Research on urban green areas can be approached in two ways: through individual tree analysis and areal analysis. The main difference between these approaches lies in the level of detail in the study. This research adopts an individual tree approach to obtain data on tree circumference, diameter, height, and position. The studied park is vertically poorly structured but highly heterogeneous in terms of tree distribution, height, circumference, and diameter, posing a significant challenge for modeling. Two field surveys were conducted: the first using traditional data collection methods with a Trimble R12i GNSS receiver and a tape measure, while the second utilized a DJI Matrice M300 RTK drone equipped with a Zenmuse L1 camera for aerial LiDAR scanning. In addition to aerial LiDAR scanning (ALS), terrestrial laser scanning (TLS) was conducted in a subsection of the research area, designated as study area B, using a Faro Focus M70. The research revealed that the positional accuracy obtained from ALS and TLS scanning is superior to the traditional method, and the tree height accuracy is better with ALS data due to the larger sample size compared to TLS data. Two software tools were compared in the study: CloudCompare (open-source software) and Spatix (commercial software). Spatix proved to be a simpler solution for tree modeling as it offers an automated data processing process with higher positional accuracy, allowing for the extraction of a greater number of trees. On the other hand, CloudCompare demonstrated greater accuracy in calculating trunk circumference for a smaller number of extracted trees.