Find the flooding on the map from social media

Georgia Coastal Flooding Platform would allow residents, researchers and community managers to visualize and estimate the current flood risk for any given location in the city of Savannah and Brunswick.

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Real-time Flood Risk Modeling Using Social Media Data

Flooding is an ever-increasing problem for coastal Georgia and requires pro-active risk management to minimize its adverse effects. Currently, flood risk management is guided by hurricane model results, which, unfortunately, are often coarse, out of date, and are not designed for local level planning. Given that coastal areas are dynamic and constantly changing, localized flood models are desperately needed to effectively plan for and respond to extreme flood events. This project aims to improve the understanding and prediction of flood risk through big data and social media analytics.

Publication supported in part by an Institutional Grant (NA18OAR4170084) to the Georgia Sea Grant College Program from the National Sea Grant Office, National Oceanic and Atmospheric Administration, U.S. Department of Commerce.

All views, opinions, findings, conclusions, and recommendations expressed in this material are those of the author(s) and do not necessarily reflect the opinions of the Georgia Sea Grant College Program or the National Oceanic and Atmospheric Administration.

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Social Media and Text Mining

The flooding information from historical tweets was extracted by text mining technolog for flooding modeling

Machinea Learning and Big Data

Machine learning algorithms were applied for predicting the flooding risk based on the historical big data

Scale and event

The sampling for modeling is based on 10-meter high resolution data and six typical storm events selected from the storms between 2011 and 2018

Historial and realtime

The trained flooding model can predict the flooding risk at any spot in the city for historical and current events.

Explore the flooding map by yourself!

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Ge Zhang

Research Scientist at Georgia Institute of Technology (GT)

Tony Giarrusso

Senior Research Scientist at GT

Jill Gambill

Faculty at University of Georgia Marine Extension and Georgia Sea Grant

Tara McKinnon

Master student of Geographic Information Science and Technology at GT

Lijun Tong

Master student of Computational Science and Engineering at GT

Yiou Zhu

Master student of Computational Science and Engineering at GT

Lier Liu

Master student of Geographic Information Science and Technology at GT