Integrating remotely sensed and ground observations for modeling, analysis, and decision support

Earthquake science and emergency response require integration of many data types and models that cover a broad range of scales in time and space. Timely and efficient earthquake analysis and response require automated processes and a system in which the interfaces between models and applications are established and well defined. Geodetic imaging data provide observations of crustal deformation from which strain accumulation and release associated with earthquakes can be inferred. Data products are growing and tend to be either relatively large in size, on the order of 1 GB per image with hundreds or thousands of images, or high data rate, such as from 1 second GPS solutions. The products can be computationally intensive to manipulate, analyze, or model, and are unwieldy to transfer across wide area networks. Required computing resources can be large, even for a few users, and can spike when new data are made available or when an earthquake occurs. A cloud computing environment is the natural extension for some components of QuakeSim as an increasing number of data products and model applications become available to users. Storing the data near the model applications improves performance for the user.