A Web-Based System with Spatial Clustering to Observe the Changes of Emergency Distribution Using Social Big Data
Understanding the changes of emergency distribution is an important step in the response to disaster. There are various emergency-related big data available on Internet; however it requires a complex system to use big data for emergency observation. In this study, we propose a Web-based system with spatial clustering to enable the observation to the changes of emergency distribution using social big data. Based upon the widely available Web technology, the proposed system is designed in three components, the social big data scrubbing, spatial big data clustering, and visualizing the changes of emergency distribution. And we applied the observations on two emergency incidents using the Twitter data, one is the Kumamoto earthquake 2016, and the other is the New York Hurricane Sandy 2012.
This research was supported by JST-NSF joint funding, Strategic International Collaborative Research Program, SICORP, entitled “Dynamic Evolution of Smartphone-Based Emergency Communications Network”, from 2015 to 2018.
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