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GCPs-Free Photogrammetry for Estimating Tree Height and Crown Diameter in Arizona Cypress Plantation Using UAV-Mounted GNSS RTK
One of the main challenges of using unmanned aerial vehicles (UAVs) in forest data acquisition is the implementation of Ground Control Points (GCPs) as a mandatory step, which is sometimes impossible for inaccessible areas or within canopy closures. This study aimed to test the accuracy of a UAV-mounted GNSS RTK (real-time kinematic) system for calculating tree height and crown height without any GCPs. The study was conducted on a Cupressus arizonica (Greene., Arizona cypress) plantation on the Razi University Campus in Kermanshah, Iran. Arizona cypress is commonly planted as an ornamental tree. As it can tolerate harsh conditions, this species is highly appropriate for afforestation and reforestation projects. A total of 107 trees were subjected to field-measured dendrometric measurements (height and crown diameter). UAV data acquisition was performed at three altitudes of 25, 50, and 100 m using a local network RTK system (NRTK). The crown height model (CHM), derived from a digital surface model (DSM), was used to estimate tree height, and an inverse watershed segmentation (IWS) algorithm was used to estimate crown diameter. The results indicated that the means of tree height obtained from field measurements and UAV estimation were not significantly different, except for the mean values calculated at 100 m flight altitude. Additionally, the means of crown diameter reported from field measurements and UAV estimation at all flight altitudes were not statistically different. Root mean square error (RMSE < 11%) indicated a reliable estimation at all the flight altitudes for trees height and crown diameter. According to the findings of this study, it was concluded that UAV-RTK imagery can be considered a promising solution, but more work is needed before concluding its effectiveness in inaccessible areas.
GCPs-Free Photogrammetry for Estimating Tree Height and Crown Diameter in Arizona Cypress Plantation Using UAV-Mounted GNSS RTK
One of the main challenges of using unmanned aerial vehicles (UAVs) in forest data acquisition is the implementation of Ground Control Points (GCPs) as a mandatory step, which is sometimes impossible for inaccessible areas or within canopy closures. This study aimed to test the accuracy of a UAV-mounted GNSS RTK (real-time kinematic) system for calculating tree height and crown height without any GCPs. The study was conducted on a Cupressus arizonica (Greene., Arizona cypress) plantation on the Razi University Campus in Kermanshah, Iran. Arizona cypress is commonly planted as an ornamental tree. As it can tolerate harsh conditions, this species is highly appropriate for afforestation and reforestation projects. A total of 107 trees were subjected to field-measured dendrometric measurements (height and crown diameter). UAV data acquisition was performed at three altitudes of 25, 50, and 100 m using a local network RTK system (NRTK). The crown height model (CHM), derived from a digital surface model (DSM), was used to estimate tree height, and an inverse watershed segmentation (IWS) algorithm was used to estimate crown diameter. The results indicated that the means of tree height obtained from field measurements and UAV estimation were not significantly different, except for the mean values calculated at 100 m flight altitude. Additionally, the means of crown diameter reported from field measurements and UAV estimation at all flight altitudes were not statistically different. Root mean square error (RMSE < 11%) indicated a reliable estimation at all the flight altitudes for trees height and crown diameter. According to the findings of this study, it was concluded that UAV-RTK imagery can be considered a promising solution, but more work is needed before concluding its effectiveness in inaccessible areas.
GCPs-Free Photogrammetry for Estimating Tree Height and Crown Diameter in Arizona Cypress Plantation Using UAV-Mounted GNSS RTK
Morteza Pourreza (author) / Fardin Moradi (author) / Mohammad Khosravi (author) / Azade Deljouei (author) / Melanie K. Vanderhoof (author)
2022
Article (Journal)
Electronic Resource
Unknown
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