Estimation of breast height diameter and trunk curvature with linear and single-photon LiDARs

Jari M. Ahola, Tapio Heikkilä (Corresponding Author), Jyrki Raitila, Teemu Sipola, Jussi Tenhunen

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Abstract

Key message
New technologies can take us towards real precision forestry: the terrestrial single-photon avalanche diode (SPAD) light detection and ranging (LiDAR) has a great potential to outperform conventional linear mode LiDARs in
measuring tree parameters at the stand level.
Context
Precision forestry together with new sensor technologies implies Digital Forest Inventories for estimation of volume and quality of trees in a stand.
Aims
This study compared commercial LiDAR, new prototype SPAD LiDAR, and manual methods for measuring tree quality attributes, i.e., diameter at breast height (DBH) and trunk curvature in the forest stand.
Methods
We measured 7 Scots pine trees (Pinus sylvestris) with commercial LiDAR (Zeb Horizon by GeoSLAM), prototype SPAD LiDAR, and manual devices. We compared manual measurements to the DBH and curvature values estimated based on LiDAR data. We also scanned a densely branched Picea abies to compare penetrability of the LiDARs and detectability of the obstructed trunk.
Results
The DBH values deviated 1–3 cm correlating to the specifed accuracies of the employed devices, showing close to acceptable results. The curvature values deviated 1–6 cm implying distorted range measurements from the top part of the
trunks and inaccurate manual measurement method, leaving space for improvement. The most important fnding was that the SPAD LiDAR outperformed conventional LiDAR in detecting tree stem of the densely branched spruce.
Conclusion
These results represent preliminary but clear evidence that LiDAR technologies are already close to acceptable level in DBH measurements, but not yet satisfactory for curvature measurements. In addition, terrestrial SPAD LiDAR has a great potential to outperform conventional LiDARs in forest measurements of densely branched trees.
Original languageEnglish
Article number79
Number of pages13
JournalAnnals of Forest Science
Volume78
Issue number3
DOIs
Publication statusPublished - 13 Sep 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • Forest inventory
  • Single-photon LiDAR

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