README.md

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title: Maya4
emoji: 📊
colorFrom: indigo
colorTo: indigo
sdk: static
pinned: true
license: apache-2.0
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/68a43a86eea45496edb28ba6/hJyITwdmrofMtEtX8qFmW.png

🏢 Maya4

🌌 Maya4

Maya4 is a project dedicated to curating and providing multi-level intermediate SAR representations from Sentinel-1 acquisitions, spanning the entire chain from Level 0 to Level 1.

The name Maya4 draws inspiration from the Māyā veil in philosophy, where reality is hidden behind successive layers—just as radar echoes undergo transformations before forming a final SAR image.

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🚀 Mission

• 📡 Curate and structure Sentinel-1 Stripmap SAR data
• 🧩 Provide intermediate signal representations for research & ML pre-training
• ☁️ Enable scalable, cloud-native access in Zarr format

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📦 Pre-Training Dataset Spaces

Maya4 provides Pre-Training (PT) dataset exposing intermediate SAR signal states in a modern (Zarr Format):

📂 Dataset Split	📊 Contents	🛰️ Acquisition Mode	💾 Size
pt1	LINK	Stripmap	17 TB
pt2	LINK	Stripmap	17 TB
pt3	LINK	Stripmap	17 TB
pt4	LINK	Stripmap	17 TB
Total	—	—	68 TB

📊 Processing Levels

A major characteristic of this dataset lies in its sharding multi-level organisation:

🌐 Level	🔤 Abbrev.	📝 Description	🎯 Purpose / Value
📡 Raw	raw	Unprocessed radar echoes as recorded by Sentinel-1	Baseline data; allows full custom SAR processing
🎚️ Range Compressed	rc	Echoes compressed in the range dimension via matched filtering	Improves SNR; isolates scatterers along range
🎯 Range Cell Migration Corrected	rcmc	Motion-compensated echoes with corrected range migration	Preserves geometric fidelity; enables proper azimuth focusing
🖼️ Azimuth Compressed	ac	Fully focused SAR image in slant-range geometry	Standard Level-1 product; interpretable imagery

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🌍 PT Use Cases

The following use cases can be addressed with Maya4:

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🙏 Acknowledgements

• 🛰️ Data provided by the Copernicus Sentinel-1 mission (ESA)
• 🏢 Curated and maintained by the Maya4 organization