Cloud-based federation and fusion of distributed data sources for supporting hurricane response : requirements, challenges, and opportunities.
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2016-12-01
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Abstract:Geospatial data have been playing an increasingly important role in disaster response and recovery. For large-scale natural disasters such as Hurricanes which often have the capacity to topple a large region within a span of a few days, disaster preparation and response often involves intensive collaborations between multiple agencies and organizations, some of them are geographically distant. However, such collaborations are often hampered by several obstacles: (1) Agencies and utility owners are often reluctant to openly share their own data sets due to their concerns on data security; (2) Sharing and moving of large-scale data sets are difficult, especially over the internet; and (3) Lack of data management solutions that are both scalable and distributed to accommodate various integrative analysis needs. As the result, integrative analyses of system vulnerabilities and system-level planning on response and recovery actions are often not possible. This study focused on Hurricane Sandy as an empirical case to characterize the types of geospatial data sets useful for disaster management, characterize processing patterns and needs with these geospatial data, review types of cloud computing infrastructures that are available for geospatial data analytics during natural disasters, and suggest gaps in technical capabilities and needs in future research efforts. The study provided first-hand knowledge about the type and the volume of geospatial data sets that now can be collected to support disaster management and a synthesis of cloud computing infrastructures for geospatial computing in time-sensitive applications. These outcomes can be used by transportation agencies to better plan their response activities.
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