Title

AWS re:Invent 2022 - Accelerate Geospatial ML with Amazon SageMaker (AER204)

Summary

• Jeff Maynard introduces the session on accelerating geospatial machine learning (ML) with Amazon SageMaker.
• Kevin Wheel from Planet and Chris Eflin from AWS discuss the use of ML on satellite imagery for disaster impact detection and other applications.
• Planet's constellation of 200 satellites provides frequent, high-quality imagery, enabling rapid ML model training and deployment.
• AWS SageMaker offers tools to build, train, and deploy ML models quickly, leveraging Planet's imagery data streams.
• The session covers various use cases, including agriculture, human rights, environmental monitoring, and disaster response.
• AWS announces new SageMaker capabilities, including full geospatial support, pre-trained models, and integration with Foursquare Studio for visualization.
• Kevin Wheel shares Planet's journey, their approach to cost-effective satellite production, and their mission to improve sustainability and security through transparency.
• Chris Eflin highlights the importance of geospatial data in ML and the vast amount of data available for analysis.
• The talk concludes with a discussion on future developments, including new satellite constellations and the importance of making geospatial analysis more accessible.

Insights

• The collaboration between AWS and Planet represents a significant advancement in the field of geospatial ML, making it easier for companies to leverage satellite imagery for various applications.
• The ability to revisit and capture imagery of the Earth in minutes and hours, rather than days, is a game-changer for real-time event detection and response.
• The integration of AWS SageMaker with Planet's satellite data democratizes access to geospatial ML, allowing even small companies or individuals to become "space companies."
• The new SageMaker capabilities, including a geospatial data catalog, pre-trained models, and visualization tools, streamline the process of working with satellite data and ML.
• The session underscores the growing importance of geospatial data in addressing global challenges such as climate change, sustainability, and human rights.
• Planet's upcoming satellite constellations, including high-resolution and hyperspectral satellites, will further enhance the capabilities for Earth observation and ML applications.
• The focus on making geospatial analysis more accessible and user-friendly is likely to expand the user base and drive innovation in the use of satellite imagery for societal benefits.