Presentation
On Building a Big Data Analysis System for California Drought
2017 IEEE International Conference on Big Data (Big Data)
(2017)
Abstract
Water scarcity is one of the serious problems that California is facing today. Water scarcity leads to doughtiness when not properly addressed. In the recent years, California faces a serious drought problem. This provides a strong demand in building a real-time system to support water resources analysis, drought modeling and prediction. Existing models and approaches lack of desirable accuracy in predicting and analyzing California Drought. This paper proposes a big data based approach to support California Drought analysis and prediction based on diverse data sets, including climate sensor and satellite data, weather data, and drought condition and water usage reports. The paper reports an implemented system supporting big data analytics for California Drought. It uses a proposed California Drought Index and presents big data analytics results based on existing big data models and algorithms, as well as proposed graphic models.
Keywords
- Drought,
- Data Analytics,
- PDSI Index,
- California
Disciplines
Publication Date
April, 2017
DOI
10.1109/BigDataService.2017.23
Comments
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Citation Information
Pengcheng Zhang, Jerry Gao, A. G. Thomas, K. P. Alagupackiam, et al.. "On Building a Big Data Analysis System for California Drought" 2017 IEEE International Conference on Big Data (Big Data) (2017) Available at: http://works.bepress.com/sen_chiao/54/