---
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
dataset_info:
  features:
  - name: image
    dtype:
      array3_d:
        dtype: uint16
        shape:
        - 64
        - 64
        - 13
  - name: label
    dtype:
      class_label:
        names:
          '0': Annual Crop
          '1': Forest
          '2': Herbaceous Vegetation
          '3': Highway
          '4': Industrial Buildings
          '5': Pasture
          '6': Permanent Crop
          '7': Residential Buildings
          '8': River
          '9': SeaLake
  - name: filename
    dtype: string
  splits:
  - name: train
    num_bytes: 1995359806
    num_examples: 16200
  - name: test
    num_bytes: 665119564
    num_examples: 5400
  - name: validation
    num_bytes: 665120060
    num_examples: 5400
  download_size: 2379014584
  dataset_size: 3325599430
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
  - split: validation
    path: data/validation-*
---

# EuroSAT MSI

<!-- Dataset thumbnail -->
![EuroSAT MSI](./thumbnail.jpg)

<!-- 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](https://sentinel.esa.int/web/sentinel/missions/sentinel-2). 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](https://sentinels.copernicus.eu/web/sentinel/user-guides/sentinel-2-msi/resolutions/spatial). 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. -->
```python
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:


```bibtex
@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}
}
```