The Evolving Role of Synthetic Data in GEOINT Tradecraft

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Synopsis

The objective of this USGIF Working Group White Paper is to educate and inform the GEOINT community on the evolving role of synthetic data. Advances in artificial intelligence (AI) methods, such as Deep Learning (DL) and Generative AI, pose new opportunities and challenges in geospatial intelligence tradecraft. At the top of the challenges list is the need for massive amounts of labeled data to feed into AI systems. Synthetic data generation has emerged as a keystone technology to address this need. In this White Paper we seek to address the following questions:

  • What is synthetic data for GEOINT?
  • How is synthetic data being used across the GEOINT community?
  • Why is synthetic data important for AI applications?
  • What future trends in synthetic data will influence GEOINT tradecraft?

Acknowledgments

Chris Andrews, Rendered.ai
Stephen Fleming, Ph.D., Institute for Environmental
and Spatial Analysis, University of North Georgia
Patrick Kenney, Whitespace
Shehzan Mohammed, Cesium
Don Widener, BAE Systems
Sacha Lepretre, Presagis

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