IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING SYNERGY BETWEEN LiDAR, RADARSAT-2 AND SPOT-5 IMAGES FOR THE DETECTION AND MAPPING OF WETLAND VEGETATION IN THE DANUBE DELTA
Fiche du document
5 août 2016
- handle: 10670/1.sxy09i
- hal: hal-01516930
- doi: 10.1109/JSTARS.2016.2545242
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1109/JSTARS.2016.2545242
info:eu-repo/semantics/OpenAccess
Mots-clés
Wetlands Danube Delta detection and mapping vegetation multisensor data integration-LiDAR RADARSAT-2 and SPOT-5.Sujets proches
Vegetable kingdom Plantae Plant kingdom Vegetation Wildlife FloraCiter ce document
Simona Niculescu et al., « IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING SYNERGY BETWEEN LiDAR, RADARSAT-2 AND SPOT-5 IMAGES FOR THE DETECTION AND MAPPING OF WETLAND VEGETATION IN THE DANUBE DELTA », HAL-SHS : géographie, ID : 10.1109/JSTARS.2016.2545242
Métriques
Partage / Export
Résumé
Wetlands are among the most productive natural environments on Earth, as they harbor exceptional biological diversity. For this paper, our study site was the Danube Delta. The biodiversity of the Danube Delta is extraordinary and it possesses one of the largest reed beds in the world. The main goal of our paper was to recognize, characterize and map the main vegetation units of the Danube Delta. The paper emphasizes the importance of the joint use of LiDAR measurements (acquired in May 2011), RADARSAT-2 radar data (acquired on 4 June 2011) and SPOT-5 optical data (acquired on 25 May 2011). LiDAR data allow for the characterization of vegetation height within centimeter accuracy (10 cm). The radar measurements are based on C-band, providing additional information about the structure of the vegetation cover. The simultaneous acquisition of HH, HV, VV and VH polarizations enabled us to discriminate between the targets, depending on their responses to the various polarizations, by calculating their polarimetric signatures. By linking multispectral LiDAR and radar data, information can be obtained about vegetation reflectance and height as well as the backscattering mechanism, allowing for improved mapping and characterization accuracy (90.60% mean accuracy). An accuracy assessment of the classification results was evaluated against the vegetation data recorded in the field.