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!

About the Writer

I'm a Remote Sensing and a Surveying Engineer. I received my degree from NTUA in 2010, where I also received my Ph.D. in hyperspectral remote sensing in 2016. From graduation in 2010, my career started as a Researcher Associate and Teaching Associate in the Laboratory of Remote Sensing of NTUA. From that time I also worked at several private companies as a Remote Sensing Expert and Geospatial Analyst. From the beginning of 2015 I was positioned as Senior Earth Observation Expert. During these years, I have participated in more than 20 funded European Commission and European Space Agency projects, have over 16 peer reviewed scientific publications in the field of Remote Sensing, and have an international patent in hyperspectral data compression.My main research and professional interests are in the optical remote sensing area, where I specialize in data (images, point measurements) processing and algorithm design and development. Some of the software tools that I operate to accomplish my research and business dreams are SNAP, ENVI, IDL, QGIS, ERDAS Imagine, ArcGIS, and Python. I have been working with these tools since 2008.

Dimitris Sykas

Remote Sensing Expert

GEO Premium

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