| --- |
| license: cdla-permissive-1.0 |
| task_categories: |
| - image-classification |
| tags: |
| - remote sensing |
| - classification |
| - multi-label |
| - sentinel-1 |
| - sentinel-2 |
| - multispectral |
| - multimodal |
| - SAR |
| - BigEarthNet |
| - reBEN |
| - LMDB |
| pretty_name: reBEN (pre-converted to LMDB) |
| configs: |
| - config_name: default |
| data_files: |
| - split: all_data |
| path: metadata.parquet |
| default: true |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| [TU Berlin](https://www.tu.berlin/) | [RSiM](https://rsim.berlin/) | [DIMA](https://www.dima.tu-berlin.de/menue/database_systems_and_information_management_group/) | [BigEarth](http://www.bigearth.eu/) | [BIFOLD](https://bifold.berlin/) |
| :---:|:---:|:---:|:---:|:---: |
| <a href="https://www.tu.berlin/"><img src="https://raw.githubusercontent.com/wiki/lhackel-tub/ConfigILM/static/imgs/tu-berlin-logo-long-red.svg" style="font-size: 1rem; height: 2em; width: auto" alt="TU Berlin Logo"/> | <a href="https://rsim.berlin/"><img src="https://raw.githubusercontent.com/wiki/lhackel-tub/ConfigILM/static/imgs/RSiM_Logo_1.png" style="font-size: 1rem; height: 2em; width: auto" alt="RSiM Logo"> | <a href="https://www.dima.tu-berlin.de/menue/database_systems_and_information_management_group/"><img src="https://raw.githubusercontent.com/wiki/lhackel-tub/ConfigILM/static/imgs/DIMA.png" style="font-size: 1rem; height: 2em; width: auto" alt="DIMA Logo"> | <a href="http://www.bigearth.eu/"><img src="https://raw.githubusercontent.com/wiki/lhackel-tub/ConfigILM/static/imgs/BigEarth.png" style="font-size: 1rem; height: 2em; width: auto" alt="BigEarth Logo"> | <a href="https://bifold.berlin/"><img src="https://raw.githubusercontent.com/wiki/lhackel-tub/ConfigILM/static/imgs/BIFOLD_Logo_farbig.png" style="font-size: 1rem; height: 2em; width: auto; margin-right: 1em" alt="BIFOLD Logo"> |
|
|
| --- |
|
|
| # reBEN (pre-converted to LMDB) |
|
|
| > **⚠️ Unofficial mirror.** This is an **unofficial, community-provided** pre-conversion of the BigEarthNet v2.0 (reBEN) dataset into LMDB format. It is provided as a convenience for researchers who wish to get started quickly without running the full conversion pipeline. In case of any discrepancy, **the original publication and the original files always take precedence**. Please refer to the authoritative sources listed below. |
|
|
| --- |
|
|
| ## Overview |
|
|
| This dataset card describes a pre-converted [LMDB](https://lmdb.readthedocs.io/en/release/) version of **BigEarthNet v2.0** (also known as **reBEN** — *Refined BigEarthNet*), a large-scale, multi-label remote sensing benchmark dataset. The dataset was converted to LMDB format using [rico-HDL](https://github.com/kai-tub/rico-hdl), which is the recommended conversion tool for reBEN. The LMDB file stores Sentinel-1 and Sentinel-2 patches as serialized [SafeTensors](https://github.com/huggingface/safetensors) entries, keyed by patch ID. |
|
|
| The accompanying `metadata.parquet` file provides all patch-level metadata (labels, split assignments, geographic information, etc.) for the included patches _without seasonal snow and cloud shadows_. |
| These are the patches that are recommended for most settings. It is the same file that can be downloaded from the official website. |
|
|
| --- |
|
|
| ## Authoritative Sources |
|
|
| Please always consult the following primary resources: |
|
|
| | Resource | Link | |
| |:---|:---| |
| | BigEarthNet project page | [bigearth.net](https://bigearth.net/) | |
| | BigEarthNet image–text dataset (txt.bigearth.net) | [txt.bigearth.net](https://txt.bigearth.net/) | |
| | Original reBEN files (Zenodo) | [zenodo.org/records/10891137](https://zenodo.org/records/10891137) | |
| | reBEN training scripts (official repository) | [git.tu-berlin.de/rsim/reben-training-scripts](https://git.tu-berlin.de/rsim/reben-training-scripts) | |
| | Pretrained model weights | [BIFOLD-BigEarthNetv2-0 on Hugging Face](https://huggingface.co/BIFOLD-BigEarthNetv2-0) | |
|
|
| --- |
|
|
| ## Dataset Details |
|
|
| ### LMDB Structure |
|
|
| Each entry in the LMDB file is a [SafeTensors](https://github.com/huggingface/safetensors)-serialized object, keyed by either the Sentinel-2 patch ID or the corresponding Sentinel-1 patch name (`s1_name`). This matches the format produced by [rico-HDL](https://github.com/kai-tub/rico-hdl). |
|
|
| - **Sentinel-2 entries** contain bands: `B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12` |
| - **Sentinel-1 entries** contain bands: `VV, VH` |
|
|
| ### Metadata |
|
|
| The `metadata.parquet` file is a direct copy of the full reBEN metadata parquet. It contains all original columns including patch IDs, labels, split assignments, and geographic metadata. |
|
|
| --- |
|
|
| ## Usage |
|
|
| The recommended way to use the dataset is with [configILM](https://github.com/lhackel-tub/ConfigILM), which directly supports pytorch dataloader and lightning datamodules with optimized multi-threaded loading. |
| Please follow the documentation for details. |
| Alternatively, to load individual patches from the LMDB file, you need `lmdb` and `safetensors`: |
|
|
| ```bash |
| pip install lmdb safetensors pandas pyarrow |
| ``` |
|
|
| ```python |
| import lmdb |
| import pandas as pd |
| from safetensors.numpy import load as safetensor_load |
| |
| lmdb_path = "path/to/BENv2.lmdb" |
| metadata_path = "path/to/metadata.parquet" |
| |
| metadata = pd.read_parquet(metadata_path) |
| lmdb_env = lmdb.open(lmdb_path, map_size=1024, max_dbs=False, readonly=True) |
| |
| # Load a Sentinel-2 patch |
| patch_id = metadata.patch_id.iloc[0] |
| with lmdb_env.begin(write=False) as txn: |
| data = txn.get(patch_id.encode()) |
| tensor = safetensor_load(data) |
| |
| # Access individual bands |
| r, g, b = tensor["B04"], tensor["B03"], tensor["B02"] |
| |
| # Load the corresponding Sentinel-1 patch |
| s1_name = metadata.s1_name.iloc[0] |
| with lmdb_env.begin(write=False) as txn: |
| data = txn.get(s1_name.encode()) |
| tensor = safetensor_load(data) |
| |
| vv, vh = tensor["VV"], tensor["VH"] |
| ``` |
|
|
| --- |
|
|
| ## Conversion Details |
|
|
| The LMDB was generated from the original reBEN dataset files (downloaded from [Zenodo](https://zenodo.org/records/10891137)) using [rico-HDL](https://github.com/kai-tub/rico-hdl), which is the officially recommended conversion tool for reBEN. |
|
|
| --- |
|
|
| ## License |
|
|
| The underlying data is licensed under the **[Community Data License Agreement — Permissive, Version 1.0 (CDLA-Permissive-1.0)](https://cdla.dev/permissive-1-0/)**, consistent with the license of the original BigEarthNet v2.0 dataset. This pre-converted version inherits the same license. |
|
|
| --- |
|
|
| ## Citation |
|
|
| If you use this dataset in your research, please cite the original reBEN publication and the ConfigILM library: |
|
|
| ```bibtex |
| @inproceedings{clasen2025refinedbigearthnet, |
| title={{reBEN}: Refined BigEarthNet Dataset for Remote Sensing Image Analysis}, |
| author={Clasen, Kai Norman and Hackel, Leonard and Burgert, Tom and Sumbul, Gencer and Demir, Beg{\"u}m and Markl, Volker}, |
| year={2025}, |
| booktitle={IEEE International Geoscience and Remote Sensing Symposium (IGARSS)}, |
| } |
| ``` |
|
|
| ```bibtex |
| @article{hackel2024configilm, |
| title={ConfigILM: A general purpose configurable library for combining image and language models for visual question answering}, |
| author={Hackel, Leonard and Clasen, Kai Norman and Demir, Beg{\"u}m}, |
| journal={SoftwareX}, |
| volume={26}, |
| pages={101731}, |
| year={2024}, |
| publisher={Elsevier} |
| } |
| ``` |
|
|
| The preprint for reBEN is also available on arXiv: |
|
|
| > K. Clasen et al., "reBEN: Refined BigEarthNet Dataset for Remote Sensing Image Analysis", arXiv:2407.03653, 2024. [https://arxiv.org/abs/2407.03653](https://arxiv.org/abs/2407.03653) |
