• Merge traditional and non-traditional sensing methodologies (kinematic, participatory networks, social media, surveillance networks)

Remote Sensing

  • Exploit hyperspectral imagery

    • Integrate with other data, GIS, etc.

    • Add time (as described in photogrammetry)

    • Exploit other information (culture, context, etc.)

  • Adaptive sensing (real-time) based on information value of sensor

  • Link the above with text information to aid classification and event and scenario recognition; link with visual analytics

  • Exploit atmospheric impacts as signals

  • Uses networks of “small satellites” to gain distributed data

  • Adapt products, tools to end user (first responder, soldier, analyst, etc.)

  • Emphasize multi-sensor fusion and information extraction

    • Decrease uncertainty

    • Exploit redundant capabilities

  • Greater utilization of state-of the art algorithms

    • Estimation theory – statistics and electrical engineering

    • Robust nonlinear optimization – numerical analysis

    • Statistical sensor measurement models - nonlinear filtering

    • Advanced software – Object oriented C++

  • Coordination with other government agencies

    • DARPA, Air Force, Army, Navy

  • Exploitation of knowledge sources beyond image data mining; make relevant knowledge sources available; knowledge-based classification

  • Enhance change analysis – beyond the process of measurement and classification to dynamics, behavior, and prediction (issue of sensor control and tasking)

  • Need more than just the inanimate landscape, but also the dynamic, social environment (e.g., the flux of a living city) = GEOINT

  • Metadata and tagging – hey for fusion; relate to other non- GEOINT sources (semantic and tagging interoperability challenge)

  • Augmenting the image analyst –more tools, knowledge, visual analytics, automation, mining given a specific remote sensor

  • Infrastructure implications – data storage, distribution, and throughput to the analyst

    • Remote sensing: We have lots of data (increased availability of commercially collected data). Can we analyze this data?

    • Data collection agency, delivering tools for data analysis (multi-resolution, multi-sensor, multi-platform, multi-temporal, current and future sensor technologies – including new sensors that are not fully understood)

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