Best practices to use the iPad Pro LiDAR for some procedures of data acquisition in the urban forest

Rogerio Bobrowski, Monika Winczek, Karolina Zięba-Kulawik, Piotr Wężyk

Research output: Working paper

Abstract

The search for means to improve urban forest inventories is a challenging task for small communities and cities with a limited budget. Mobile applications on iPad or iPhone seem to be 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 position for 10 different groups of species in the Polish Airmen Park, Kraków. For each group, we measured 10 trees to get information about 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 scanning 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 trees’ trunks from other trees. In each procedure, we compared 3D point clouds acquired by iPad Pro with data from measuring tape and Faro TLS point clouds. The results showed that the shorter the distance from the iPad to the trunk surface – the PBH value estimation can be more precise, not significantly different (p>0,01) from the Faro TLS values. Distances between 1.0 and 2.0 m would be the best to use the iPad Pro application but performing two turns around the tree trunk would improve results for the PBH measurements. Trees scanned as 3-tree groups presented the smallest PBH differences when compared to Faro 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.
Original languageEnglish
Number of pages32
DOIs
Publication statusPublished - 16 Feb 2022

Publication series

NameSSRN
PublisherElsevier

Keywords

  • urban forestry
  • tree inventory
  • Terrestrial Laser Scanning
  • Mobile Laser Scanning

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