Satlas is a project by AllenAI that combines the power of modern AI with the scale of public domain satellite imagery to provide monthly monitoring of the planet. AI models in Satlas process freely available satellite images captured by the European Space Agency’s Sentinel-2 satellites. These images cover the majority of the planet every week, but are low in resolution, making them difficult to interpret even for humans.
The AI models in Satlas are pre-trained on a new large-scale remote sensing dataset called SatlasPretrain. This vast dataset contains over 30 TB of imagery with 302 million labels spanning 137 diverse categories, from tree cover and crop fields to wind farms and oil wells. The AI models use state of the art machine learning architectures and training methods. They input a sequence of the three most recent satellite images captured at each location. Each image is passed through a Swin Transformer backbone to extract features. These features are then combined via max temporal pooling, and passed to task-specific neural network heads to make the final predictions³.