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This work addresses the use of commercial off-the-shelf rotor-based unmanned aerial vehicles (UAVs) to facilitate emergency forces in the rapid structural assessment of a disaster site by means of aerial image-based reconnaissance. It proposes a framework that consists of two parts and relies on the integrated stereo vision sensor and the visual payload camera of the UAV to execute three high-level applications that aim at facilitating first responders in disaster relief missions.

Aerial reconnaissance.

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To assist in moving intelligence, surveillance, and reconnaissance (ISR) planning and execution forward from a fixed target and deliberate planning focus to one centered on emerging targets, the authors propose enhancing the collection management process with a strategies-to-tasks and utility framework. By linking collection targets to operational tasks, objectives, and top-level commander's guidance with relative utilities, planning for the daily intelligence collections and real-time retasking for ad hoc ISR targets could be enhanced. When current tools are modified to provide this information, planners will be able to link collection targets to top-level objectives for better decisionmaking and optimization of low-density, high-demand collection assets, and intelligence officers will be better able to deal with time-sensitive, emerging targets by rapidly comparing the value of collecting an ad hoc collection with the value of collecting opportunities already planned.

Aerial reconnaissance --- Military intelligence

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Aerial reconnaissance --- History.

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Dramatic changes in the security environment in the past two decades have led to a greatly increased demand for U.S. Air Force intelligence, surveillance, and reconnaissance (ISR) capabilities. Today, the Air Force must provide ISR to support a growing set of missions while remaining postured to support major combat operations (MCOs) should the need arise. To meet these requirements, the Air Force is currently undertaking unprecedented measures to expand and enhance its ISR capabilities. Particular urgency has been attached to cultivating its fleet of sophisticated remotely piloted aircraft (RPA) to support current operations in Afghanistan and Iraq. Equally critical to these efforts, however, is the Air Force's extensive processing, exploitation, and dissemination (PED) force, which is essential to convert the raw data collected into usable intelligence and deliver it to the warfighter. It is therefore imperative to assess the size and mix of the Air Force's PED force to ensure that the ability to conduct all necessary PED within required timelines keeps pace with the increases in the amount and type of information collected. This study addressed the particular challenges associated with the exploitation of motion imagery within the Air Force Distributed Common Ground System (DCGS). Motion imagery collections from full-motion video (FMV) sensors on RPAs have risen rapidly to the point at which they now consume the largest share of Air Force DCGS resources, and new wide-area motion imagery (WAMI) sensors now being deployed have the potential to vastly increase the amount of raw data collected. The information explosion resulting from these vast amounts of motion imagery threatens to leave Air Force intelligence analysts drowning in data. One approach to meeting these challenges was inspired by an examination of related practices in the commercial world. It consists of implementing certain process changes and adopting a new organizational construct to improve the effectiveness of Air Force intelligence analysts while confronting the reality of limited resources.

Aerial reconnaissance --- Military intelligence --- United States.

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Environmental monitoring. --- Remote sensing. --- Aerial reconnaissance.