Tracking Airborne and Satellite Remote Sensing Collection Assets for Emergency Response Phase
In the event of a natural disaster, technological disaster, terrorist attack, or other major event, remotely sensed imagery collected immediately after the event can provide highly useful information. Imagery can provide a situational awareness of the geographic dimensions of the disaster. Post-event imagery becomes an onscreen “back-drop” to the previous infrastructure locations, helping to guide emergency responders to damaged facilities. Information extracted from post-event imagery provides quantitative information on the resources needed for the response and subsequent recovery phases of the disaster cycle. Post-event imagery can also provide the historic documentation of the affected landscape for governmental, insurance, and civilian applications. Perhaps the most valuable information from post-event imagery is during the emergency response phase of the hazard cycle when estimates of damage extent, damage to critical facilities/transportation routes or lifelines, or housing damage can be quickly accessed (i.e. within 24-hours of the event).
The purpose of this project is to design and implement a database, analytical methods, collaborative solution, and autonomous methods for immediately determining the airborne and satellite remote sensing solutions for disaster response. This two-year project builds on existing capabilities at NASA-Stennis, the University of South Carolina, and commercial airborne collection/downlink solutions supported and utilized within the Department of Homeland Security’s interests. Working with Department of Homeland Security staff and aeroservice industry staff, faculty (Michael E. Hodgson and Sarah E. Battersby) and staff (Kevin Remington) from the GIScience and Remote Sensing Laboratory in the Department of Geography are designing and implementing a solution to track and collaboratively select appropriate airborne remote sensing (in addition to satellite) assets during the disaster response phase in a spatial decision support system.
The implemented solution will include 1) web-server geospatial collection/distribution approaches for airborne remote sensing assets, 2) composite satellite collection opportunity modeling for imaging a large geographic damage area, 3) collaborative framework environment for ranking collection strategies based on multiple stakeholders, 4) a ground-station siting model for receiving airborne image downlinks, and 5) an autonomous notification module for earthquake events (as a prototype).