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Jeff Thurston — ” It is vitally important that we not lose track of the fact that human markup on imagery or maps, is intelligence of the highest quality and most useful. This is why maps, in the truest sense, are the highest forms of geospatial intelligence. They contain both GEOINT derived information and, as circumstance permit, are fused with human intelligence. “

Matt Ball — ” Maps are a good means for portable communication, but geospatial intelligence adds additional channels to map-based communications. Geospatial intelligence involves simultaneous access and input to integrated information by a group of individuals with different areas of expertise. The map becomes the repository for these multiple interpretations and collaboration.”

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A map has much wider scope than geospatial intelligence. But not all maps are created equal, some are more intelligent than others. This is why cartographer’s scratch their heads every time they hear the term geospatial intelligence. A good map is intelligence – period.

However, in 2004 the U.S. National Imagery and Mapping Agency (NIMA) renamed itself to become the National Geospatial-Intelligence Agency (NGA). Overnight, this put the term ‘geospatial intelligence’ into the limelight and peoples minds. Furthermore, NGA outlined a definition [1]:

“(5) The term `geospatial intelligence’ means the exploitation and analysis of imagery and geospatial information to describe, assess, and visually depict physical features and geographically referenced activities on the Earth. Geospatial intelligence consists of imagery, imagery intelligence, and geospatial information.”.

For many, this definition is taken as the de facto definition. Thus geospatial intelligence, as a term, by and large evolves from the military, supported by that definition – in layman terms, information is extracted from imagery.

My research into this question discovered a morphing of the term. As author Harrison Donnelly writes in Military Geospatial Technology magazine, “geospatial intelligence continues to define itself as a profession, gaps remain between the needs of geoint-using government agencies and the growing number of academic programs in the field, according to a recent roundtable of experts.”

Consequently, I think it is fair to say that the term ‘geospatial intelligence’ is evolving well beyond where it started as an imagery focused term. In fact, I would argue that slowly we are awakening to the fact that infrastructure in whatever form it takes, has a strategic importance of military significance. |In other words, transportation corridors, bridges, utilities and all else, are sources of geospatial intelligence and invoke the use of geotechnologies like CAD and GIS in their design, construction, protection and management.

One must clearly understand, that without imagery in the equation, under today’s definition, there is no geospatial intelligence.

Maps can exist without geospatial intelligence. They can be created from memory, terrestrial measurement, global positioning system (GPS) technology, surveying equipment of through scanning, digitising and or copying. Maps exist as drawings on rocks, stones, paper, wood or almost any other type of surface. They can also be digital. You don’t necessarily need a satellite image to create a map, and aerial imaging is not needed either.

But – let me be quick to point out that I doubt we would see half the maps being created today, if imagery related creation techniques such as feature extraction did not exist.

Popular marketing has ‘intelligized’ geography today. You can find military intelligence, business intelligence, location intelligence, geospatial intelligence, ambient intelligence, spatial intelligence and fused intelligence.

But – the world is starving for intelligent maps.

And this is really the objective. An intelligent map is more than a dot on a pixel. An intelligent map includes a rich blend of spatial analysis, understandable and descriptive annotation and accurate features and geo-referencing.

Intelligent maps go way beyond this further to encompass the hardware systems intelligent maps are delivered within (2D, 3D and 4D) as well as incorporating cultural and communication variables. The intelligent map knows no bounds toward delivering its message and achieving its result. We like to think that geospatial intelligence is only military in nature, but I would caution folks not to limit their definitions. In a military context, information is information, the chief difference being only where it is applied and which use.

You will hear the term fusion or data fusion quite often today. Fusion intelligence is about integrating sources of disparate information into one place, implying a convergence of information for ease of accessibility and use. Location intelligence is based on the notion that location is the primary element that adds intelligence – you can have wholly wrong information, yet still have a place, and call it location intelligence. Fusion, at least to me, implies correctness in the single sources as they are integrated – underline the word correctness. It goes to the heart of quality.

Military intelligence, in a classical sense, means military-specific information obtained through all channels to support military missions and decision making. This does not necessarily mean classified information only. Spatial intelligence implies an ability to operate in a spatial context, such as manipulating ideas and information spatially.

Why? Because we were doing all of these in 1800, 1900, 1940 and 1970 and 2008 already.

Geospatial Intelligence is really about quality.

When you get down to it. Whether it’s military intelligence, environmental intelligence or business intelligence; quality matters, because it goes to the heart of usability, uncertainty, accuracy, timeliness and being fit-for-purpose. We want high intelligence information of a locative nature for effective decisions.

Maps are for everyone. The quality varies dependent upon the application and context though. Where a truck driver wants to get home early, may not necessarily require a high quality digital elevation model (DEM). But where an airborne drone is being used, then a high quality DEM will probably matter.

Today map production is highly dependent upon satellite imagery. Many excellent products like those from ENVI, Leica Geosystems Geospatial Imaging, BAE Systems, PCI Geomatics and Clemex (scale difference) can extract features. Each of these can be automated to achieve high levels of feature extraction, processing lots of imagery per hour. In this way they contribute to map making.

But, it is vitally important that we not lose track of the fact that human markup on imagery or maps, is intelligence of the highest quality and most useful. This is why maps, in the truest sense, are the highest forms of geospatial intelligence. They contain both GEOINT derived information and, as circumstance permit, are fused with human intelligence. Artifical intelligence and other interesting research will help us to cross the bridge between auto-intelligence and human-intelligence.

So – let me ask you this. If geospatial intelligence involves imagery and can be automated; just how useful is geospatial intelligence alone – given human intelligence is not added to the map?

Maps have wider scope and usually entail human logic and deduction into their creation, regardless of where the data is derived from.

It will be very interesting to see artificial intelligence, robotics and semantics make their way into geospatial intelligence applications for this reason. I also think we have barely opened the door to understanding how GIS will contribute to such applications in the future.

Additional Information:

[1] Conference Report on H.R. 1588, National Defense Authorization Act For Fiscal Year 2004: Conference Report (H. Rept. 108-354)

[2] Three Days of Geoint Tech

  The term geospatial intelligence was initially coined by the National Imagery and Mapping Agency, now the National Geospatial-Intelligence Agency, to describe the exploitation and analysis of imagery and mapping data to reference activities on the Earth. The term is a good explanation of the integration of a number of data sources to create an ever clearer picture of an evolving reality.

In a previous Perspectives post I took a crack at the difference between maps vs. digital data, but geospatial intelligence is a different matter. The distinction that I make between simply digital geospatial data and geospatial intelligence is the addition of analysis, and the use of data of the greatest currency (if not real-time).

Maps are a good means for portable communication, but geospatial intelligence adds additional channels to map-based communications. Geospatial intelligence involves simultaneous access and input to integrated information by a group of individuals with different areas of expertise. The map becomes the repository for these multiple parties to add their interpretations and communicate scenarios to deal with an evolving situation. The dynamic map becomes the ultimate collaboration tool when dealing with an Earth-based event of significant geographic scope.

Maps Beyond Media

There’s an important paper in the International Journal of Geographical Information Science by Daniel Sui and Michael Goodchild that describes GIS as media, with the common base map containing many layers that can each be thought of as channels of information. I really like the analogy of GIS to media, it communicates the dynamic nature of GIS and its utility as a repository for multidisciplinary information.

I believe that geospatial intelligence goes well beyond the one-way communication that is media. Rather than simply a repository of knowledge, geospatial intelligence adds interaction, experimentation, scenario building and heightened awareness of a location that allows us to effectively and efficiently deal with problems.

As our systems evolve to invoke our cognitive processes, they will speed the collaborative interchange and will be better equipped to help us make quick sense of complex situations. There’s the potential here for a system that applies a degree of artificial intelligence that understands spatial relationships and processes to aid the human agents. A system that can clearly relate the potential outcomes to model-based user inquiries will prove the full potential of geospatial technology.

Technology Evolution

What are the technological evolutions needed to realize the above scenario? Data interoperability between disparate systems is key. A model-based interaction at multiple scales with multiple inputs is necessary. The addition of temporal capabilities to go backward and forward along a timeline, seeing how situations evolve. The integration of sensors to automatically add constant intelligence to the model for manipulation.

Work on all of the above items is underway by researchers working in industry and academia. A considerable amount of money is being invested in these objectives, with a majority of spending in military circles.

This vision is clearly part of the Open Geospatial Consortium’s interoperability program. The OGC Web Services (OWS)-4 testbed incorporated many of these items, including sensors, workflows, decision support, and CAD/GIS/BIM integration. Only the temporal component seems to be missing here. View the demonstration video to get a clearer picture of what’s currently possible.

Geospatial Intelligence for an Evolving World

While the term geospatial intelligence has its roots in the military, there’s an application of these concepts in a wide range of situations. Earth systems are decidedly dynamic, and with the increased volatility of climate change and human development in areas of questionable suitability, natural disasters have the potential of exacting an increasing toll on human life. The tools and techniques of geospatial intelligence can play an important role to mitigate these impacts.

Geospatial intelligence isn’t relegated only to reactions to crisis situations, it can also be employed to understand the complex and sometimes slow-moving progress of global change. A network of sensors that feed data into a common view that can be used to monitor and model multidisciplinary theories can lead to a much-greater understanding of our planet.

As geospatial technology evolves from maps to digital data to geospatial intelligence, we build upon our knowledge and understanding. Each iteration of this evolution will continue to have a role to play, yet geospatial intelligence, which is the most immediate and least abstract, will capture a dominant market share.

 

 

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