ESA-philab/S1_Dataset
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AI & ML interests
ESA’s Φ-lab mission is to accelerate the future of Earth Observation (EO) by means of transformational innovations, i.e. innovations that completely transform or create entire industries via new technologies, with the aim to strengthen the world-leading competitiveness of the European EO industrial and research sectors.
Recent Activity
SoleneDEBUYSERE
published 2
datasets 20 days ago
sirbastiano94
updated a
bucket about 2 months ago
sirbastiano94
published a
bucket about 2 months ago
sirbastiano94
updated a
collection 3 months ago
mikonvergence
posted an update 3 months ago
Post
240
🥕 Introducing BetaEarth - your own Earth embedding emulator [𝐏𝐫𝐞-𝐑𝐞𝐥𝐞𝐚𝐬𝐞]
The past year has brought many notable embedding products, like AlphaEarth, TESSERA or OlmoEarth. We are entering a phase where embeddings begin to act as a substitute for real observation data.
BetaEarth is an attempt to explore how much one can learn from a model based on its embeddings alone, and whether those embeddings can serve as a useful training target for other models. Huge credit to the AlphaEarth team for releasing the embedding archive openly — it's what made this kind of community-built extension possible.
[𝐁𝐞𝐭𝐚𝐄𝐚𝐫𝐭𝐡 𝐢𝐬 𝐧𝐨𝐭 𝐚 𝐟𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐦𝐨𝐝𝐞𝐥 𝐛𝐮𝐭 𝐢𝐭 𝐭𝐫𝐢𝐞𝐬 𝐢𝐭𝐬 𝐛𝐞𝐬𝐭]
BetaEarth is a flexible (and relatively lightweight) emulator of the AlphaEarth annual product. It doesn't reproduce AlphaEarth's exact outputs, nor the product, but it reaches ~0.87 cosine similarity on held-out data and retains 97% of downstream land-cover classification accuracy. It only took 1-2 days to train.
It can encode any combination (including multi-temporal) of:
- Sentinel-2 L1C
- Sentinel-2 L2A
- Sentinel-1 RTC
- COP-DEM 30 product
The model weights are open, just like its training data (built exclusively using Major TOM). The GitHub repository provides a script for automated generation of embeddings across any footprint.
You can also try the workflow over small bounding boxes on the free Hugging Face web app!
⚙️ GitHub: https://github.com/asterisk-labs/beta-earth
🖥️ Web App: asterisk-labs/betaearth
🏭 Models: https://huggingface.co/collections/asterisk-labs/beta-earth
🟨 Colab: https://colab.research.google.com/github/asterisk-labs/beta-earth/blob/main/examples/generate_demo.ipynb
🗞️ Pre-print: https://github.com/asterisk-labs/beta-earth/blob/main/docs/beta_earth_preprint.pdf
The past year has brought many notable embedding products, like AlphaEarth, TESSERA or OlmoEarth. We are entering a phase where embeddings begin to act as a substitute for real observation data.
BetaEarth is an attempt to explore how much one can learn from a model based on its embeddings alone, and whether those embeddings can serve as a useful training target for other models. Huge credit to the AlphaEarth team for releasing the embedding archive openly — it's what made this kind of community-built extension possible.
[𝐁𝐞𝐭𝐚𝐄𝐚𝐫𝐭𝐡 𝐢𝐬 𝐧𝐨𝐭 𝐚 𝐟𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐦𝐨𝐝𝐞𝐥 𝐛𝐮𝐭 𝐢𝐭 𝐭𝐫𝐢𝐞𝐬 𝐢𝐭𝐬 𝐛𝐞𝐬𝐭]
BetaEarth is a flexible (and relatively lightweight) emulator of the AlphaEarth annual product. It doesn't reproduce AlphaEarth's exact outputs, nor the product, but it reaches ~0.87 cosine similarity on held-out data and retains 97% of downstream land-cover classification accuracy. It only took 1-2 days to train.
It can encode any combination (including multi-temporal) of:
- Sentinel-2 L1C
- Sentinel-2 L2A
- Sentinel-1 RTC
- COP-DEM 30 product
The model weights are open, just like its training data (built exclusively using Major TOM). The GitHub repository provides a script for automated generation of embeddings across any footprint.
You can also try the workflow over small bounding boxes on the free Hugging Face web app!
⚙️ GitHub: https://github.com/asterisk-labs/beta-earth
🖥️ Web App: asterisk-labs/betaearth
🏭 Models: https://huggingface.co/collections/asterisk-labs/beta-earth
🟨 Colab: https://colab.research.google.com/github/asterisk-labs/beta-earth/blob/main/examples/generate_demo.ipynb
🗞️ Pre-print: https://github.com/asterisk-labs/beta-earth/blob/main/docs/beta_earth_preprint.pdf
sirbastiano94
updated 2
buckets 3 months ago
sirbastiano94
updated a
collection 3 months ago
sirbastiano94
published a
bucket 3 months ago
mikonvergence
authored 2
papers 4 months ago
sirbastiano94
updated a
bucket 4 months ago
sirbastiano94
published a
bucket 4 months ago
sirbastiano94
updated a
Space 4 months ago
blumenstiel
authored 2
papers 4 months ago