Project-AgML/cocoa_tree_point_cloud_segmented

Cocoa Tree Point Cloud Segmented

This dataset provides real LiDAR point cloud data of cocoa trees in a field environment in Cameroon, collected for crop segmentation applications within agroforestry systems. Captured using a ground-based Leica ScanStation C10 during August 2019, it delivers high-resolution structural information of cocoa tree canopies for agricultural monitoring research. The dataset contains 85 images across 3 classes: full, leaf, wood.
Images per class:

• full: 48
• leaf: 9
• wood: 28

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{peynaud2024terrestrial,
  title={Terrestrial LiDAR point cloud dataset of cocoa trees grown in agroforestry systems in Cameroon},
  author={Peynaud, Emilie and Momo Takoudjou, Stéphane},
  journal={Data in Brief},
  volume={53},
  pages={110108},
  year={2024},
  publisher={Elsevier}
}

Momo Takoudjou, S., & Peynaud, E. (2021). Cocoa tree point clouds obtained by terrestrial Lidar scanning in agroforestry systems in Cameroon (Version V3) [dataset]. CIRAD Dataverse. https://doi.org/doi:10.18167/DVN1/5HZB1F

This dataset was reformatted from its original format to match HuggingFace standards.