In forestry, the airborne laser scanning is already being used for various purposes. Data gathered from airborne laser scanning besides positional coordinates also provides surface reflectance from which the laser echoes derived. Echoes intensity describes surface reflectance, upon which some authors already tried to classify individual tree species. By comparing average intensities of individual trees species we assessed characteristic values, which could belong to specified tree species. Four sets of data where included into analysis. First two datasets where gathered in leaf on with wavelength of 1550 nm. First dataset was gathered in spring; second set was gathered in late summer. Third and fourth dataset were gathered with wavelength of 1064 nm, in which the third set was gathered in leaf off, but the fourth in leaf on.
Fifty-seven coniferous and fifty-six deciduous trees, together hundred thirteen diverse tree species were included into analysis. Within conifers, we point our focus onto spruce and larch. Among deciduous the focus was on walnut, maple, ash and linden. We found out that classification between coniferous and deciduous is much more reliable in leaf off. Average intensity of coniferous is twice the average intensity of deciduous, the more so with third dataset in which 1064 nm wavelength has been used. Difference in average intensities between deciduous and coniferous also stand out in leaf on. Average intensity of deciduous is higher than average intensity of coniferous. Differences are bigger in the forth dataset (1064 nm) and smaller in the first and the second datasets (1550 nm). In general, our research also shows that intensity of bark and wood is lower than the intensity of needles and leaves. It also turns out that according to the decrease or increase proportion of first echoes in the specific wavelength it can be distinguished whether deciduous are leaf on or not. In this way, we found out that walnut and ash in the first dataset have not had yet fully developed crown in comparison to maple and linden.