AI-powered cloud-free Sentinel-2 satellite imagery

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ClearSKY Vision is an AI platform that produces cloud-free, Sentinel-2-compatible imagery by fusing optical and SAR observations. Deep-learning models (Stratus-3, Stratus-2-Fast, Stratus-2, Nimbus and the on-request Cumulus) reconstruct cloud-covered, cloud-shadowed and missing pixels rather than masking them, delivering 10-band Level-2A imagery that is interchangeable with original Sentinel-2 products. Required inputs are Sentinel-1 C-SAR and Sentinel-2 MSI, with Landsat 8/9 (OLI/TIRS) required by Stratus-3 and an optional input group elsewhere, plus optional CBERS-4/4A and Amazonia-1 on Cumulus. Outputs are delivered as Cloud Optimized GeoTIFFs and XYZ tiles through a REST API and web dashboard, with a per-pixel Usability Score included, supporting GIS, analytics and monitoring workflows in agriculture, forestry, urban and environmental programmes. Only current and past observations are used, so historical series never leak future data. ClearSKY Vision is a 2023 CASSINI Challenges product winner and delivered more than 250 million km2 of imagery last year.
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No cost; basic functionality available at zero charge.
One-time
Single upfront payment for lifetime access.
Pay-per-use
Charges based on actual usage or consumption.
Subscription
Recurring fees for ongoing access and support.
Quote-based
Pricing is not published; the provider quotes per customer or project (contact sales, request a quote).
Vesoljska zmogljivost
Obdelava
Data Fusion & Analytics
Combines data sources and applies analytics to uncover patterns.
Dostavljeno kot
System Integration
Geografski obseg

ClearSKY Vision
ClearSKY Vision provides cloud-free, analysis-ready satellite imagery using AI-powered cloud removal and multi-sensor (optical & SAR) data fusion. They deliver near real-time, preprocessed Sentinel-2 products via API and dashboard for monitoring applications in agriculture, forestry, and environmental management.
2020
Ustanovljeno
11-50
Velikost ekipe
Danska
Država
Embeds data and insights into existing systems and workflows.