Unmanned Aerial Systems for Disaster Response and Recovery
Abstract
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. Commercial Remotely Sensed (CRS) data is an invaluable resource in that it facilitates damage mapping, particularly in areas where deploying ground crews is not feasible. Traditional methods of acquiring CRS data can be costly and cumbersome, and the end products may lack the temporal and spatial resolution characteristics to be of use to managers. Unmanned Aerial Systems (UAS) have the potential to overcome these limitations. In this presentation we will describe a decision support system centered on a lightweight, easily-deployable UAS capable of capturing mapping-grade 2D imagery and producing 3D models suitable for a range of post-event analyses from identifying damage to computing the amount of fill needed to repair a road
Jarlath O’Neil-Dunne is the Director of the University of Vermont’s (UVM) Spatial Analysis Laboratory (SAL). He is a faculty member in the Rubenstein School of the Environment and Natural Resources and a faculty associate in UVM’s Transportation Research Center (TRC). Over the years his research has focused on the application of geospatial technology to a broad set of issues ranging from ecology to urban planning to disaster response to environmental justice. He has expertise in the application of object-based image analysis techniques, unmanned aerial systems, and spatial modeling. He is also a former officer in the United States Marine Corps where he served in East Africa, the Middle East, and East Asia. During the early stages of Operation Iraqi Freedom he co-directed the Marine Corps’ imagery intelligence assets.
Sponsored by: The Office of Research and Technology (OST-R), University Transportation Centers Program
“DISCLAIMER: The views, opinions, findings and conclusions reflected in this presentation are the responsibility of the authors only and do not represent the official policy or position of the USDOT/OST-R, or any State or other entity.”
For more information, contact Denise E. Dunn at denise.e.dunn@dot.gov