--- task_categories: - image-classification --- # BigEarthNet Dataset The **BigEarthNet** dataset is a large-scale benchmark Archive for remoting sensing. The dataset contains both Sentinel-2 and Sentinel-1 imagery. We have pre-processed the dataset by upsampling all sentinel-2 channels to 120x120 pixels and concatenated them together. Please see [Torchgeo/bigearthnet](https://github.com/microsoft/torchgeo/blob/main/torchgeo/datasets/bigearthnet.py#L385) for more information about pre-processing. Please see our [GFM-Bench](https://github.com/uiuctml/GFM-Bench) for more information about how to use the dataset! 🙂 ## Metadata The following metadata provides details about the Sentinel-2 and Sentinel-1 imagery used in the dataset: ```python S2_MEAN = [752.40087073, 884.29673756, 1144.16202635, 1297.47289228, 1624.90992062, 2194.6423161, 2422.21248945, 2517.76053101, 2581.64687018, 2645.51888987, 2368.51236873, 1805.06846033] S2_STD = [1108.02887453, 1155.15170768, 1183.6292542, 1368.11351514, 1370.265037, 1355.55390699, 1416.51487101, 1474.78900051, 1439.3086061, 1582.28010962, 1455.52084939, 1343.48379601] S1_MEAN = [-12.54847273, -20.19237134] S1_STD = [5.25697717, 5.91150917] metadata = { "s2c": { "bands":["B1", "B2", "B3", "B4", "B5", "B6", "B7", "B8", "B8A", "B9", "B11", "B12"], "channel_wv": [442.7, 492.4, 559.8, 664.6, 704.1, 740.5, 782.8, 832.8, 864.7, 945.1, 1613.7, 2202.4], "mean": S2_MEAN, "std": S2_STD }, "s1": { "bands": ["VV", "VH"], "channel_wv": [5500, 5700], "mean": S1_MEAN, "std": S1_STD } } SIZE = HEIGHT = WIDTH = 120 NUM_CLASSES = 19 spatial_resolution = 10 ``` ## Split The **BigEarthNet** dataset consists splits of: - **train**: 269,695 samples. - **val**: 123,723 samples. - **test**: 125,866 samples. ## Features: The **BigEarthNet** dataset consists of following features: - **optical**: the Sentinel-2 image. - **radar**: the Sentinel-1 image. - **label**: the classification label. - **optical_channel_wv**: the wavelength of each optical channel. - **radar_channel_wv**: the wavelength of each radar channel. - **spatial_resolution**: the spatial resolution of images. ## Citation If you use the BigEarthNet dataset in your work, please cite the original paper: ``` @inproceedings{sumbul2019bigearthnet, title={Bigearthnet: A large-scale benchmark archive for remote sensing image understanding}, author={Sumbul, Gencer and Charfuelan, Marcela and Demir, Beg{\"u}m and Markl, Volker}, booktitle={IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium}, pages={5901--5904}, year={2019}, organization={IEEE} } ```