Best Practices to Use the Ipad Pro Lidar for Some Procedures of Data Acquisition in the Urban Forest

SSRN Electronic Journal(2022)

引用 7|浏览3
暂无评分
摘要
The search for means to improve urban forest inventories is challenging for small communities and cities with a limited budget. Mobile applications on iPad or iPhone seem promising equipment to make some inventory practices cheaper and faster, although procedures of use are still limited. So, we tested the LiDAR scanner application on an iPad Pro 2020 for trunk perimeter measures and the position for 10 different groups of species in the Polish Airmen Park, Krak ' ow (Poland). For each group, in 10 trees, we measured the perimeter at breast height (PBH) and relative tree trunk position. The first procedure tested the estimation of PBH according to the distance of an iPad Pro from the trunk, the time of 3D data acquisition and the number of turns around trees. The second procedure tested PBH estimations according to the number of trees scanned in just one try (3, 6 and 10 trees). The third procedure tested the estimation of the relative position of tree trunks from other trees. In each procedure, we compared 3D point clouds generated by an App running on iPad Pro with data from a measuring tape and FARO FOCUS 3D (TLS) point clouds. The results showed that the shorter the distance from the iPad Pro to the trunk surface, the more precise the PBH estimation, not significantly different (p > 0,01) from TLS values. Distances between 1.0 and 2.0 m would be most suitable for the iPad Pro application but performing two turns around the tree trunk would improve results for PBH measurements. Trees scanned as 3-tree groups with the iPad Pro presented the smallest PBH differences compared to TLS point clouds. No significant differences (p > 0,01) were found between the methods for estimating the distance among trees, which shows that the iPad Pro can deliver a precise relative position of tree trunks.
更多
查看译文
关键词
Urban forestry,Tree inventory,Terrestrial Laser Scanning,Hand-held Laser Scanning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要