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The National Geospatial-Intelligence Agency (NGA) is a combat support agency within the United States Department of Defense whose primary mission is collecting, analyzing, and distributing geospatial intelligence (GEOINT) in support of national security.
Geographic information systems (GIS) play a constantly evolving role in geospatial intelligence (GEOINT) and United States national security.These technologies allow a user to efficiently manage, analyze, and produce geospatial data, to combine GEOINT with other forms of intelligence collection, and to perform highly developed analysis and visual production of geospatial data.
The United States Army Geospatial Intelligence Battalion (GEOINT Battalion or AGB), previously known as the 3rd Military Intelligence Center, is a military intelligence battalion specializing in the production and exploitation of geospatial intelligence (GEOINT), and the only operational military command at the National Geospatial-Intelligence Agency (NGA). [1]
A de facto definition of geospatial intelligence, which is more reflective of the broad international nature of the discipline, is vastly different from the de jure definition expressed in U.S. Code. This de facto definition is: Geospatial Intelligence is a field of knowledge, a process, and a profession.
The term "location intelligence" is often used to describe the people, data and technology employed to geographically "map" information. These mapping applications like Polaris Intelligence can transform large amounts of data linked to location (e.g. POIs, demographics, geofences) into color-coded visual representations (heat maps and thematic maps of variables of interest) that make it easy ...
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The GEOnet Names Server (GNS), sometimes also referred to in official documentation as Geographic Names Data [1] or geonames [2] in domain and email addresses, is a service that provides access to the United States National Geospatial-Intelligence Agency's (NGA) and the US Board on Geographic Names's (BGN) database of geographic feature names and locations for locations outside the US.
Because the world is much more complex than can be represented in a computer, all geospatial data are incomplete approximations of the world. [9] Thus, most geospatial data models encode some form of strategy for collecting a finite sample of an often infinite domain, and a structure to organize the sample in such a way as to enable interpolation of the nature of the unsampled portion.