Sadeghian, H., Naghavi, H., Maleknia, R., Soosani, J., & Pfeifer, N. (2022). Estimating the attributes of urban trees using terrestrial photogrammetry. Environmental Monitoring and Assessment, 194(9), Article 625. https://doi.org/10.34726/2521
3D model; Point clouds; Sample plot; SfM-MVS; Urban greening
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Abstract:
Today, different methods are used to measure two-dimensional (2D) and three-dimensional (3D) attributes of trees. One of these methods, which is considered in recent years is using point clouds and a 3D model extracted from terrestrial photogrammetry (TP). This study aims to estimate the 2D and 3D attributes of urban trees at three levels of seedlings, single trees and sample plot using TP. Structure-from-Motion with Multi-View Stereo-photogrammetry (SfM-MVS) method was used to derive the point clouds and the 3D model. Comparing estimated values of diameter at the middle of trunk of seedlings and diameter at breast height (DBH) of trees, using TP with measured values showed that the values of RMSE% were < 2% at three levels of seedlings, single trees and sample plot. Furthermore, validation of the estimated values of total height and crown height attributes of seedlings and trees at three levels showed that the RMSE% did not exceed 4% and 5%, respectively. Considering the overlap of tree crowns with each other in the sample plot, the average diameter of the crown attribute was estimated only in seedlings and single tree levels with RMSE% = 6.51% and 9.34%, respectively. The validation of estimated values of stem volume of seedlings and trees at three levels showed that the lowest errors were returned from trees within a sample plot with RMSE% = 14.37%, whereas the highest rates of errors were achieved for seedlings with RMSE% = 20.99%. As an alternative to approaches such as employing laser scanners, this method is quick, inexpensive, non-destructive, and does not need specialized equipment.
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Research Areas:
Efficient Utilisation of Material Resources: 50% Environmental Monitoring and Climate Adaptation: 50%
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Science Branch:
1059 - Sonstige und interdisziplinäre Geowissenschaften: 100%