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README.md

@@ -28,4 +28,33 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-segmentation
+size_categories:
+- n<1K
 ---
+# Tree Crown Segmentation
+
+This dataset provides real multispectral imagery of Camellia oleifera tree crowns collected in a field environment in China. Captured using a UAV platform with a DJI Mavic 3 M drone featuring RGB and multispectral sensors, it offers high-resolution aerial data for semantic segmentation applications in agricultural monitoring. The dataset contains 595 images with pixel-level mask annotations.
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+The original train/test/val split has been preserved in the `split` column.
+
+## Citation
+
+```bibtex
+@article{peng2026uav,
+  title={UAV-based two-stage deep learning for tree crown segmentation and height estimation in Camellia oleifera plantations},
+  author={Peng, Yongkang and Yan, Enping and Xu, Xiaocheng and Mo, Dengkui and Wei, Wei},
+  journal={Ecological Informatics},
+  volume={96},
+  pages={103868},
+  year={2026},
+  publisher={Elsevier}
+}
+```
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*