson, Andrew
    Johansen, Kasper cc
    KAUST Department
    Biological and Environmental Sciences and Engineering (BESE) Division
    Hydrology, Agriculture and Land Observation Group, Water Desalination and Reuse Center, King Abdullah University of Science and Technology, Thuwal 23955-6900, Saudi Arabia
    Water Desalination and Reuse Research Center (WDRC)
    Date
    2019-12-18
    Online Publication Date
    2019-12-18
    Print Publication Date
    2020-02
    Embargo End Date
    2021-05-05
    Permanent link to this record
    http://hdl.handle.net/10754/660966
    
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    Abstract
    In recent times, multi-spectral drone imagery has proved to be a useful tool for measuring tree crop canopy structure. In this context, establishing the most appropriate flight planning variable settings is an essential consideration due to their controls on the quality of the imagery and derived maps of tree and crop biophysical properties. During flight planning, variables including flight altitude, image overlap, flying direction, flying speed and solar elevation, require careful consideration in order to produce the most suitable drone imagery. Previous studies have assessed the influence of individual variables on image quality, but the interaction of multiple variables has yet to be examined. This study assesses the influence of several flight variables on measures of data quality in each processing step, i.e. photo alignment, point cloud densification, 3D model building, and ortho-mosaicking. The analysis produced a drone flight planning and image processing workflow that delivers accurate measurements of tree crops, including the tie point quality, densified point cloud density, and the measurement accuracy of height and plant projective cover derived from individual trees within a commercial avocado orchard. Results showed that flying along the hedgerow, at high solar elevation and with low image pitch angles improved the data quality. Optimal flying speed needs to be set to achieve the required forward overlap. The impacts of each image acquisition variable are discussed in detail and protocols for flight planning optimisation for three scenarios with different drone settings are suggested. Establishing protocols that deliver optimal image acquisitions for the collection of drone data over horticultural tree crops, will create greater confidence in the accuracy of subsequent algorithms and resultant maps of biophysical properties.
    Citation
    Tu, Y.-H., Phinn, S., Johansen, K., Robson, A., & Wu, D. (2020). Optimising drone flight planning for measuring horticultural tree crop structure. ISPRS Journal of Photogrammetry and Remote Sensing, 160, 83–96. doi:10.1016/j.isprsjprs.2019.12.006
    Sponsors
    This research was funded by Department of Agriculture and Water Resources, Australian Government and Horticulture Innovation Australia as part of its Rural R&D for Profit Program's subproject “Multi-Scale Monitoring Tools for Managing Australia Tree Crops - Industry Meets Innovation” [grant number RnD4Profit-14-01-008].
    Publisher
    Elsevier BV
    Journal
    ISPRS Journal of Photogrammetry and Remote Sensing
    DOI
    10.1016/j.isprsjprs.2019.12.006
    Additional Links
    https://linkinghub.elsevier.com/retrieve/pii/S0924271619302941
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.isprsjprs.2019.12.006
    Scopus Count
    Collections
    Articles; Biological and Environmental Science and Engineering (BESE) Division; Water Desalination and Reuse Research Center (WDRC)

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