--- license: cc-by-4.0 tags: - satellite - sentinel-2 - remote-sensing - ssl --- # S2-100K Preprocessed Derived from [torchgeo/s2-100k](https://huggingface.co/datasets/torchgeo/s2-100k). ## What changed The original dataset stores patches as uint16 GeoTIFF files inside plain tar archives with no compression. This version converts every patch to a blosc2/zstd-compressed float32 array for faster I/O in training pipelines. **No season selection is performed.** Each patch in the source dataset is a single Sentinel-2 L2A acquisition (no temporal dimension), so every patch is included as-is. ## Source statistics | Property | Value | |----------|-------| | Total patches | 100,000 | | Shards | 100 (1,000 patches each) | | Spatial size | 256 × 256 px (resampled to 10 m/px) | | Spectral bands | 12 (B01–B09, B11, B12; no B10) | | DN scale | L2A reflectance × 10000 (uint16 in source) | **Band order** (index 0–11): B01, B02, B03, B04, B05, B06, B07, B08, B08A, B09, B11, B12 ## Format WebDataset `.tar` shards under `train/`. Each sample contains two files: | File | Description | |------|-------------| | `{patch_id}.bands.b2` | blosc2/zstd-compressed `[12, 256, 256]` **float32** array | | `{patch_id}.meta.json` | {"lon":…,"lat":…,"fn":…,"shard":…,"patch_idx":…} | `patch_id` format: `s2100k_{shard:05d}_{patch_idx:05d}` `patch_idx` is the **shard-local** 0-based index (0–999), matching the `patch_idx` column in the source `metadata.parquet`. e.g. `s2100k_00003_00042` = shard 3, the 43rd patch in that shard (0-indexed). ## Loading a sample ```python import blosc2, numpy as np, json, tarfile N_CHANNELS, H, W = 12, 256, 256 with tarfile.open('s2100k_preprocessed_shard_00000.tar') as tf: members = {m.name: m for m in tf.getmembers()} patch_id = 's2100k_00000_00000' raw = blosc2.decompress(tf.extractfile(members[f'{patch_id}.bands.b2']).read()) arr = np.frombuffer(raw, dtype=np.float32).reshape(N_CHANNELS, H, W) meta = json.loads(tf.extractfile(members[f'{patch_id}.meta.json']).read()) print(arr.shape, arr.dtype, meta) ```