EVALUATING THE POSSIBILITY OF TREE SPECIES CLASSIFICATION WITH DUAL-WAVELENGTH ALS DATA

Abstract. Airborne laser scanning (ALS) plays an important role in spatial data acquisition. One of the advantages of this technique is laser beam penetration through vegetation, which makes it possible to not only obtain data on the tree canopy but also within and under the canopy. In recent years, multi-wavelength airborne laser scanning has been developed. This technique consists of simultaneous acquisition of point clouds in more than one band. The aim of this experiment was to examine and assess the possibilities of tree segmentation and species classification in an urban area. In this experiment, point clouds registered in two wavelengths (532 and 1064 nm) were used for tree segmentation and species classification. The data were acquired with a Riegl VQ-1560i-DW laser scanner over Elblag, Poland, during August 2018. Tree species collected by a botanist team within terrain measurements were used as a reference in the classification process. Within the experiment segmentation and classification process were performed. Regarding the segmentation, TerraScan software and Li et al.’s algorithm, implemented in LidR package were used. Results from both methods are clearly over-segmented in comparison to the manual segments. In Terrasolid segmentation, single reference segments are over-segmented in 28% of cases, whereas, for LidR, over-segmentation occurred in 73% of the segments. According the classification results, Thuja, Salix and Betula were the species, for which the highest classification accuracy was achieved.