VIS-SAR-Sat-Dataset / README.md
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metadata
license: cc-by-4.0
task_categories:
  - image-feature-extraction
tags:
  - remote-sensing
  - sar
  - optical
  - multimodal
  - contrastive-learning
  - sentinel-1
  - landsat
size_categories:
  - 1M<n<10M

VIS–SAR Satellite Dataset

Spatially- and temporally-aligned visible (optical) ↔ SAR satellite image patches for cross-modal representation learning (CLIP-style SAR↔visible alignment).

Contents

  • ~3.68M paired patches (this is a snapshot of an in-progress 10M build).
  • shards/ — WebDataset .tar shards. Each sample key K has three members:
    • K.vis.npy — visible/optical, uint8 [3, 224, 224] (3 bands)
    • K.sar.npy — SAR, uint8 [2, 224, 224] (VV, VH)
    • K.json — per-sample metadata (AOI, biome, region, lat/lon, acquisition times, CRS, transform, SAR scaling, cloud cover, Δt hours)
  • index.parquet — random-access offset index, one row per sample: key, shard, vis_offset, vis_size, sar_offset, sar_size, ground_tile_id, aoi_id, biome, region. A worker can seek+read a single sample without scanning the shard.
  • manifests/ — per-shard metadata sidecars. manifest.parquet — consolidated metadata.

Decoding (uint8 → physical)

Values are quantized from normalized ranges to uint8 (4× smaller than float32, retrieval-neutral):

  • Visible: physical reflectance clipped to [0, 30000][0,1]uint8. Decode: x/255.0 gives normalized [0,1].
  • SAR: linear amplitude → dB, clipped to [-40, 5][0,1]uint8. Decode: x/255.0 gives normalized [0,1]; dB = x/255*45 - 40.

Training

Directly consumable by the multi-modal CLIP training pipeline: point it at the shard directory and the offset index —

--shards_dir  <download>/shards
--index_path  <download>/index.parquet

The loader (tar_dataset) auto-detects the uint8 dtype and rescales to [0,1] on read (no re-normalization needed). Use ground_tile_id for leak-free train/val splits (group by tile so the same ground location never spans splits).

Notes

  • Patches are 224×224 at a common spatial grid (VIS and SAR resampled to the same grid).
  • SAR penetrates cloud/night, so VIS↔SAR pairs are matched within a Δt tolerance (see dt_hours in metadata).