blanchon/EuroSAT_MSI

EuroSAT MSI

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<!-- Provide a quick summary of the dataset. --> 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

<!-- Provide a longer summary of what this dataset is. -->

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"). <!-- Provide any additional information on how to use this dataset. -->

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

Citation

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> 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}
}