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

A study combining LiDAR, RADARSAT-2 radar, and SPOT-5 optical data achieved a mean accuracy of 90.60% in mapping wetland vegetation in the Danube Delta, one of the world's largest reed beds. The synergy of these datasets—LiDAR for centimeter-level vegetation height characterization (10 cm), RADARSAT-2's C-band polarimetric signatures, and SPOT-5 multispectral reflectance—enhanced discrimination between vegetation types by integrating structural and backscattering information. Field-recorded vegetation data validated the classification results, demonstrating the potential of integrated remote sensing for high-accuracy wetland mapping.

Niculescu, S., Lardeux, C., Grigoras, I., Hanganu, J., & David, L. (2016). Synergy Between LiDAR, RADARSAT-2, and Spot-5 Images for the Detection and Mapping of Wetland Vegetation in the Danube Delta. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(8), 3651–3666. https://doi.org/10.1109/jstars.2016.2545242