Crowd-based spatial risk assessment of urban flooding: Results from a municipal flood hotline in Detroit, MI

This study uses a crowd-sourced municipal call database to characterize the spatial distribution of floodrisk in Detroit, MI. Call data, including dates and addresses, were obtained from the City of Detroit Department of Public Works for 2021. Calls were mapped and aggregated to census tract counts and merged with neighborhood-level data. Associations of predictors with flood calls were tested using spatial regression models. 

The publication concludes the following:

• Multivariate models of census tract level call counts indicated that increased poverty and Black, immigrant, and older residents were positively associated with flood calls, while increased elevation was associated with protective effects;
• Crowd-sourced flood hotline call data can be considered for use as a tool to assess spatial flood risk, but care must be taken to account for possible biases due to socio-economic and technological factors;
• These results should prompt deeper discussion of the determinants of flood risk and should help policymakers and stake-holders design and implement strategies to mitigate risks.