12:00 PM - 12:15 PM
[HTT15-12] Mapping Human Dynamics in Response to Extreme Weather Events Using Geospatial Big Data
★Invited Papers
Keywords:human dynamics, human-centered location data, disaster management, urban resilience
This presentation introduces the innovative use of large-scale geospatial big data, including cellphone location data and seismic noise measurements, to analyze human dynamics during extreme weather events. Human-centric geographic information derived from large-scale social sensing data (e.g. social media, mobile devices, traffic records) is essential in disaster resilience research, as it opens opportunities for innovation by incorporating human responses and human dynamics at the spatial and temporal scales that traditional data sources are unable to capture. This presentation will showcase two case studies: human mobility and extreme heat, and urban activity monitoring using seismic noise.
First, the escalating frequency, duration, and intensity of extreme heat events have posed a significant threat to human society in recent decades. Understanding the dynamic patterns of human mobility under extreme heat will contribute to accurately assessing the risk of extreme heat exposure. Despite the fact that heat-related deaths and illnesses can be greatly decreased through adaptation measures by reducing extreme heat exposure, the extent to which people employ these behavioral adaptation strategies remains largely unquantified. This study leverages an emerging geospatial data source, anonymous cell phone location data, to investigate how people in different communities adapt travel behaviors responding to extreme heat events. Taking the Greater Houston Metropolitan Area as an example, we develop two indices, the Mobility Disruption Index (MDI) and the Activity Time Shift Index (ATSI), to quantify diurnal mobility changes and activity time shift patterns at the city and intra-urban scales.
Once considered irrelevant "noise" in seismological studies, ambient seismic noise is now recognized for its ability to reflect urban human activities such as traffic and construction. Our study leverages data from the Texas Seismological Network (TexNet), which includes 13 seismic stations across the Dallas-Fort Worth area, to detect changes in urban activity levels. During the COVID-19 lockdowns, researchers observed significant reductions in seismic noise concurrent with decreases in human mobility, demonstrating the value of seismic data in real-time monitoring of urban dynamics. This segment of the presentation will discuss our work in extracting human activity indicators from seismic noise and compare these with traditional human mobility data to validate their correlation.
First, the escalating frequency, duration, and intensity of extreme heat events have posed a significant threat to human society in recent decades. Understanding the dynamic patterns of human mobility under extreme heat will contribute to accurately assessing the risk of extreme heat exposure. Despite the fact that heat-related deaths and illnesses can be greatly decreased through adaptation measures by reducing extreme heat exposure, the extent to which people employ these behavioral adaptation strategies remains largely unquantified. This study leverages an emerging geospatial data source, anonymous cell phone location data, to investigate how people in different communities adapt travel behaviors responding to extreme heat events. Taking the Greater Houston Metropolitan Area as an example, we develop two indices, the Mobility Disruption Index (MDI) and the Activity Time Shift Index (ATSI), to quantify diurnal mobility changes and activity time shift patterns at the city and intra-urban scales.
Once considered irrelevant "noise" in seismological studies, ambient seismic noise is now recognized for its ability to reflect urban human activities such as traffic and construction. Our study leverages data from the Texas Seismological Network (TexNet), which includes 13 seismic stations across the Dallas-Fort Worth area, to detect changes in urban activity levels. During the COVID-19 lockdowns, researchers observed significant reductions in seismic noise concurrent with decreases in human mobility, demonstrating the value of seismic data in real-time monitoring of urban dynamics. This segment of the presentation will discuss our work in extracting human activity indicators from seismic noise and compare these with traditional human mobility data to validate their correlation.