5 citations · 21 across the 12 of their papers we have counts for
12 papers
Downscaling human mobility data based on demographic socioeconomic and commuting characteristics using interpretable machine learning methods
Yuqin Jiang, Andrey A. Popov, Tianle Duan +1
Understanding urban human mobility patterns at various spatial levels is essential for social science. This study presents a machine learning framework to downscale origin-destinat…
Situational Preparedness Dynamics for Sequential Tropical Cyclone Hazards
Tianle Duan, Qingchun Li, Fengxiu Zhang +2
Sequential tropical cyclone hazards--two tropical cyclones (TCs) making landfall in the same region within a short time--are becoming increasingly likely. This study investigates s…
Uncovering cooling center usage as an adaptation strategy for hurricane-blackout-heat compound hazards during Hurricane Beryl (2024)
Tianle Duan, Fengxiu Zhang, Qingchun Li
Extreme heat and hurricane-induced blackouts could occur simultaneously in the summer, posing great challenges to community health and well-being. Cooling centers serve as a key ad…
Attributed Network Embedding Model for Exposing COVID-19 Spread Trajectory Archetypes
Junwei Ma, Bo Li, Qingchun Li +2
The spread of COVID-19 revealed that transmission risk patterns are not homogenous across different cities and communities, and various heterogeneous features can influence the spr…
Unraveling the Temporal Importance of Community-scale Human Activity Features for Rapid Assessment of Flood Impacts
Faxi Yuan, Yang Yang, Qingchun Li +1
The objective of this research is to explore the temporal importance of community-scale human activity features for rapid assessment of flood impacts. Ultimate flood impact data, s…
Spatio-Temporal Graph Convolutional Networks for Road Network Inundation Status Prediction during Urban Flooding
Faxi Yuan, Yuanchang Xu, Qingchun Li +1
The objective of this study is to predict the near-future flooding status of road segments based on their own and adjacent road segments current status through the use of deep lear…
Revealing Critical Characteristics of Mobility Patterns in New York City during the Onset of COVID-19 Pandemic
Akhil Anil Rajput, Qingchun Li, Xinyu Gao +1
New York has become one of the worst-affected COVID-19 hotspots and a pandemic epicenter due to the ongoing crisis. This paper identifies the impact of the pandemic and the effecti…
Unraveling the Dynamic Importance of County-level Features in Trajectory of COVID-19
Qingchun Li, Yang Yang, Wangqiu Wang +6
The objective of this study was to investigate the importance of multiple county-level features in the trajectory of COVID-19. We examined feature importance across 2,787 counties…
Early Indicators of COVID-19 Spread Risk Using Digital Trace Data of Population Activities
Xinyu Gao, Chao Fan, Yang Yang +4
The spread of pandemics such as COVID-19 is strongly linked to human activities. The objective of this paper is to specify and examine early indicators of disease spread risk in ci…
Detecting Early-warning signals in Time Series of Visits to Points of Interests to Examine Population Response to COVID -19 Pandemic
Qingchun Li, Zhiyuan Tang, Natalie Coleman +1
The objective of this paper is to examine population response to COVID-19 and associated policy interventions through detecting early-warning signals in time series of visits to po…
Disparate Patterns of Movements and Visits to Points of Interests Located in Urban Hotspots across U.S. Metropolitan Cities during COVID-19
Qingchun Li, Liam Bessell, Xin Xiao +3
We examined the effect of social distancing on changes in visits to urban hotspot points of interest. Urban hotspots, such as central business districts, are gravity activity cente…
Effects of Population Co-location Reduction on Cross-county Transmission Risk of COVID-19 in the United States
Chao Fan, Sanghyeon Lee, Yang Yang +3
The rapid spread of COVID-19 in the United States has imposed a major threat to public health, the real economy, and human well-being. With the absence of effective vaccines, the p…