Abstract : Nowadays the use of remote sensing for vegetation mapping over large areas is becoming progressively common, with the increase of satellites providing a good trade-off between metric spatial resolution and large swath (e.g. Spot 5, RapidEye). Infra-metric imagery of Pléiades constellation offer valuable insights on vegetation structure. In the framework of the French national project CarHAB, this research aims at exploring the potential of this imagery and associated texture features (Haralick et SFS) in order to improve the discrimination of woody and herbaceous habitats and vegetation associated to screes. The work was tested in both, plain and mountainous environments in the French Alps (Isere Department). Promising results suggested that texture features derived from Pléiades imagery have a great potential discriminating vegetation structure. In all, the approach developed opens innovative ways towards a replicable rule-based classification scheme for vegetation mapping over open environments.
