Utilizing Remote Sensing Technology in Post-Disaster Management of Transportation Networks

Infrastructure system components such as bridges, highways, tunnels, traffic systems, road pavements, and other systems are considered assets that should be protected and properly managed. Yet, the degree of deterioration and the risk of exposure to natural (e.g., earthquakes, floods, etc.) as well as malicious disasters are dangerously high. Major decisions must be made to allocate the available but limited funds for maintaining and safeguarding our national infrastructure. Additionally, transportation services play an important role in post-disaster recovery and are an integral part of most response functions. These services are vital for initial rescue operations and disaster assistance. Traffic delays that occur during the reconstruction period can be greatly minimized through effective traffic management strategies. The need for vulnerability assessment and disaster mitigation in densely populated areas, such as the NY/NJ metropolitan area, is obvious. In this project, the authors propose the use of novel remote sensing technologies to quickly assess damage to the transportation infrastructure. Some of the latest remote sensing technologies can detect very small displacements of infrastructure elements, such as roads and bridges, up to centimeter accuracy. Thus, this information along with historic information about transportation infrastructure components combined with simple yet accurate structural engineering models can be used to determine individual components of a given network that are susceptible to failure under various loading conditions. This probabilistic failure mapping of the infrastructure can then be used to develop robust transportation and emergency response plans that minimize the risk of disruptions. Based on the preliminary findings of this research project, it is shown that the information obtained from remote sensing technology is important in providing reliable support for the decision-making system for preparedness and mitigation. However, the availability of high-resolution images is key to the future success of the research initiative described in this report. In the absence of such high-resolution satellite images, the proposed post-disaster management approach cannot be realistically tested unless simulated images are employed. Even though using simulated images is beyond the scope of this project, the authors hope to be able to access high-resolution satellite SAR data of earthquake-prone urban areas in the near-future. This option will allow to further study the appearance of bridges and highways in synthetic aperture radar (SAR) and the advanced InSAR images, and extract as much information as possible on their conditions. Once the feasibility of damage assessment is verified using real satellite images, the next step will be to use this information in conjunction with probabilistic routing and dynamic traffic assignment algorithms that can generate low risk routes for evacuation and other post-disaster operations in dense urban areas.

• Record URL:
  http://utrc2.org/research/assets/156/Remote-Sensing1.pdf
• 
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/61309
• Supplemental Notes:
  • This research was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Rutgers University, Piscataway

  Center for Advanced Information Processing, 96 Frelinghuysen Road
  Piscataway, NJ  United States  08854-8014

  University Transportation Research Center

  City College of New York
  Marshak Hall, Suite 910, 160 Convent Avenue
  New York, NY  United States  10031

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Nassif, Hani H
  • Ozbay, Kaan
  • Elawar, Ayman
• Publication Date: 2011-1-21

Language

• English

Media Info

• Media Type: Web
• Edition: Final Report
• Features: Figures; References;
• Pagination: 45p

Subject/Index Terms

• TRT Terms: Bridges; Decision making; Disaster preparedness; Disasters and emergency operations; Dynamic traffic assignment; Emergency management; Evacuation; Highways; Infrastructure; Remote sensing; Routing; Urban areas
• Identifier Terms: Synthetic aperture radar
• Uncontrolled Terms: Damage assessment; High resolution data; Satellite imagery
• Subject Areas: Bridges and other structures; Highways; Operations and Traffic Management; Security and Emergencies; I72: Traffic and Transport Planning; I73: Traffic Control;

Filing Info

• Accession Number: 01341789
• Record Type: Publication
• Report/Paper Numbers: Report No. 49777-20-19
• Files: UTC, NTL, TRIS, USDOT
• Created Date: Jun 3 2011 4:41PM