Development of a remote sensing network for time-sensitive detection of fine scale damage to transportation infrastructure : [final report].
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Development of a remote sensing network for time-sensitive detection of fine scale damage to transportation infrastructure : [final report].

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      This research project aimed to develop a remote sensing system capable of rapidly identifying fine-scale damage to critical transportation infrastructure following hazard events. Such a system must be pre-planned for rapid deployment, automate processing routines to expedite the delivery of information, fit within existing standard operating procedures to facilitate ready use during a hazard response scenario, and the tools need to be commercially available to state DOTs. To design the system and meet these needs, the project team proposed an airborne remote sensing system based on a network of collection platforms, an automated image co-registration and change detection routine, and implementation of all software tools within BAE Systems’ GXP line of geospatial software. All image-processing and interpretation tools developed through the project are now commercially available from BAE Systems Inc.

      The resulting proposed system, which satisfies these design parameters, includes:

       Automated image co-registration, change enhancement, and change detection without human intervention required.

       Web based tools for review by engineers of raw imagery, change enhanced, and change detection images through a web browser. Engineers can provide image clips with annotations and text to report their findings to a central common operating picture.

       Software tools to access and supplement interpreted results during field inspections.

       A relationship with US Air Force auxiliary Civil Air Patrol, who operate a nationally distributed network of aircraft and have as part of their existing mission hazard response and other rapid deployment missions.

      Results from the stage 2 “feedback” survey of NMDOT engineers indicate that the system is useful for the inspection of roads and bridges. However, because the system has limited utility for inspecting the superstructure of bridges, confidence is higher when used for inspecting road sections. From the moment the decision is made to deploy the system, it is estimated that information delivery to engineers for remote inspection occurs within 6 hours. This performance rate is currently constrained primarily by the number of platforms available and likely to be improved through introduction of unmanned airborne systems (UAS).

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