Researchers from various universities and labs enhance flood data collection with natural language processing and machine vision

Summary:

Researchers at UC Berkeley, University of Dundee, Oak Ridge National Laboratory, Tufts University and Blue Urchin LLC have employed social media and crowdsourcing data to address the lack of hyper-resolution datasets for urban flooding. Data gathered from Twitter and a crowdsourcing app, MyCoast, are analysed using natural language processing and computer vision. The complementary data gathering method can improve detailed flooding risk analysis, urban flooding control, and the validation of hyper-resolution numerical models.

Problem:

As urbanization proceeds and climate change intensifies, urban planners and city managers are facing the challenge of preparing for and mitigating flood damage. They need tools to monitor and predict the event for emergency response and development planning.

Monitoring and predicting urban floods needs high-resolution data with good coverage. It is also important to have a good coverage of flood data to obtain complete information."