Planet makes its geospatial data available through Amazon SageMaker
Planet Labs PBC a leading provider of daily data and insights about Earth, today announced it is making geospatial data available through Amazon SageMaker, a fully managed machine learning (ML) service from Amazon Web Services (AWS). Now, Planet data can be directly embedded into Amazon SageMaker, allowing data scientists and ML engineers to acquire and analyze global, daily satellite data. With this data, customers can train, test, and deploy ML models all within Amazon SageMaker.
Planet operates the largest constellation of earth observation satellites in the world, with the capacity to provide daily medium- and high-resolution imagery of Earth’s landmass every day. Planet is using AWS to better serve its customers who can now benefit from the simplicity and speed of Amazon SageMaker’s new geospatial ML capabilities to build, train, and deploy ML models using Planet’s geospatial data at up to 10x the speed. These enhanced capabilities create new opportunities for Planet customers to accelerate data access within geospatial tools and cloud platforms.
Due to the challenging work required to use geospatial data for ML, access to ML has historically been out of reach for many geospatial data customers. With Amazon SageMaker, customers can pull in their proprietary data sources, such as Planet satellite data, from Amazon Location Service and AWS Data Exchange. It’s a first of its kind partnership and the only on-demand, high cadence satellite imagery ML model training, inference, and visualization platform available in the market.