Project-AgML/subalpine_forest_segmentation

Subalpine Forest Segmentation

This dataset provides real RGB imagery of subalpine forest ecosystems captured in the field using a DJI Mavic 2 UAV equipped with a 1-inch CMOS camera. Collected on June 15, 2020, in Wanglang National Nature Reserve, China, the images depict natural forest structures and ground cover under typical high-altitude temperate conditions. It serves as a field-based resource for semantic segmentation tasks in ecological monitoring and forest analysis. The dataset contains 11,336 images with pixel-level mask annotations.

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

Citation

@article{shi2025evaluation,
  title={Evaluation of a CNN model to map vegetation classification in a subalpine coniferous forest using UAV imagery},
  author={Shi, Weibo and Liao, Xiaohan and Wang, Shaoqiang and Ye, Huping and Wang, Dongliang and Yue, Huanyin and Liu, Jianli},
  journal={Ecological Informatics},
  volume={87},
  pages={103111},
  year={2025},
  publisher={Elsevier}
}

Shi, weibo (2025), “CNN model to map vegetation classification in a subalpine coniferous forest using UAV imagery”, Mendeley Data, V2, doi: 10.17632/d9f4m2735b.2

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