Improving and Optimising Visualisations of Full-waveform LiDAR Data

dc.contributor.author	Miltiadou, Milto	en_US
dc.contributor.author	Campbell, Neill D. F.	en_US
dc.contributor.author	Brown, Matthew	en_US
dc.contributor.author	Cosker, Darren	en_US
dc.contributor.author	Grant, Michael	en_US
dc.contributor.editor	Cagatay Turkay and Tao Ruan Wan	en_US
dc.date.accessioned	2016-09-15T09:05:52Z
dc.date.available	2016-09-15T09:05:52Z
dc.date.issued	2016
dc.identifier.isbn	978-3-03868-022-2
dc.identifier.issn	-
dc.identifier.uri	http://dx.doi.org/10.2312/cgvc.20161295
dc.identifier.uri	https://diglib.eg.org:443/handle/10.2312/cgvc20161295
dc.description.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.	en_US
dc.publisher	The Eurographics Association	en_US
dc.title	Improving and Optimising Visualisations of Full-waveform LiDAR Data	en_US
dc.description.seriesinformation	Computer Graphics and Visual Computing (CGVC)
dc.description.sectionheaders	Image Based and Lighthing Techniques
dc.identifier.doi	10.2312/cgvc.20161295
dc.identifier.pages	45-47