1. Achieving persistent “tasking, processing, exploitation, and dissemination” (TPED);

  2. Exploiting all forms of imagery, in the context of persistent surveillance, including the following challenges (3-6):

  3. Detecting weapons of mass destruction;

  4. Tracking moving targets;

  5. Thwarting denial and deception; and

  6. Targeting precisely;

  7. Compressing time lines (for preparation and dissemination of intelligence);

  8. Sharing with (coalition) forces, foreign partners, and communities at large;

  9. Supporting homeland security; and

  10. Promoting “horizontal integration.”

The immediacy of these challenges requires a research agenda that simultaneously addresses these short-term needs, while it pursues the evolution to a next-generation methodology for dealing with geospatial intelligence, GEOINT2. The vision for GEOINT2 involves bringing intelligence into a single operating environment that will allow analysts to draw from a variety of sources when making interpretations. Data for a specified location on Earth’s surface require both general knowledge of human and physical processes and specific knowledge of geography, culture, and tradition. Data on the physical environment may be directly measurable by sensors, or come from maps, but other data will come from the other intelligences (INTs), especially from open, public information about people and their lands. It is tempting to compare the necessary source integration to the multiple map-layer data model commonly encountered in NGA’s existing geographic information system (GIS) technology. Intelligence layers currently include weather information, strategic battle planning overlays, intelligence reports, and a layer attributing navigation safety. The underlying data foundation layers include georeferenced gravity data, vector features, bathymetry and elevation, intelligence baselines or reference data, and imagery.

A layered model, however, is inadequate. Multisource information does not easily resolve into layers; consequently, this information fits poorly with the existing GIS approach. For example, sensor webs provide data in real time that are spatially and temporally discontinuous and asynchronous, and often point-based. Human and signals intelligence may be in the form of textual reports with place name and other references. Data may also arrive as video, audio, web-based extensible markup language (XML), or any of a plethora of other media formats. The simple “data integration by spatial coregistration” standard that is the foundation of

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