Synergy Between LiDAR, RADARSAT-2, and Spot-5 Images for the Detection and Mapping of Wetland Vegetation in the Danube Delta

• Published in: IEEE journal of selected topics in applied earth observations and remote sensing Vol. 9; no. 8; pp. 3651 - 3666
• Main Authors: Niculescu, Simona, Lardeux, Cedric, Grigoras, Ion, Hanganu, Jenica, David, Laurence
• Format: Journal Article
• Language: English
• Published: IEEE 01-08-2016
• Subjects: Danube Delta; detection and mapping vegetation; Laser radar; multisensor data integration-LiDAR; Optical sensors; RADARSAT-2 and SPOT-5; Remote sensing; Satellites; Vegetation mapping; Wetlands
• ISSN: 1939-1404
• DOI: 10.1109/JSTARS.2016.2545242

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 June 4, 2011), and SPOT-5 optical data (acquired on May 25, 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.