Crowdsourced Disaster Map Shows Real-Time Risks During Critical Incidents

With input from residents on the ground, the crowdsourced RiskMap provides real-time, street-by-street disaster information to the public and first responders.

by Chris Bousquet, Data-Smart City Solutions / September 19, 2017

Hurricanes Harvey and Irma unleashed the power of a civic technology community intent on lending a helping hand. Both before and during these natural disasters, tech advocates created tools that would aid with response and recovery.

Risk Map is one project that leveraged technological advances and the power of resident knowledge to ensure the safety of those in Irma’s wake. Created by research scientists at the MIT Urban Risk Lab via a partnership with Broward County, FL, is a crowdsourced platform that displays real-time, street-by-street information on the status of flooding in affected areas. 

The tool allowed residents to submit flooding reports via messages with a chatbot on Twitter, Telegram, and Facebook. Users submitted their location, a description of the conditions, and a photo, and the RiskMap aggregated this information and assigned city corridors one of four alert levels based on estimated flood depth.

While only launched in Broward County for Irma—the project is still in its pilot stage—the tool provided a critical resource for flood information. By tapping into the knowledge of residents on the ground in real time, the map provided up-to-date and accurate information on flooded areas.

If expanded to a greater geographic area and larger user base, the RiskMap could transform resident alert systems and emergency response. Instead of receiving alerts about flooding in neighborhoods or streets they may not even know the names of, residents could visualize the status of flooding on every street of their city. And, if put in the hands of first responders, the tool could direct interventions to those areas in greatest need.

Irma was the second test for the application, following a pilot in Indonesia earlier this year that attracted more than 300,000 users in 24 hours and linked up with Uber to help drivers avoid floodwaters. Going forward, the Urban Risk Lab team hopes to expand the scope of the project, include information on other types of hazards like power outages or downed trees, and add an alert system to inform residents of dangerous areas.