Cloud Computing for Science Data Processing in Support of Emergency Response

In a crisis, up-to-date information is one of the most important commodities for decision-makers. Remote sensing data have been instrumental in regional scale damage detection and recovery progress monitoring after significant disasters. However, using remotely sensed data to support an emergency response requires not only the availability of hardware, software, and manpower to process and analyze the data, but also the time to stage the datasets that are required for analyses. Additionally, the volume of remote sensing data that needs to be processed to detect temporal changes accurately in a terrestrial or oceanic ecosystem can easily exceed several terabytes, even for a small region. This is because emergency response requires the use of well-calibrated remotely sensed data products, like those that are generated by the MODIS (Moderate Resolution Imaging Spectroradiometer) Adaptive Processing System (MODAPS). These data sets are stored and distributed by the Level 1 and Atmosphere Archive and Distribution System (LAADS), both located at Goddard Space Flight Center (GSFC), and are necessary to create the custom data products that are needed and used for emergency management situations. Generally, the MODIS datasets are downloaded from GSFC, stored at the user’s facility, and then processed locally. This approach is standardly used by researchers worldwide.