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Research

Rapid Exploitation of Commercial Remotely Sensed Imagery for Disaster Response & Recovery

Principal Investigator: Jarlath O'Neil-Dunne
Funding Agency: USDOT

Project Summary

Natural disasters can severely impact transportation networks. In the hours and days following a major flooding event, knowing the location and extent of the damage is crucial for incident managers for a number of reasons: it allows for emergency vehicle access to affected areas; it facilitates the efficient rerouting of traffic; it raises the quality and reduces the cost of repairs; and it allows repairs to be completed faster, in turn reducing the duration of costly detours. Commercial Remote Sensing (CRS) imagery is increasingly being used in disaster response and recovery, but acquiring imagery is far easier than extracting actionable information from it. An automated approach to damage assessment is needed, but traditional automated image analysis techniques are inadequate for identifying or characterizing road and bridge damage from high resolution imagery. We propose a project with two objectives: 1) to develop, calibrate and deploy a decision support system capable of identifying road and bridge damage from high-resolution commercial satellite images and; 2) to estimate the amount and type of fill material required for repairs using digital surface models derived from lightweight Unmanned Aerial Vehicles (UAV) programmed to fly over damage road segments. This approach would employ state-of-the-art, object-based image analysis techniques, cost-based image matching, and other advanced computing techniques. We also propose to collaborate with state departments of transportation to develop a web-based interface to share information derived from the CRS imagery.

Irene Damage
Figure 1A. Image of Vermont roads pre-Irene. Figure 1B. Image of Vermont roads post-Irene (copyright DigitialGlobe)


Project Team

Caesar Singh, Program Manager (PM), US DOT
Jarlath O'Neil-Dunne, Faculty Research Associate and Director of the UVM Spatial Analysis Laboratory (SAL) - Principal Investigator
Austin Troy, PhD, Director of the University of Vermont (UVM) Transportation Research Center (TRC)
Amanda Hanaway-Corrente, Professional Engineer (PE) at UVM
James Sullivan, Research Analyst at UVM TRC
Sean MacFaden, Research Specialist at UVM SAL
Ernest Buford, Research Specialist at UVM SAL


Technical Advisory Committee

Guy Rouelle, Aviation Program Administrator, Vermont Agency of Transportation (VTrans)
Stephanie Magnan, Asset Management Specialist, VTrans
Wayne Gammell, Maintenance Administrator, VTrans
Johnathan Croft, GIS Database Administrator, VTrans
Michele Boomhower, Chittenden County Regional Planning Commission (CCRPC) Assistant/Metropolitan Planning Organization (MPO) Director
Christopher Jolly, Planning & Programming Engineer, Federal Highway Association (FHWA) - Vermont Division
Roger Thompson, ITS/Safety Engineer, FHWA - Vermont Division
Charles Hebson, Manager of Surface Water Resources, Maine Department of Transportation (DOT)
Staci Pomeroy, River Scientist, Vermont Department of Environmental Conservation


Project Documents
Technical Proposal
Contract
Quarterly Report Guidelines
Task List

Project Links
Video: Obtaining Data from the USGS Hazard Data Distribution System (HDDS)
White Paper on Commercial Remotely Sensed (CRS) Data
White Paper on Lessons Learned on Flying Unmanned Aerial Vehicles (UAVs) in Vermont
"Emerging Technologies Help State DOTs Meet the Growing Challenge of Extreme Weather", reprinted with permission from AASHTO Climate Change Briefing, 10/1/13
NEW: 2014 Transportation Research Board Annual Meeting Presentation: Sensing Technologies for Transportation Applications
Quarterly Reports:
December 2012 through March 2013
April 2013 through June 2013
July 2013 through September 2013
October 2013 through December 2013

Technical Advisory Committee Meeting Minutes:
March 19, 2013 Meeting
March 19, 2013 Meeting (Recording)
December 06, 2013 Meeting
December 06, 2013 Meeting (Recording)

Password Protected Documents:
None at this time.