Improving and Optimising Visualisations of Full-waveform LiDAR Data
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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 {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}
}
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}
}