Calculation of biomass of individual trees on a combination of ground, aerial laser scanning and multispectral imagery from an unmanned aerial vehicle

Biomass is a key indicator for monitoring the global carbon cycle. Parameters of individual tree species in mixed forests are crucial for forestry, but research mainly focuses on forests dominated by a single species. The issue of biomass estimation in mixed forests remains underexplored. This study determined the biomass of various tree species in a mixed forest by integrating aerial and ground scanning data with multispectral aerial imagery. The study involved classifying trees using multispectral data combined with field surveys on a test plot, merging results from ground and aerial surveys, and using point clouds to measure tree diameter and height. Results indicate that with specialized processing of multispectral images, tree species can be identified with 63% accuracy, and individual tree biomass can be calculated using laser scanning data. Comparisons of tree diameters and heights from laser scanning and field measurements showed maximum discrepancies of 11%. Tree heights measured from point clouds were more accurate than field measurements, while trunk diameters from scanning and field data showed similar accuracy.