Mapping of conifer forest plantations using airborne hyperspectral and Lidar data

This paper addresses the feasibility of using lidar and hyperspectral data in order to discriminate between forest stands on the basis of species and age. The red edge position (REP) is computed for each hyperspectral pixel, using derivative-based methods. The spatial distribution of REP correlates well with species type and clearly distinguishes the broad-leaved category and as well as allowing discrimination of coniferous types in terms of species and age. The addition of mean canopy height, derived from co-registered first and last return Lidar data, helps to improve the discriminating power of the procedure.