Estimation of tree height using UAV photogrammetric data

Dimensional characterization of trees plays important roles in phytoremediation project of precision agriculture and environmental protection. The dimensional characterization can be evaluated by using UAV-based geomatic surveys. The work in this study applies low-cost UAV photogrammetry for tree height estimation, particularly for a phytoremediation project on contaminated soils. Two locations that had differing mean tree heights (7m and 4m) were used for the purpose of study. Three different UAV flights were carried out at 40m, 50m, and 60m altitudes in Area 1, an olive grove, and two different flights at 45m and 52m altitudes in Area 2, which has poplar species. The Structure from Motion (SfM) method, Vegetation Filter (VF), Digital Surface Models (DSMs), and Raster computational tool were used to process the UAV point clouds in order to produce Canopy Height Models (CHMs) for a local maximum driven extraction of tree height. Relatively, the results obtained from the tree height estimation experiment for the locations using UAV are higher than the results obtained using in-field measurement, thereby justifying the suitability of UAV photogrammetric data for tree height estimation.