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--- |
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license: cc-by-4.0 |
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language: |
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- en |
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tags: |
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- climate |
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pretty_name: BioMassters |
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size_categories: |
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- 100K<n<1M |
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--- |
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# BioMassters: A Benchmark Dataset for Forest Biomass Estimation using Multi-modal Satellite Time-series [https://nascetti-a.github.io/BioMasster/] |
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The objective of this repository is to provide a deep learning ready dataset to predict yearly Above Ground Biomass (AGB) for Finnish forests using multi-temporal satellite imagery from |
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the European Space Agency and European Commission's joint Sentinel-1 and Sentinel-2 satellite missions, designed to collect a rich array of Earth observation data |
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### Reference data: |
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* Reference AGB measurements were collected using LiDAR (Light Detection and Ranging) calibrated with in-situ measurements. |
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* Total 13000 patches, each patch covering 2,560 by 2,560 meter area. |
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### Feature data: |
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* Sentinel-1 SAR and Sentinel-2 MSI data |
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* 12 months of data (1 image per month) |
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* Total 310,000 patches |
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### Data Specifications: |
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### Data Size: |
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``` |
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dataset | # files | size |
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-------------------------------------- |
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train_features | 189078 | 215.9GB |
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test_features | 63348 | 73.0GB |
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train_agbm | 8689 | 2.1GB |
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``` |
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## Citation : under review |
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