Radiant MLHub

BigEarthNet

satellite

BigEarthNet is a new large-scale Sentinel-2 benchmark archive, consisting of 590,326 Sentinel-2 image patches. To construct BigEarthNet, 125 Sentinel-2 tiles acquired between June 2017 and May 2018 over the 10 countries (Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg, Portugal, Serbia, Switzerland) of Europe were initially selected. All the tiles were atmospherically corrected by the Sentinel-2 Level 2A product generation and formatting tool (sen2cor). Then, they were divided into 590,326 non-overlapping image patches. Each image patch was annotated by the multiple land-cover classes (i.e., multi-labels) that were provided from the CORINE Land Cover database of the year 2018 (CLC 2018).

Dataset ID

bigearthnet_v1

DOI

10.14279/depositonce-10149browse DOI

Creator

BigEarthNet

Contact

contact@bigearth.net

Documentation

Citation

G. Sumbul, M. Charfuelan, B. Demir, V. Markl, "[BigEarthNet: A Large-Scale Benchmark Archive for Remote Sensing Image Understanding](http://bigearth.net/static/documents/BigEarthNet_IGARSS_2019.pdf)", IEEE International Geoscience and Remote Sensing Symposium, pp. 5901-5904, Yokohama, Japan, 2019.

Python Client example

from radiant_mlhub import Dataset

ds = Dataset.fetch('bigearthnet_v1')
for c in ds.collections:
    print(c.id)

Python Client quick-start guide

Source Imagery Collection

Description

BigEarthNet v1.0

License

CDLA-Permissive-1.0

Collection ID

bigearthnet_v1_source

Download

Labels Collection

Description

BigEarthNet v1.0

License

CDLA-Permissive-1.0

Collection ID

bigearthnet_v1_labels

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