metadata

language: en
license: unknown
size_categories:
  - 10K<n<100K
task_categories:
  - image-classification
paperswithcode_id: eurosat
pretty_name: EuroSAT MSI
tags:
  - remote-sensing
  - earth-observation
  - geospatial
  - satellite-imagery
  - land-cover-classification
  - multispectral
  - sentinel-2

EuroSAT MSI

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

Paper: https://arxiv.org/abs/1709.00029
Homepage: https://github.com/phelber/EuroSAT

Description

The EuroSAT dataset is a comprehensive land cover classification dataset that focuses on images taken by the ESA Sentinel-2 satellite. It contains a total of 27,000 images, each with a resolution of 64x64 pixels. These images cover 10 distinct land cover classes and are collected from over 34 European countries.

The dataset is available in two versions: RGB only and all 13 (this repo) Multispectral (MS) Sentinel-2 bands. EuroSAT is considered a relatively easy dataset, with approximately 98.6% accuracy achievable using a ResNet-50 architecture.

Total Number of Images: 27000
Bands: 13 (MSI)
Image Resolution: 64x64m
Land Cover Classes: 10
Classes: Annual Crop, Forest, Herbaceous Vegetation, Highway, Industrial Buildings, Pasture, Permanent Crop, Residential Buildings, River, SeaLake

Usage

To use this dataset, simply use datasets.load_dataset("blanchon/EuroSAT_MSI").

from datasets import load_dataset
EuroSAT_MSI = load_dataset("blanchon/EuroSAT_MSI")

Citation

If you use the EuroSAT dataset in your research, please consider citing the following publication:

@article{helber2017eurosat,
   title={EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification},
   author={Helber, et al.},
   journal={ArXiv preprint arXiv:1709.00029},
   year={2017}
}