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Here Geospatial Intelligence, or the frequently used term GEOINT, is an intelligence discipline comprising the exploitation and analysis of geospatial data and information to describe, assess, and visually depict physical features (both natural and constructed) and geographically reference activities on the Earth.
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.
In business intelligence, location intelligence (LI), or spatial intelligence, is the process of deriving meaningful insight from geospatial data relationships to solve a particular problem. [1] It involves layering multiple data sets spatially and/or chronologically, for easy reference on a map, and its applications span industries, categories ...
There are also many different types of geodata, including vector files, raster files, geographic databases, web files, and multi-temporal data. Spatial data or spatial information is broader class of data whose geometry is relevant but it is not necessarily georeferenced, such as in computer-aided design (CAD), see geometric modeling.
Electronic intelligence (ELINT) – gathered from electronic signals that do not contain speech or text (which are considered COMINT) Foreign instrumentation signals intelligence (FISINT) – entails the collection and analysis of telemetry data from a missile or sometimes from aircraft tests; formerly known as telemetry intelligence or TELINT
This is a list of GIS data sources (including some geoportals) that provide information sets that can be used in geographic information systems (GIS) and spatial databases for purposes of geospatial analysis and cartographic mapping. This list categorizes the sources of interest.
For example, a significant number of major programs, such as SLS, Orion, and ML2 are over budget, behind schedule, and/or otherwise troubled. ... geospatial intelligence, satellite communications ...
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.