Next-generation geospatial-temporal information technologies for disaster management
- IBM T. J. Watson Research Center, Yorktown Heights, NY (United States); Johns Hopkins University
- IBM T. J. Watson Research Center, Yorktown Heights, NY (United States)
Traditional geographic information systems (GIS) have been disrupted by the emergence of Big Data in the form of geo-coded raster, vector, and time-series Internet-of-Things data. This article discusses the application of new scalable technologies that go far beyond relational databases and file-based storage on spinning disk or tape to incorporate both storage and processing data in the same platform. The roles of the Apache Hadoop Distributed File Systems and NoSQL key-value stores such as the Apache Hbase are discussed, along with indexing schemes that optimally support geospatial-temporal use. Here, we highlight how this new approach can rapidly search multiple GIS data layers to obtain insights in the context of early warning, impact evaluation, response, and recovery to earthquake and wildfire disasters.
- Research Organization:
- Johns Hopkins University, Baltimore, MD (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
- Grant/Contract Number:
- EE0008215
- OSTI ID:
- 1991276
- Journal Information:
- IBM Journal of Research and Development, Journal Name: IBM Journal of Research and Development Journal Issue: 1/2 Vol. 64; ISSN 0018-8646
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
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