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---
license: other
license_name: cc-by-4.0
license_link: https://creativecommons.org/licenses/by/4.0/deed.en
size_categories:
- 100K<n<1M
---
Rehosted dataset from [official repo](https://huggingface.co/datasets/nascetti-a/BioMassters). However, we have created tar balls instead of split zip archives, since they are easier to extract.
We also changed the nested directory structure of the `train_features` directory and renamed the .csv files.
The tar balls can be extracted with theses commands:
```cli
tar -xvf train_agbm.tar.gz
tar -xvf test_agbm.tar.gz
cat train_features.tar.gz* | tar xvfz -
cat test_features.tar.gz* | tar xvfz -
```
You can also check the accompanying dataloader in [torchgeo](https://torchgeo.readthedocs.io/en/latest/api/datasets.html#biomassters).
If you use this dataset, please cite:
```
@inproceedings{nascetti2023biomassters,
title={BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series},
author={Nascetti, Andrea and Yadav, Ritu and Brodt, Kirill and Qu, Qixun and Fan, Hongwei and Shendryk, Yuri and Shah, Isha and Chung, Christine},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
year={2023}
}
``` |