Lidar dataset paper; today's reading.

agricultural-robotics dataset diameter-at-breast-height forestry lidar today-i-read

  1. Derek Cheng et al., “ TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards .” arXiv, October 2023 [Online]. Available at: [Accessed: October 6, 2023]

    tl;dr: Dataset paper. Acquired LiDAR scans of forestry and large orchard trees (almond, pistachio) from under the canopy, using small UAVs or a mobile unit in a backpack or cart. Provides semantic segmentation labels of scans for tree stems, ground, and misc. Provides ground truth diameter at breast height (DBH) measurements. Baseline semantic segmentation methods are RangeNet++, SqueezeSegV2, and SqueezeSegV3. Baseline diameter estimation methods are DBCRE and SLOAM.

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