How Phone Data Helps Cities Adapt to Flood Risks from Heavy Rain

What is it about?

The research developed a novel framework to assess changes in human mobility during rainfall events using approximately 2.6 million mobile phone signal data collected in Jiangsu, China, during the summer of 2018. The research analyzed human movement at a high spatial granularity of 500-meter grid cells, identifying spatial hotspots with abnormal clustering or reduced human activities. When aggregated to the prefecture-city level, mobility changes varied between -3.6% and 8.9%. The research utilized piecewise structural equation modeling to determine that factors such as city size, transport system, and crowding levels directly affect these mobility responses, while economic conditions have indirect effects. Overlaying this mobility data with a historical urban flood map, the study quantified that mobility changes helped 23 cities reduce flood risks for 0.45 million people by 2.6% but increased risks by a mean of 1.64% in 12 cities affecting 0.21 million people. The research provides insights into urban dwellers' mobility patterns post-heavy precipitation events, aiding urban flood risk assessment and small-scale hazard management.

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Photo by Fredrik Solli Wandem on Unsplash

Photo by Fredrik Solli Wandem on Unsplash

Why is it important?

Understanding the impact of heavy precipitation on human mobility is crucial for improving urban flood risk assessment and supporting the development of resilient and safe cities, aligning with Sustainable Development Goal #11. This study introduces a novel framework utilizing mobile phone data to analyze human mobility changes during rainfall events at a high spatial resolution. By identifying spatial hotspots of altered human activity, the research aids in enhancing urban adaptation and hazard management strategies, ultimately contributing to more sustainable urban environments. Key Takeaways: 1. Mobility Variation: The study reveals that human mobility changes during rainfall events range between -3.6% and 8.9% at the prefecture-city level, indicating significant variability in intracity movement across different urban areas. 2. Influencing Factors: City size, transport systems, and crowding levels are found to directly impact mobility responses, while economic conditions influence these changes indirectly, suggesting multiple layers of factors shaping mobility during heavy precipitation. 3. Flood Risk Implications: Changes in human mobility during heavy rainfall events help reduce flood risks for 23 cities, covering 0.45 million people, but increase risks in 12 cities, affecting 0.21 million people, highlighting the dual impact on urban flood exposure.