Liang Mao is an assistant professor in the Department of Geology in the College of Liberal Arts and Sciences. Liang's research aims to offer better understanding on the human-disease system with geospatial science approaches and technologies.
Areas of Expertise (3)
Agent-Based Modeling and Simulation
Geospatial Network Analysis
Spatial Accessibility and Disparities
Agent-based Modeling to Evaluate Human–Environment Interactions in Community Flood Risk MitigationRisk Analysis
Yu Han, et. al
This article deals with household-level flood risk mitigation. We present an agent-based modeling framework to simulate the mechanism of natural hazard and human interactions, to allow evaluation of community flood risk and to predict various adaptation outcomes. The framework considers each household as an autonomous, yet socially connected, agent. A Beta–Bernoulli Bayesian learning model is first applied to measure changes of agents’ risk perceptions in response to stochastic storm surges.
A data driven agent-based model that recommends non-pharmaceutical interventions to suppress Coronavirus disease 2019 resurgence in megacitiesJournal of The Royal Society Interface
Ling Yin, et. al
Before herd immunity against Coronavirus disease 2019 (COVID-19) is achieved by mass vaccination, science-based guidelines for non-pharmaceutical interventions are urgently needed to reopen megacities. This study integrated massive mobile phone tracking records, census data and building characteristics into a spatially explicit agent-based model to simulate COVID-19 spread among 11.2 million individuals living in Shenzhen City, China.
Determinants of travel mode choice for seeking healthcare: A comparison between elderly and non-elderly patientsJournal of Transport Geography
Fangye Du, et. al
People's travel mode choices can vary significantly by age group due to different influencing factors, but relevant research on health-related travel is scarce. In this study, we explored and compared the determinants of travel mode choice for healthcare-seeking non-elderly and elderly patients in Beijing, China. A multinomial logit model was used to analyze data from a recent healthcare-seeking behavior survey.
Internet of people enabled framework for evaluating performance loss and resilience of urban critical infrastructuresSafety Science
Faxi Yuan, et. al
Critical infrastructures (CIs) such as road networks play a critical role in transporting affected people to hospitals and shelters during disasters. Timely evaluation of road networks’ performance loss and resilience enables emergency management agencies (EMAs) to make quick and optimized decisions on resource allocation to critical road segments and bridges.