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mikonvergenceย 
posted an update 3 days ago
Post
296
๐Œ๐š๐ฃ๐จ๐ซ ๐“๐Ž๐Œ โž• ๐†๐จ๐จ๐ ๐ฅ๐ž ๐ƒ๐ž๐ž๐ฉ๐Œ๐ข๐ง๐'๐ฌ ๐€๐ฅ๐ฉ๐ก๐š๐„๐š๐ซ๐ญ๐ก ๐„๐ฆ๐›๐ž๐๐๐ข๐ง๐ ๐ฌ ๐š๐ซ๐ž ๐ง๐จ๐ฐ ๐š๐ฏ๐š๐ข๐ฅ๐š๐›๐ฅ๐ž โ€ผ๏ธ

This is a tiny (about 6 TB of data, but only 62,489 grid cells of ~100 sqkm) prototype dataset that allows to instantly connect existing Major TOM data with AlphaEarth embeddings.

Major-TOM/Core-AlphaEarth-Embeddings

I curated it to support several relevant research projects, but I figured it could help more people in the community to experiment and explore new applications of AlphaEarth.

๐ƒ๐ข๐ซ๐ž๐œ๐ญ๐ข๐จ๐ง๐ฌ ๐Ÿ๐จ๐ซ ๐”๐ฌ๐ž
Each embedding sample comes from the original annual dataset produced by Google DeepMind. It means that, unlike samples from Sentinel-2 or Sentinel-1, it contains aggregated annual information from a particular year and is not linked to one particular observation. The existing Major TOM samples from physical sensors provide information potentially (and likely) contained in the AlphaEarth embedding sample, but they miss the temporal component represented within AEF embedding fields.

For more information, please check the dataset card on HuggingFace.

โš ๏ธ ๐–๐€๐‘๐๐ˆ๐๐†: ๐„๐ฆ๐›๐ž๐๐๐ข๐ง๐ ๐ฌ ๐ข๐ง ๐ญ๐ก๐ข๐ฌ ๐๐š๐ญ๐š๐ฌ๐ž๐ญ ๐๐จ ๐ง๐จ๐ญ ๐ซ๐ž๐ฉ๐ซ๐ž๐ฌ๐ž๐ง๐ญ ๐ข๐ง๐๐ข๐ฏ๐ข๐๐ฎ๐š๐ฅ ๐ฌ๐š๐ฆ๐ฉ๐ฅ๐ž๐ฌ, ๐›๐ฎ๐ญ ๐š ๐ฐ๐ก๐จ๐ฅ๐ž ๐ฒ๐ž๐š๐ซ ๐จ๐Ÿ ๐ฆ๐ฎ๐ฅ๐ญ๐ข-๐ฆ๐จ๐๐š๐ฅ ๐จ๐›๐ฌ๐ž๐ซ๐ฏ๐š๐ญ๐ข๐จ๐ง๐ฌ. ๐‡๐š๐ฏ๐ž ๐Ÿ๐ฎ๐ง!

๐Ÿ™ Built on top of fantastic work of
Christopher Brown, Michal Kazmierski, Valerie Pasquarella, Emily Schechter and others at Google DeepMind.