What’s the difference between maps and geospatial intelligence?

by Matt Ball on January 18, 2008

perspectivesblogheader.jpgThe 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.

See what Jeff Thurston has to say on this topic here.

{ 3 comments… read them below or add one }

Paul Dumas May 14, 2008 at 1:16 pm

I haven’t found a value for ground-sample distance in the KML meta-data. Is it a value that is to remain classified?

Matt Ball May 14, 2008 at 3:22 pm


Thanks for the question about KML. I reached out to Carl Reed at the Open Geospatial Consortium, and he states that there are absolutely no proprietary elements of the KML standard.

He suggests that you tap into the KML Developer Support site in Google Groups (http://groups.google.com/group/kml-support) for the answer to your question.


banji olojo November 21, 2008 at 1:38 am

i am interested in been trained in geospatial intelligence.please does any one know an organization or school that does training in such area?

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