---
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.