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• W238817139 abstract "Abstract : One of six primary intelligence disciplines, IMINT traditionally has accounted for the lion's share of intelligence-derived information since World War II. Because raw imagery has limited value until it has been exploited, the increased volume of raw imagery demands an enhanced ability for combatant commanders and the National Imagery and Mapping Agency (NIMA) to effectively manage imagery exploitation assets in support of combatant commanders strategic and operational intelligence requirements. A shortage of imagery analysts (IA) relative to the amount of raw imagery needing exploitation has drawn national-level attention to IMINT. This monograph offers a model that the intelligence community may use to determine the most effective operational employment of reserve component (RC) intelligence elements in support of combatant commanders strategic and operational intelligence requirements. In terms of scope, RC forces account for approximately 40 percent of intelligence production in support of the combatant commands. More than 90 percent of all RC imagery analysts have deployed in the 18 months following the 11 September 2001 terrorist attacks. The model will show how optimal use of imagery analysts whether active or reserve, military or civilian will maximize combatant commanders analytical power, and therefore improve their ability to fulfill their strategic and operational intelligence requirements. To define the issues associated with RC contribution to IMINT and geospatial information requirements, the author surveyed the combatant commanders intelligence leadership at the Joint Intelligence Centers (JIC). The study structure identifies and links the major players involved in RC contribution to combatant commanders IMINT and geospatial information needs." @default.
• W238817139 created "2016-06-24" @default.
• W238817139 creator A5050020318 @default.
• W238817139 date "2003-05-22" @default.
• W238817139 modified "2023-09-23" @default.
• W238817139 title "Reserve Component Contribution to Imagery Intelligence" @default.
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• W238817139 doi "https://doi.org/10.21236/ada416241" @default.
• W238817139 hasPublicationYear "2003" @default.
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