Efficient and cost-effective monitoring of urban green spaces using combination of photogrammetry, LiDAR, and RTK in an iPhone-Based approach

Urban green spaces (UGS) provide various ecological, cultural, aesthetic, and psychological functions contributing to public health and well-being. To ensure proper management and the optimal performance of all these functions, it is essential to closely monitor their structure: number of trees, species composition, tree size, health status, location and surrounding objects. Traditionally, parameters are measured using conventional methods: calipers, altimeters, and diameter tapes. However, while modern 3D data collection technologies such as terrestrial and mobile laser scanners or photogrammetry have been employed for monitoring UGS, their use is often challenging. Therefore, we aimed to test and create a methodology using a novel device (Pix4D & Emlid Scanning Kit), which uniquely combines photogrammetry and light detection and ranging with real-time kinematics in a smartphone. Since the solution is smartphone-based, it provides relatively low-cost employability. The research was conducted in Adolf Priesol Park in Zvolen (Slovakia) over an area of approximately 6,000 m². We focused on the device’s positional accuracy in measuring footpaths, park amenities, and trees, as well as its tree detection rate and accuracy in determining tree diameter. The results demonstrated that the device exhibited high positional accuracy (horizontal RMSE = 0.08 m, vertical RMSE = 0.07 m), a 100% tree detection rate, and exceptional diameter at the breast height accuracy, with an RMSE of 1.1 cm in the area-based approach and 0.42 cm in the individual approach. Notably, the 6,000 m² area was covered in 80 minutes, including collecting almost 85 trees, all footpaths and all park amenities.