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Using UAV LiDAR to Measure Tree Height in an Urban Atlantic Rain Forest
An international team of scientists from Brazil and the University of Florida are working together to study urban forests as a means of mitigating climate change. The University of Florida’s Second Generation GatorEye UAV LiDAR system uses a Phoenix Scout Ultra system to provide scientific backing for policies to preserve the forest inventory in the urban landscape.
This team’s objective is to improve what has been a difficult and costly data gathering process by incorporating remote sensing technology, such as UAV LiDAR, and to determine the levels of point density that return the best data. Ultimately, their goal is to increase the amount of research done on a part of the urban landscape that is difficult to research, and to provide decision makers with better information on which to base policy decisions.
This study looked closely at how other studies used LiDAR in similar situations. They found LiDAR is great for measuring tree parameters and designing vegetation structure 3D maps, and it provides spatial and temporal flexibility that other methods don’t offer. The other researchers got high resolution data at significantly lower cost, and also indicated applicability for urban forests using LiDAR alone or integrated with optical images.
LiDAR is more convenient than airborne LiDAR—lower cost, more accessible transportation, higher density of points. UAV LiDAR provides models with higher resolution, even though the value of point density influence for individual tree parameters is still not understood and needs further research.
Based on other studies’ findings, combining field-based research and remote sensing data seems to be best practice, especially if high-resolution LiDAR is available.
In November 2019, this Brazilian and U.S. team performed a physical measurement of 171 Brazilian pines, including circumference, height, and geographical position, in an urban forest remnant located in Curitiba, State of Parana, southern Brazil. They then collected the same trees’ data using UAV LiDAR and compared the data.
This team used the University of Florida GatorEye ‘Generation 2’ LiDAR system. It includes a modified Phoenix Scout Ultra system with a STIM300 Internal Motion Unit 111 (IMU), an L1/L2 dual-frequency GNSS receiver, an SSD drive, and a Velodyne 32c Ultra Puck. The Velodyne 32c accommodates 32 lasers with a range up to 220 m, providing an along-track field of view (FOV) of 40 degrees and 360 degrees of cross-track data. The post- processing kinematic (PPK) flight trajectory was produced with on-site base station data in Novatel Inertial Explorer software, providing an point cloud absolute spatial accuracy of approximately 5 cm RMSE.
Compared to the physical measurements, the LiDAR for tree profiles performed better with higher point cloud densities.
For example, the tree crowns captured at 75 meters from the ground returned more points than the tree stems. Lower density surveys captured the stems more poorly. However, digital terrain models were less affected by density, and while tree models benefited from higher density; overall statistics benefited from lower pulse density.
Depending on what is being studied, higher and lower LiDAR point densities have value, and UAV LiDAR provides higher point densities than traditional aircraft-mounted LiDAR, especially considering cost and operator experience factors for traditional methods. Further definition of the minimum point density for certain types of measurements is required, and the costs and machine effort required to process higher point densities is something to be considered.
