Datasets:
Tasks:
Image Classification
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
remote-sensing
earth-observation
geospatial
satellite-imagery
land-cover-classification
multispectral
License:
File size: 3,462 Bytes
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---
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 -->
<!-- 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}
}
```
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