By Laura Lundin, National Geospatial-Intelligence Agency (www.nga.mil), Office of Geospatial Intelligence Management,Â Springfield, Va.
For many organizations, shrinking budgets and constrained resources mean slashing existing programs and limiting futureÂ investments. But how do decision makers determine where to cut and where to invest while limiting risks often associated withÂ new technologies and aging legacy systems? For the geospatial intelligence (GEOINT) community, the answer lies in computerÂ models, data sets, visualization tools, system configurations and an increased awareness of system capabilities.
Exploring the GEOINT Frontier
Two current efforts under way in the National Geospatial- Intelligence Agency's Office of Geospatial Â ntelligence
Management (OGM) Frontiers Division apply these tools and techniques to help the GEOINT community look to the future whileÂ defining, studying and analyzing current capabilities and technology applications.
The division's modeling and simulation efforts and the Community Information Needs Forecast (CINF) database workÂ together to ensure the intelligence community and Defense Department leaders and National System for Geospatial IntelligenceÂ (NSG) partners have up-to-date, data-driven information at their disposal to objectively inform their decision making.
The Frontiers Division builds uponÂ today's GEOINT capabilities by identifying potential system-after-next systems, which can take years to design, build and deploy.Â Given these lengthy development cycles, the CINF database is crucial to understanding current system capabilities and buildingÂ fact-based, objective recommendations for future ones.
The Community InformationÂ Needs Forecast
Primarily supporting the NSG modeling and simulation community, the CINF outlines a target set populated with informationÂ on the community's GEOINT requirements and systems performance measures from partners around the world.
Starting as a simple dBase II file in 1990, the CINF is now a large, complex, relational database that contains projectedÂ future imagery and geospatial information needs for the NSG and documents the community's end-to-end intelligenceÂ foundation, peacetime and crisis requirements. Built to represent the needs of the NSG user, the Frontiers Division, FutureÂ Needs Branch, maintains the CINF and engages with NSG and Allied System for Geospatial Intelligence members to identifyÂ intelligence priority areas and projected requirements.
The CINF impacts future GEOINT operations by validating GEOINT user needs coupled with an evaluation of possible gapsÂ in capabilities across the NSG, according to Robert Spans, chief of OGM's Current and Future Needs Branch. This ensures theÂ CINF represents community needs for GEOINT capabilities that are robust, flexible, integrated and readily available, providing aÂ critical baseline on which to advance GEOINT.
Modeling the Future of GEOINT
Building on the CINF's tools and information, OGM's modeling and simulation program generates computer models thatÂ simulate the performance of GEOINT systems in an effort to analyze their performance and explore alternatives, said Riley Jay,Â chief of OGM's Modeling and Simulation branch.
Initially, the CINF team produces a subset of the CINF database, tailored to the anticipated global and regional needsÂ appropriate to the questions at hand and supportive of multiple scenarios. The modeling team then defines the sensor,Â intelligence cycle requirements and operations concept for the architecture being modeled.
These elements are combined with the tailored CINF needs information and input into OGM modeling tools, which provideÂ quantity and quality collection statistics over a specific time period for the system being modeled. The CINF's visualization toolsÂ provide breakouts of day-by-day and cumulative collection results, which can be broken down by things such as architecture,Â sensor type and target type.
These performance results may also beÂ incorporated into a value model that combines multiple metrics into a single utility value, which then can be plotted to showÂ systems performance versus cost of investment. Historically, these efforts studied capabilities in a larger, general context, butÂ some recent studies have focused on specific questions or systems from GEOINT partners concerned with system Â performance while facing looming budget cuts.
One such partner at the Defense Intelligence Agency is U.S. Strategic Command's Joint Functional Component CommandÂ for Intelligence, Surveillance and Reconnaissance (JFCC-ISR). According to Bob Metcalf, chief of the JFCC-ISR Modeling andÂ Analysis Support Branch, OGM's models and studies have helped senior leadership make timely, well-informed decisions byÂ distilling complex geospatial intelligence questions down to necessary details in a concise, accurate and repeatable fashion.
Defining Future Efforts
Both the CINF and OGM's modeling and simulation efforts are vital to ensuring the community's success. By developingÂ robust system data sets and operating advanced models and quantitative tools with analytic flexibility, OGM can address aÂ range of scenarios, deliver results quickly and enable independent verification and validation of analyses.
Given today's austere budget conditions and evolving analytic environment, these objective evaluations grow in importance.Â The criticality of meeting NSG users' mission needs, while being good stewards of public investment, necessitates a rigorousÂ examination of each GEOINT capability. As national security priorities evolve, NSG commitments to global and defenseÂ operations will continue to demand timely and accurate GEOINT support to U.S. and allied missions around the world.
Additionally, the Frontiers Division is expanding modeling efforts and data sets, providing new capabilities to better informÂ NSG leadership. The group is working to include technologies such as overhead persistent infrared and light detection andÂ ranging, both of which have seen increased usage in GEOINT operations, such as during the 2010 Haiti earthquakeÂ humanitarian and recovery efforts.