The cloud made for satellite data

As you probably already know, there are many cloud providers that are able to support you with your data processing workflows.

Having large amount of data to ingest, process, and extract information is usually the one of the main reasons to move in the cloud in the fist place, i.e. scalability is key.

That said, this is true for most use cases in the data science domain. The real problem starts to appear, when the amount of data become enormous. This is the case in Earth Observation.

Satellites orbiting the earth are taking "pictures" at different spectral bands, almost every day (in some cases even more frequent) of the entire planet!

This translates to TBs of data comming per day!

This amount is even challenging for cloud providers.


CloudSigma is building and maintaining a repository of Sentinel data backed by a powerful service level agreement ensuring availability and performance. 

Moreover, this enables Sentinel data to form the foundation for critical commercial and public sector services. 

Also, it includes services requirement fast access speeds and heavy processing of large amounts of Sentinel data. 

In short, the marriage of CloudSigma’s computing environment with a powerful data repository creates a unique environment for earth observation related workloads.

The data repository is stored on a modular equipment architecture using an object oriented storage environment. 

This repository maintains a copy of data delivered through the SciHub and provides a RESTful web service for querying and accessing the data and metadata. 

Currently, the full archive of Sentinel-1 SLC products for Europe and North America is available in CloudSigma object storage environment. This data is provided free of charge to all CloudSigma cloud users.


Start learning how to use CloudSigma's cloud environment. It's FREE! CloudSigma customers & GEO premium users can use the satellite repository for free!

  • Tutorial on CloudSigma online platform

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    Learn how to use CloudSigma platform and get ready for the next generation of Earth Observation and GIS cloud computing environments

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About the Writer

Dimitris Sykas is a Remote Sensing and Surveying Engineer with a Ph.D. in hyperspectral remote sensing from the National Technical University of Athens (2016). He has spent fifteen years turning satellite data into operational products: at the NTUA Remote Sensing Laboratory, at Planetek Hellas as Senior EO Engineer, at Neuropublic building machine-learning models for smart farming and CAP monitoring, as a postdoctoral researcher on deep learning for agricultural Earth observation at the National Observatory of Athens, and as CTO of the cloudeo group. In 2024 he co-founded GOVADI, an Athens-based company building sovereign, on-premises AI systems for the Greek public sector and large enterprises, where he leads the technical direction of its products: Greek speech-to-text, retrieval-augmented generation with local models and embedding stores, document OCR and PII anonymisation. He has taken part in more than 25 funded EU and ESA projects, has authored over 23 peer-reviewed publications in remote sensing, and holds an international patent in hyperspectral data compression. He founded GEO University to bring hands-on GIS and Earth observation training online.

Dimitris Sykas

Remote Sensing Engineer, Ph.D. · Co-founder and Director, GOVADI · Founder, GEO University