USGS Imagery Applications During Disaster Response After Recent Earthquakes

Abstract:

It is not only important to rapidly characterize surface fault rupture and related ground deformation after an earthquake, but also to repeatedly make observations following an event to forecast fault afterslip. These data may also be used by other agencies to monitor progress on damage repairs and restoration efforts by emergency responders and the public. Related requirements include repeatedly obtaining reference or baseline imagery before a major disaster occurs, as well as maintaining careful geodetic control on all imagery in a time series so that absolute georeferencing may be applied to the image stack through time. In addition, repeated post-event imagery acquisition is required, generally at a higher repetition rate soon after the event, then scaled back to less frequent acquisitions with time, to capture phenomena (such as fault afterslip) that are known to have rates that decrease rapidly with time. For example, lidar observations acquired before and after the South Napa earthquake of 2014, used in our extensive post-processing work that was funded primarily by FEMA, aided in the accurate forecasting of fault afterslip. Lidar was used to independently validate and verify the official USGS afterslip forecast. In order to keep pace with rapidly evolving technology, a development pipeline must be established and maintained to continually test and incorporate new sensors, while adapting these new components to the existing platform and linking them to the existing base software system, and then sequentially testing the system as it evolves. Improvements in system performance by incremental upgrades of system components and software are essential. Improving calibration parameters and thereby progressively eliminating artifacts requires ongoing testing, research and development. To improve the system, we have formed an interdisciplinary team with common interests and diverse sources of support. We share expertise and leverage funding while effectively and rapidly improving our system, which includes the sensor package and software for all steps in acquiring, processing and differencing repeat-pass lidar and electro-optical imagery, and the GRiD metadata and point cloud database standard, already used during disaster response surge events by other agencies (e.g., during Hurricane Sandy in 2012).