AI-powered cloud detection for enhanced Earth observation

Effective cloud and cloud shadow detection is a critical pre-processing step for Earth Observation (EO) applications. With clouds obscuring on average 67% of the Earth at any given time, their presence can significantly affect the accuracy of satellite image analysis.

Our solution employs Deep Convolutional Neural Networks (DCNNs) to segment clouds and shadows in Copernicus Sentinel 2 satellite imagery. This approach has been rigorously tested and shows superior performance compared to traditional methods and other deep learning models.

The key benefits of our AI solution include:

• Improved data quality: by accurately identifying and segmenting clouds and shadows, our technology ensures clearer images for EO analysis.
• Increased efficiency: our solution streamlines the pre-processing of satellite data by effectively minimising the impact of clouds and shadows.
• Reliable performance: our solution offers an exhaustive quantitative comparison, showcasing its outstanding effectiveness and other advanced deep learning approaches.

This AI solution is designed to support a variety of EO applications by providing cleaner, more accurate satellite imagery data, enhancing the value of satellite-derived insights.