Abstract This study presents a capability analysis of the various options for the technical implementation of a two-wavelength laser altimeter for monitoring forests. The results of woodlands pieces identification statistical simulation for a neuronic net using experimentally measured spectral reflectance are presented. It is shown that the neuronic net provides a strong probability of correct identification when using information about the reflectivity and the height of woodlands pieces. Two wavelengths 532 and 1064 nm and the neuronic provide the probability of correct identification of green broad-leaved and needle-leaved trees understory, wetlands and ground vegetation of greater than 0.89 and the misidentification probability of lower than 0.055.