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pds4-tools>=1.3
colour-demosaicing>=0.2
colour-science>=0.4
scikit-image>=0.21
Pillow>=10.0
numpy>=1.24

Chang'E-4 TCM Dataset

Tools and data for terrain classification using Chang'E-4 Yutu-2 rover imagery.

Dataset: Segmentation masks are available on Hugging Face.

Note: Original Chang'E-4 images are not included due to copyright restrictions. You must download the source images directly from CLPDS (see instructions below).

Quick Start

# Install dependencies
pip install -r requirements.txt

# Convert PDS files to images
python scripts/convert_pds.py data/raw data/images

Downloading Chang'E-4 Data

Data is available from China's Lunar and Planetary Data System (CLPDS).

1. Register an Account

  1. Go to https://clpds.bao.ac.cn
  2. Create an account (check spam folder for confirmation email from NAOC)

2. Download Data

  1. Navigate to Chang'E-4 data search: https://clpds.bao.ac.cn/ce5web/searchOrder-ce4En.do
  2. Select an instrument:
    • PCAM - Panoramic Camera (rover, stereo pairs)
    • TCAM - Terrain Camera (lander)
    • LPR - Lunar Penetrating Radar
    • VNIS - Visible/Near-IR Spectrometer
  3. Choose data level (L2A or higher for calibrated data)
  4. Add files to cart and process order
  5. Download and extract to data/raw/

Data Format

Chang'E-4 uses PDS4 format:

  • XML label file (.xml) - metadata
  • Data file (.img, *L) - image data

Converting to Images

The conversion script applies debayering and contrast stretching:

# Convert all PDS files in data/raw to PNG
python scripts/convert_pds.py data/raw data/images

# Preview files without converting
python scripts/convert_pds.py data/raw data/images --dry-run

# Flatten output to single directory
python scripts/convert_pds.py data/raw data/images --flat

Processing Steps

  1. Read PDS4 file using pds4_tools
  2. Debayer raw Bayer images (PCAM full-resolution)
  3. Apply 2% linear contrast stretch
  4. Save as PNG

Project Structure

β”œβ”€β”€ data/
β”‚   β”œβ”€β”€ masks/        # Segmentation mask annotations (JSON)
β”‚   β”œβ”€β”€ raw/          # Downloaded PDS4 files (you provide)
β”‚   └── images/       # Converted PNG images (generated)
β”œβ”€β”€ docs/
β”‚   └── chinese-moon-data-access.md
β”œβ”€β”€ scripts/
β”‚   └── convert_pds.py
└── requirements.txt

References

Citation

If you use this dataset in your research, please cite:

@misc{chang4tcm2026,
  author       = {Yu, Sam and Huang, Christoper and Nasika, Tanvi and Shao, Yi and Singhania, Amay},
  title        = {Chang'E-4 Terrain Classification Dataset},
  year         = {2026},
  organization = {Lothan Space, IHS Maker Club},
  publisher    = {HuggingFace},
  url          = {https://huggingface.co/datasets/lothanspace/change4-tcm-dataset}
}

Please also cite the original data source:

@misc{clpds2025,
  author       = {{Ground Research and Application System of China's Lunar and Planetary Exploration Program}},
  title        = {Chang'E-4 Scientific Data},
  publisher    = {China National Space Administration},
  url          = {https://moon.bao.ac.cn}
}

License

The code and segmentation masks in this repository are licensed under CC BY-NC 4.0 (Creative Commons Attribution-NonCommercial 4.0). You are free to use, share, and adapt for non-commercial purposes with attribution.

Original Chang'E-4 imagery is owned by CLPDS/NAOC and must be downloaded directly from their portal. See docs/chinese-moon-data-access.md for their citation requirements.

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