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license: cc-by-4.0
task_categories:
- other
task_ids: []
tags:
- remote-sensing
- forecasting
- geospatial
pretty_name: calvingdb — Calving Front Benchmark
---
# calvingdb — Calving Front Benchmark
First benchmark dataset for **data-driven annual calving front forecasting**, covering 123 marine-terminating glaciers in Svalbard from 2013 to 2023.
Each benchmark sample asks: given five past calving front observations (spanning roughly four years), predict where the calving front will be **365 days in the future**.
---
## Dataset at a glance
| Property | Value |
|---|---|
| Glaciers | 123 (RGI 6.0, region 07 — Svalbard) |
| Total observations | 17,358 calving front scenes |
| Benchmark samples | 1,234 (866 train / 109 val / 259 test) |
| Temporal coverage | 2013–2023 |
| Spatial resolution | 30 m |
| CRS | EPSG:3995 (Arctic Polar Stereographic) |
| Prediction horizon | 365 days |
| Input sequence length | 5 snapshots |
| Version | 1.0.0 |
| License | CC BY 4.0 |
---
## Repository layout
```
calvdb/
├── zarr_zipped/ # per-glacier zip archives (for download)
│ └── RGI60-07.XXXXX.zarr.zip
├── splits/
│ ├── train.json # 866 benchmark samples
│ ├── val.json # 109 benchmark samples
│ ├── test.json # 259 benchmark samples
│ ├── normalisation_stats.json # channel statistics (train split only)
│ └── sampling_params.json # reproducibility config
├── croissant.json # MLCommons Croissant metadata
└── README.md
```
---
## Normalisation
`splits/normalisation_stats.json` contains per-channel mean and standard deviation computed **from the training split only**. Apply z-score normalisation before training.
## License
This dataset is released under the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license.
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