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Comparison of UAV- and mowing machine-mounted LiDAR for grassland canopy height estimation

Justus Bracke; Marcel Storch; Janis Bald; Thomas Jarmer
In: Biodiversität fördern durch digitale Landwirtschaft: Welchen Beitrag leisten KI und Co?. GIL-Jahrestagung (GIL-2024), February 27-28, Hohenheim, Germany, Gesellschaft für Informatik, 2024.


Towards autonomous process monitoring, canopy height estimation in grassland based on data from a mowing machine-mounted LiDAR and a UAV-LiDAR system is compared to manually measured ground truth heights. In a field trial, a LiDAR mounted on the cabin roof of the mowing machine recorded data during the mowing process, while two recording flights before and after the mowing were conducted with a UAV-LiDAR. The data from both systems were processed similarly and parameters such as height estimation method, spatial resolution and percentile filters were systematically varied to investigate their influence on height estimation accuracy. Statistical evaluation showed that canopy height estimates based on the UAV-LiDAR (R² = 0.89, RMSE = 0.05 m) were more accurate and precise than those based on the mowing machine-mounted LiDAR (R² = 0.51, RMSE = 0.08 m). The influence of the different investigated parameters varied.


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