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dc.contributor.authorKEMPENEERS Pieteren_GB
dc.contributor.authorDERONDE Ben_GB
dc.contributor.authorPROVOOST S.en_GB
dc.contributor.authorHOUTHUYS S.en_GB
dc.date.accessioned2012-04-18T08:38:11Z-
dc.date.available2010-09-29en_GB
dc.date.available2012-04-18T08:38:11Z-
dc.date.created2009-02-02en_GB
dc.date.issued2009en_GB
dc.date.submitted2009-01-30en_GB
dc.identifier.citationJOURNAL OF COASTAL RESEARCH vol. Fall 2009 no. Special Issue 53 p. 73-82en_GB
dc.identifier.issn0749-0208en_GB
dc.identifier.urihttp://www.jcronline.org/toc/coas//10053en_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC50094-
dc.description.abstractDriven by the successful applications of LiDAR in forestry, and the availability of LiDAR technology, new research on other ecosystems is being carried out. While LiDAR data have often been used to study tall forest ecosystems, the current study explored their possibilities for the lower-canopy ecosystems in the Belgian coastal dune belt. This area is largely covered by marram dune, moss dune, grassland, scrubs and some woodland. Small diameter (0.4m) footprint LiDAR was applied to derive the canopy height by analyzing the first and last pulse returns simultaneously. It was investigated whether the height of low-canopy ecosystems could be mapped with adequate accuracy. An error analysis was performed first on flat terrain (tennis court and parking lot) and then on vegetation canopy. The mapping of coastal dune vegetation is a necessary element in the definition of the strength of the dune belt. Dune vegetation fixes the sand dunes, protecting them from erosion and from possible breakthroughs threatening the historically reclaimed land (polders) situated inland from the dunes. Next to the LiDAR data, multispectral data was acquired from a digital camera with visual and near infrared channels. The digital camera overflight was not conducted on the same platform as the LiDAR. After ortho-rectification of the multispectral image, the data of both sources were fused. The limited spectral information delivered by the digital camera was not able to provide a sufficiently detailed and accurate vegetation map. The fusion with LiDAR data provides the extra information needed to obtain the desired vegetation and dune strength maps. A total of 14 classes were defined, from which 12 cover vegetation. It was shown that classification accuracy can be improved with 16% from 55% to 71% after data fusion.en_GB
dc.description.sponsorshipJRC.H.7-Climate Risk Managementen_GB
dc.format.mediumPrinteden_GB
dc.languageENGen_GB
dc.publisherCOASTAL EDUCATION & RESEARCH FOUNDATIONen_GB
dc.relation.ispartofseriesJRC50094en_GB
dc.titleSynergy of Airborne Digital Camera and LiDAR Data to Map Coastal Dune Vegetationen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.2112/SI53-009.1en_GB
JRC Directorate:Sustainable Resources

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