eurosat

  • Description:

EuroSAT dataset is based on Sentinel-2 satellite images covering 13 spectral bands and consisting of 10 classes with 27000 labeled and geo-referenced samples.

Two datasets are offered: - rgb: Contains only the optical R, G, B frequency bands encoded as JPEG image. - all: Contains all 13 bands in the original value range (float32).

URL: https://github.com/phelber/eurosat

Split Examples
'train' 27,000
  • Citation:
@misc{helber2017eurosat,
    title={EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification},
    author={Patrick Helber and Benjamin Bischke and Andreas Dengel and Damian Borth},
    year={2017},
    eprint={1709.00029},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

eurosat/rgb (default config)

  • Config description: Sentinel-2 RGB channels

  • Download size: 89.91 MiB

  • Dataset size: 89.50 MiB

  • Auto-cached (documentation): Yes

  • Feature structure:

FeaturesDict({
    'filename': Text(shape=(), dtype=string),
    'image': Image(shape=(64, 64, 3), dtype=uint8),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=10),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
filename Text string
image Image (64, 64, 3) uint8
label ClassLabel int64

Visualization

eurosat/all

  • Config description: 13 Sentinel-2 channels

  • Download size: 1.93 GiB

  • Dataset size: 5.36 GiB

  • Auto-cached (documentation): No

  • Feature structure:

FeaturesDict({
    'filename': Text(shape=(), dtype=string),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=10),
    'sentinel2': Tensor(shape=(64, 64, 13), dtype=float32),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
filename Text string
label ClassLabel int64
sentinel2 Tensor (64, 64, 13) float32