---
license: mit
task_categories:
  - image-classification
  - feature-extraction
language:
  - en
tags:
  - satellite
  - sentinel-2
  - remote-sensing
  - geospatial
  - satclip
size_categories:
  - 100K<n<1M
pretty_name: S2-100K (SatCLIP)
---

# S2-100K

A complete re-host of the **S2-100K** dataset used to train [SatCLIP](https://arxiv.org/abs/2311.17179) (Klemmer et al., 2023).

100,000 globally sampled multi-spectral [Sentinel-2 L2A](https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-2) image patches (256×256 px, 12 bands, uint16), with longitude/latitude coordinates for each patch.

## Why this re-host?

The original Microsoft-hosted blob (`https://satclip.blob.core.windows.net/...`) is the canonical source. The only public mirror, [`davanstrien/satclip`](https://huggingface.co/datasets/davanstrien/satclip), is missing some patches ([discussion](https://huggingface.co/datasets/davanstrien/satclip/discussions/3)). This repo is a verified-complete copy: 100,000 / 100,000 patches present, sourced directly from the original Microsoft container.

## File layout

```
metadata.parquet        # fn, lon, lat, patch_idx, shard  (100,000 rows)
index.csv               # fn, lon, lat (verbatim from upstream)
data/shard-00000.tar    # patches 0..999
data/shard-00001.tar    # patches 1000..1999
...
data/shard-00099.tar    # patches 99000..99999
satclip.tar             # all 100,000 patches in one tar (78 GB) - included as a safety copy
```

Each shard is a plain (uncompressed) tar containing 1000 `patch_<N>.tif` files. Sharding the original 78 GB tar makes resumable downloads and partial loads practical; the single `satclip.tar` is included as well so users can grab everything at once if they prefer.

## Per-patch format

Each `patch_<N>.tif` is a GeoTIFF with:

- **Shape:** 256 × 256 pixels
- **Bands:** 12 (Sentinel-2 L2A: B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B11, B12 — B10 is excluded)
- **dtype:** uint16 (raw reflectance, scale by 10,000 to get [0,1])
- **CRS:** UTM zone of the source raster (EPSG:326XX / 327XX)
- **Resolution:** 10 m

> **Note:** Pillow / `datasets.Image` cannot decode 12-band uint16 GeoTIFFs. Use `rasterio` (or `tifffile`) to read these files.

## Loading

### Stream a few shards directly

```python
import io
import tarfile

import rasterio
from huggingface_hub import hf_hub_download

shard_path = hf_hub_download(
    repo_id="kklmmr/s2-100k",
    filename="data/shard-00000.tar",
    repo_type="dataset",
)

with tarfile.open(shard_path) as tar:
    member = tar.getmember("patch_42.tif")
    buf = tar.extractfile(member).read()

with rasterio.MemoryFile(buf) as mem, mem.open() as src:
    arr = src.read()           # shape: (12, 256, 256), dtype uint16
    bounds = src.bounds        # UTM bbox
    crs = src.crs              # e.g. EPSG:32610
```

### Pair patches with their coordinates

```python
import pandas as pd
from huggingface_hub import hf_hub_download

meta_path = hf_hub_download(
    repo_id="kklmmr/s2-100k",
    filename="metadata.parquet",
    repo_type="dataset",
)
meta = pd.read_parquet(meta_path)
# columns: fn, lon, lat, patch_idx, shard
```

### Download everything

```python
from huggingface_hub import snapshot_download

local_dir = snapshot_download(
    repo_id="kklmmr/s2-100k",
    repo_type="dataset",
    local_dir="./s2-100k",
)
```

## Provenance

- **Original dataset:** Sampled and released by the SatCLIP authors (Klemmer et al., 2023).
- **Original host:** `https://satclip.blob.core.windows.net/$web/satclip/` (Microsoft Azure Blob Storage).
- **Source code:** [microsoft/satclip](https://github.com/microsoft/satclip).
- **Paper:** [SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery](https://arxiv.org/abs/2311.17179).

This repository contains **only the dataset**. The pretrained SatCLIP model checkpoints are available from the original SatCLIP authors.

## License

MIT, matching the upstream SatCLIP project.

## Citation

```bibtex
@article{klemmer2023satclip,
  title={SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery},
  author={Klemmer, Konstantin and Rolf, Esther and Robinson, Caleb and Mackey, Lester and Ru{\ss}wurm, Marc},
  journal={arXiv preprint arXiv:2311.17179},
  year={2023}
}
```