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The United States faces numerous, varied, and evolving threats to national security, including terrorism, scarcity and disruption of food and water supplies, extreme weather events, and regional conflicts around the world. Effectively managing these threats requires intelligence that not only assesses what is happening now, but that also anticipates potential future threats. The National Geospatial-Intelligence Agency (NGA) is responsible for providing geospatial intelligence on other countries—assessing where exactly something is, what it is, and why it is important—in support of national security, disaster response, and humanitarian assistance. NGA’s approach today relies heavily on imagery analysis and mapping, which provide an assessment of current and past conditions. However, augmenting that approach with a strong modeling capability would enable NGA to also anticipate and explore future outcomes.

A model is a simplified representation of a real-world system that is used to extract explainable insights about the system, predict future outcomes, or explore what might happen under plausible what-if scenarios. Such models use data and/or theory to specify inputs (e.g., initial conditions, boundary conditions, and model parameters) to produce an output.

From Maps to Models: Augmenting the Nation's Geospatial Intelligence Capabilities describes the types of models and analytical methods used to understand real-world systems, discusses what would be required to make these models and methods useful for geospatial intelligence, and identifies supporting research and development for NGA. This report provides examples of models that have been used to help answer the sorts of questions NGA might ask, describes how to go about a model-based investigation, and discusses models and methods that are relevant to NGA’s mission.

Suggested Citation

National Academies of Sciences, Engineering, and Medicine. 2016. From Maps to Models: Augmenting the Nation's Geospatial Intelligence Capabilities. Washington, DC: The National Academies Press. https://doi.org/10.17226/23650.

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Publication Info

134 pages |  8.5 x 11 |  Ebook
ISBN: 978-0-309-44994-6
DOI: https://doi.org/10.17226/23650

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