115 citations · 190 across the 11 of their papers we have counts for
11 papers
ML4EJ: Decoding the Role of Urban Features in Shaping Environmental Injustice Using Interpretable Machine Learning
Yu-Hsuan Ho, Zhewei Liu, Cheng-Chun Lee +1
Understanding the key factors shaping environmental hazard exposures and their associated environmental injustice issues is vital for formulating equitable policy measures. Traditi…
MaxFloodCast: Ensemble Machine Learning Model for Predicting Peak Inundation Depth And Decoding Influencing Features
Cheng-Chun Lee, Lipai Huang, Federico Antolini +4
Timely, accurate, and reliable information is essential for decision-makers, emergency managers, and infrastructure operators during flood events. This study demonstrates a propose…
ELEV-VISION: Automated Lowest Floor Elevation Estimation from Segmenting Street View Images
Yu-Hsuan Ho, Cheng-Chun Lee, Nicholas D. Diaz +2
We propose an automated lowest floor elevation (LFE) estimation algorithm based on computer vision techniques to leverage the latent information in street view images. Flood depth-…
Energy Inequality in Climate Hazards: Empirical Evidence of Social and Spatial Disparities in Managed and Hazard-Induced Power Outages
Natalie Coleman, Amir Esmalian, Cheng-Chun Lee +3
The energy sector in the United States is ever more vulnerable to extreme climatic hazards, leading to multiple hazard-induced and managed power outages. Utility companies reported…
Large-scale Building Damage Assessment using a Novel Hierarchical Transformer Architecture on Satellite Images
Navjot Kaur, Cheng-Chun Lee, Ali Mostafavi +1
This paper presents \dahitra, a novel deep-learning model with hierarchical transformers to classify building damages based on satellite images in the aftermath of natural disaster…
Roadmap Towards Responsible AI in Crisis Resilience Management
Cheng-Chun Lee, Tina Comes, Megan Finn +1
Novel data sensing and AI technologies are finding practical use in the analysis of crisis resilience, revealing the need to consider how responsible artificial intelligence (AI) p…
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 Community Formation in Response to Extreme Weather Events through Human Mobility Networks
Cheng-Chun Lee, Junwei Ma, Kai Yin +3
Community formation in socio-spatial human networks is one of the important mechanisms for mitigating hazard impacts of extreme weather events. Research is scarce regarding latent…
Specifying Evacuation Return and Home-switch Stability During Short-term Disaster Recovery Using Location-based Data
Cheng-Chun Lee, Charles Chou, Ali Mostafavi
The objectives of this study are: (1) to specify evacuation return and home-switch stability as two critical milestones of short-term recovery during and in the aftermath of disast…
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…
Community-scale Big Data Reveals Disparate Impacts of the Texas Winter Storm of 2021 and its Managed Power Outage
Cheng-Chun Lee, Mikel Maron, Ali Mostafavi
Aggregated community-scale data could be harnessed to allow insights into the disparate impacts of managed power outages, burst pipes, and food inaccessibility during extreme weath…