8 citations · 27 across the 10 of their papers we have counts for
10 papers
Data-driven Tracking of the Bounce-back Path after Disasters: Critical Milestones of Population Activity Recovery and Their Spatial Inequality
Yuqin Jiang, Faxi Yuan, Hamed Farahmand +3
The ability to measure and track the speed and trajectory of a community's post-disaster recovery is essential to inform resource allocation and prioritization. The current survey-…
Unveiling Vulnerability and Inequality in Disrupted Access to Dialysis Centers During Urban Flooding
Faxi Yuan, Hamed Farahmand, Russell Blessing +2
Despite the criticality of dialysis facilities, limited knowledge exists regarding the extent and inequality of disrupted access caused by weather events. This study uses mobility…
Quantitative Measures for Integrating Resilience into Transportation Planning Practice: Study in Texas
Cheng-Chun Lee, Akhil Rajput, Chia-Wei Hsu +10
The objective of this study is to propose a system-level framework with quantitative measures to assess the resilience of road networks. The framework proposed in this paper can he…
Characterizing Equitable Access to Grocery Stores During Disasters Using Location-based Data
Amir Esmalian, Natalie Coleman, Faxi Yuan +2
Natural hazards cause disruptions in access to critical facilities, such as grocery stores, impeding residents ability to prepare for and cope with hardships during the disaster an…
Smart Flood Resilience: Harnessing Community-Scale Big Data for Predictive Flood Risk Monitoring, Rapid Impact Assessment, and Situational Awareness
Faxi Yuan, Chao Fan, Hamed Farahmand +7
Smart resilience is the beneficial result of the collision course of the fields of data science and urban resilience to flooding. The objective of this study is to propose and demo…
Predicting Road Flooding Risk with Machine Learning Approaches Using Crowdsourced Reports and Fine-grained Traffic Data
Faxi Yuan, William Mobley, Hamed Farahmand +5
The objective of this study is to predict road flooding risks based on topographic, hydrologic, and temporal precipitation features using machine learning models. Predictive flood…
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…
Unveiling Spatial Patterns of Disaster Impacts and Recovery Using Credit Card Transaction Variances
Faxi Yuan, Amir Esmalian, Bora Oztekin +1
The objective of this study is to examine spatial patterns of impacts and recovery of communities based on variances in credit card transactions. Such variances could capture the c…
Quantifying Community Resilience Based on Fluctuations in Visits to Point-of-Interest from Digital Trace Data
Cristian Podesta, Natalie Coleman, Amir Esmalian +2
This study aims to quantify community resilience based on fluctuations in the visits to various Point-of-Interest (POIs) locations. Visit to POIs is an essential indicator of human…