README.md

metadata

license: cc-by-nc-sa-4.0
task_categories:
  - image-segmentation

The Dataset

The LandCover.ai (Land Cover from Aerial Imagery) dataset is a dataset for automatic mapping of buildings, woodlands, water and roads from aerial images.

Dataset features

• land cover from Poland, Central Europe (1)
• three spectral bands - RGB
• 33 orthophotos with 25 cm per pixel resolution (~9000x9500 px)
• 8 orthophotos with 50 cm per pixel resolution (~4200x4700 px)
• total area of 216.27 km2

Dataset format

• rasters are three-channel GeoTiffs with EPSG:2180 spatial reference system
• masks are single-channel GeoTiffs with EPSG:2180 spatial reference system

(1): Image source: Head Office of Geodesy and Cartography, Poland

Reproduce and compare

We provide split.py to split images into 512x512 pieces, and following files: train.txt, val.txt and test.txt containing lists of pieces used for training, validation and testing respectively.

Versions

Version 1

• classes: building (1), woodland (2), water(3), road(4)
• areas: 1.85 km2 of buildings, 72.02 km2 of woodlands, 13.15 km2 of water, 3.5 km2 of roads

Paper

Citation

To cite our work, please use the following:

@InProceedings{Boguszewski_2021_CVPR,
    author = {Boguszewski, Adrian and Batorski, Dominik and Ziemba-Jankowska, Natalia and Dziedzic, Tomasz and Zambrzycka, Anna},
    title = {LandCover.ai: Dataset for Automatic Mapping of Buildings, Woodlands, Water and Roads from Aerial Imagery},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
    month = {June},
    year = {2021},
    pages = {1102-1110}
}

License

This dataset is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Contact

If you encounter any problem or have any feedback, please contact [email protected]