Marine Biodiversity and Ecosystem Functioning
EU Network of Excellence

 
Main Menu

· Home
· Contacts
· Data Systems
· Documents
· FAQ
· Links
· MarBEF Open Archive
· Network Description
· Outreach
· Photo Gallery
· Quality Assurance
· Register of Resources
· Research Projects
· Rules and Guidelines
· Training
· Wiki
· Worldconference

 

Register of Resources (RoR)

 People  |  Datasets  |  Literature  |  Institutes  |  Projects 

[ report an error in this record ]basket (1): add | show Print this page

one publication added to basket [211021]
Synergy of airborne digital camera and Lidar data to map coastal dune vegetation
Kempeneers, P.; Deronde, B.; Provoost, S.; Houthuys, R. (2009). Synergy of airborne digital camera and Lidar data to map coastal dune vegetation. J. Coast. Res. SI 53: 73-82. dx.doi.org/10.2112/SI53-009.1
In: Journal of Coastal Research. Coastal Education and Research Foundation: Fort Lauderdale. ISSN 0749-0208; e-ISSN 1551-5036
Peer reviewed article  

Available in  Authors 

Author keywords
    lidar; vegetation classification; mapping; digital elevation models;

Authors  Top 
  • Kempeneers, P.
  • Deronde, B.
  • Provoost, S.
  • Houthuys, R.

Abstract
    Driven by the successful applications of lidar in forestry and the availability of lidar technology, new research is being carried out in other ecosystems. While lidar data have often been used to study tall forest ecosystems, this Study explores the utility of lidar in the lower-canopy ecosystems of the Belgian coastal dune belt. This area is largely covered by marram dune, moss dune, grassland, scrubs and some woodland. Small diameter (0.4 m) footprint lidar was applied to derive the canopy height by analyzing the first and last pulse returns simultaneously. The investigation focused on whether the height of low-canopy ecosystems Could be mapped with adequate accuracy. An error analysis was performed first on flat terrain (i.e., tennis court and parking lot) and then on vegetation canopy. The mapping of coastal dune vegetation is necessary to establish 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, 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 provided the extra information needed to obtain the desired vegetation and dune strength maps. A total of fourteen classes were defined, of which twelve cover vegetation. It was shown that overall classification accuracy improved 16%, from 55% to 71% after data fusion.

All data in the Integrated Marine Information System (IMIS) is subject to the VLIZ privacy policy Top | Authors 


If any information here appears to be incorrect, please contact us
Back to Register of Resources
 
Quick links

MarBEF WIKI

Erasmus Mundus Master of Science in Marine Biodiversity and Conservation (EMBC)
Outreach

Science
Responsive Mode Programme (RMP) - Marie Nordstrom, copyright Aspden Rebecca

WoRMS
part of WoRMS logo

ERMS 2.0
Epinephelus marginatus Picture: JG Harmelin

EurOBIS

Geographic System

Datasets

 


Web site hosted and maintained by Flanders Marine Institute (VLIZ) - Contact data-at-marbef.org