Sentinel-2 Sample Data

This repository contains 5 Sentinel-2 Level-2A (12 bands) images that are part of the BigEarthNet Dataset (Sumbul et al. 2019, https://bigearth.net/). The images in this dataset focus on coastal areas.

The image data for each scene and band were upscaled to a common ground sample distance of 10m per pixel using linear interpolation. Furthermore, all bands of each scence were combined into a single NumPy array and stored into separate .npy binary files. Data processing was performed by Linus Scheibenreif, University of St. Gallen.

The data can be easily read in with Python using the following code snippet:

import os
import numpy as np

data = []
for filename in os.listdir('data/'):
    if filename.endswith('.npy'):
        data.append(np.load(open(os.path.join('data', filename), 'rb'),
                        allow_pickle=True))
data = np.array(data)

This repository also contains the file coastal_labels.json, which contains polygons for labels grassland, forest, water and sand, using the YOLO format.

This dataset is provided mainly for teaching purposes under the Creative Commons Attribution 4.0 International licence. BigEarthNet data are provided under the Community Data License Agreement (Permissive, Version 1.0).

Michael Mommert, Stuttgart University of Applied Sciences, 2025-03-07