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    Improving and Optimising Visualisations of Full-waveform LiDAR Data

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    Date
    2016
    Author
    Miltiadou, Milto
    Campbell, Neill D. F.
    Brown, Matthew
    Cosker, Darren
    Grant, Michael
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    Abstract
    Visualisations of Remotely Sensed data has a significant role in forestry. Foresters have a great knowledge about forests (for example they can identify tree diseases) and they can derive a wealth of information directly from visualisations, saving the travelling time and cost of getting into the forests.
    BibTeX
    @inproceedings {10.2312:cgvc.20161295,
    booktitle = {Computer Graphics and Visual Computing (CGVC)},
    editor = {Cagatay Turkay and Tao Ruan Wan},
    title = {{Improving and Optimising Visualisations of Full-waveform LiDAR Data}},
    author = {Miltiadou, Milto and Campbell, Neill D. F. and Brown, Matthew and Cosker, Darren and Grant, Michael},
    year = {2016},
    publisher = {The Eurographics Association},
    ISSN = {-},
    ISBN = {978-3-03868-022-2},
    DOI = {10.2312/cgvc.20161295}
    }
    URI
    http://dx.doi.org/10.2312/cgvc.20161295
    https://diglib.eg.org:443/handle/10.2312/cgvc20161295
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    • Computer Graphics & Visual Computing (CGVC) 2016

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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
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