ThetaSpace develops and maintains the CloudlessEO software, an artificial intelligence program based on deep neural networks that fuses Synthetic Aperture Radar (SAR - Sentinel-1) satellite data and cloud-corrupted Optical satellite imagery (Sentinel-2) to remove clouds and their shadows and fill those gaps with geometrical and spectral information as if there were no clouds!

How it works

CloudlessEO accurately detects and masks clouds on every Sentinel-2 imagery, then exploits the temporally closest sentinel-1 in two processes:

  • Generating high frequency object geometries

  • As a mapping space for spectral information contained in the Sentinel-2 acquisition.

  • CloudlessEO uses multiple inputs to accurately generate cloud-free optical images that match the ground truth, such as geolocation, prior image acquisition, etc.

    Thetaspace is currently developing a beta version of CloudlessEO that aims to provide on demand cloud-free, high resolution optical satellite imagery for the RGBNIR (Red, Green, Blue and Near Infrared) spectral bands with a global coverage of Earth's land surface with a revisit time of up to 6 days.


    We believe that satellite imagery is the world's largest yet most underutilized dataset in history. One of the reasons of this being clouds, shadows, haze... Clouds cover around 70% of earth's land surface 1. For this reason optical satellite imagery are not reliable for many thematic use cases e.g. land monitoring especially in cloud-prone regions, disaster management, ...

    Although SAR, thanks to its longer wavelength, can penetrate through clouds and can deliver data day or night, it has many limitations that prevent it from being an alternative to optical imagery. SAR is a complex data that is much more difficult to interpret than an optical image. SAR requires tedious preprocessing , which requires the use of special software and its knowledge. Unlike SAR, optical imagery is user friendly and can be immediately interpreted by virtually anyone.

    We believe that our solution CloudlessEO, efficiently overcome the cloud obstruction problem in optical imagery and:

  • provides guaranteed recent optical imagery that matches the ground truth at the time of acquisition

  • unlocks new thematic applications that were not usually possible especially in cloud-prone regions

  • saves time, effort and money wasted in looking for cloud-free imagery, whose existence isn't even guaranteed.