Heng Cai
Biographic Data
| ID | 3635502 |
|---|---|
| NAME | Heng Cai |
| GIVEN NAMES | Heng |
| FAMILY NAME | Cai |
| SIGNATURE | CAI H |
| AFFILIATIONS | Texas A&M University |
| ORCID | 0000-0001-6068-5150 |
| VERIFIED | Yes |
| TOTAL WORKS | 16 |
| TOTAL CITATIONS | 26 |
| AUTHOR COUNT | 16 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
From seismic signals to urban sensing
Rapid Disaster Response and Damage Estimation with Social Media and Pretrained Large Language Models
Understanding the disparate impacts of the 2021 Texas winter storm and power outages through mobile phone location data and nighttime light images
Prime
Deciphering spatial-temporal dynamics of flood exposure in the United States
Sensing the pulse of the pandemic
Social media offers a unique lens to observe large-scale, spatial-temporal patterns of users' reactions toward critical events. However, social media use varies across demographics, with younger users being more prevalent compared to older populations. This difference introduces biases in data representativeness, and analysis based on social media without proper adjustment will lead to overlooking the voices of digitally marginalized communities …
Learners’ motivation caught between the interplay of policy and practice
The past few decades have seen a boom in English-medium instruction (EMI) in Chinese universities. Despite growing research interest in EMI policy and practices in China, little is known about how students' motivation to study in the EMI programs is influenced by EMI policy and its implementation at the meso and micro levels. This study addresses this gap by examining an EMI program at a Chinese medical college. Through a survey of 118 students a…
Social media for emergency rescue
Algorithmic uncertainties in geolocating social media data for disaster management
The rapid development of information and communications technology has turned individuals into sensors, fostering the growth of human-generated geospatial big data. In disaster management, geospatial big data, mainly social media data, have opened new avenues for observing human responses to disasters in near real-time. Previous research relies on geographical information in geotags, content, and user profiles to locate social media messages. How…
VictimFinder
Economics over Risk
We analyzed the migration consideration factors of residents from the Mississippi River Delta in southern Louisiana, which is under the influence of rising sea levels, subsiding land, and increasing flood risks. Through the use of a telephone survey of 1,125 adult individuals in twenty-four parishes, we gathered the demographic data and flood risk experiences and perceptions of each respondent. The data were analyzed through descriptive statistic…
A synthesis of disaster resilience measurement methods and indices
Modeling the Dynamics of Community Resilience to Coastal Hazards Using a Bayesian Network
Studies on how variables of community resilience to natural hazards interact as a system that affects the final resilience (i.e., their dynamical linkages) have rarely been conducted. Bayesian network (BN), which represents the interdependencies among variables in a graph while expressing the uncertainty in the form of probability distributions, offers an effective way to investigate the interactions among different resilience components and addr…
Mining Twitter Data for Improved Understanding of Disaster Resilience
Coastal communities faced with multiple hazards have shown uneven responses and behaviors. These responses and behaviors could be better understood by analyzing real-time social media data through categorizing them into the three phases of the emergency management: preparedness, response, and recovery. This study analyzes the spatial–temporal patterns of Twitter activities during Hurricane Sandy, which struck the U.S. Northeast on 29 October 2012…
Changes in Exposure to Flood Hazards in the United States
This article conducts a national, county-based assessment of the changes in population and urban areas in high-risk flood zones from 2001 to 2011 in the contiguous United States. The U.S. Federal Emergency Management Agency's (FEMA) 100-year flood maps, land cover data, and census data were used to extract the proportion of developed (urban) land in flood zones by county at the two time points, and indexes of difference were calculated. Local Mor…
A cyberinfrastructure for community resilience assessment and visualization
Disaster resilience is a major societal challenge. Cartography and GIS can contribute substantially to this research area. This paper describes a cyberinfrastructure for disaster resilience assessment and visualization for all counties in the United States. Aided by the Application Programming Interface-enabled web mapping and component-oriented web tools, the cyberinfrastructure is designed to better serve the US communities with comprehensive r…
Mining Twitter Data for Improved Understanding of Disaster Resilience
Coastal communities faced with multiple hazards have shown uneven responses and behaviors. These responses and behaviors could be better understood by analyzing real-time social media data through categorizing them into the three phases of the emergency management: preparedness, response, and recovery. This study analyzes the spatial–temporal patterns of Twitter activities during Hurricane Sandy, which struck the U.S. Northeast on 29 October 2012…
Changes in Exposure to Flood Hazards in the United States
This article conducts a national, county-based assessment of the changes in population and urban areas in high-risk flood zones from 2001 to 2011 in the contiguous United States. The U.S. Federal Emergency Management Agency's (FEMA) 100-year flood maps, land cover data, and census data were used to extract the proportion of developed (urban) land in flood zones by county at the two time points, and indexes of difference were calculated. Local Mor…
Modeling the Dynamics of Community Resilience to Coastal Hazards Using a Bayesian Network
Studies on how variables of community resilience to natural hazards interact as a system that affects the final resilience (i.e., their dynamical linkages) have rarely been conducted. Bayesian network (BN), which represents the interdependencies among variables in a graph while expressing the uncertainty in the form of probability distributions, offers an effective way to investigate the interactions among different resilience components and addr…
A cyberinfrastructure for community resilience assessment and visualization
Disaster resilience is a major societal challenge. Cartography and GIS can contribute substantially to this research area. This paper describes a cyberinfrastructure for disaster resilience assessment and visualization for all counties in the United States. Aided by the Application Programming Interface-enabled web mapping and component-oriented web tools, the cyberinfrastructure is designed to better serve the US communities with comprehensive r…
Algorithmic uncertainties in geolocating social media data for disaster management
The rapid development of information and communications technology has turned individuals into sensors, fostering the growth of human-generated geospatial big data. In disaster management, geospatial big data, mainly social media data, have opened new avenues for observing human responses to disasters in near real-time. Previous research relies on geographical information in geotags, content, and user profiles to locate social media messages. How…
A cyberinfrastructure for community resilience assessment and visualization
Disaster resilience is a major societal challenge. Cartography and GIS can contribute substantially to this research area. This paper describes a cyberinfrastructure for disaster resilience assessment and visualization for all counties in the United States. Aided by the Application Programming Interface-enabled web mapping and component-oriented web tools, the cyberinfrastructure is designed to better serve the US communities with comprehensive r…
Changes in Exposure to Flood Hazards in the United States
This article conducts a national, county-based assessment of the changes in population and urban areas in high-risk flood zones from 2001 to 2011 in the contiguous United States. The U.S. Federal Emergency Management Agency's (FEMA) 100-year flood maps, land cover data, and census data were used to extract the proportion of developed (urban) land in flood zones by county at the two time points, and indexes of difference were calculated. Local Mor…
A synthesis of disaster resilience measurement methods and indices
Modeling the Dynamics of Community Resilience to Coastal Hazards Using a Bayesian Network
Studies on how variables of community resilience to natural hazards interact as a system that affects the final resilience (i.e., their dynamical linkages) have rarely been conducted. Bayesian network (BN), which represents the interdependencies among variables in a graph while expressing the uncertainty in the form of probability distributions, offers an effective way to investigate the interactions among different resilience components and addr…
Mining Twitter Data for Improved Understanding of Disaster Resilience
Coastal communities faced with multiple hazards have shown uneven responses and behaviors. These responses and behaviors could be better understood by analyzing real-time social media data through categorizing them into the three phases of the emergency management: preparedness, response, and recovery. This study analyzes the spatial–temporal patterns of Twitter activities during Hurricane Sandy, which struck the U.S. Northeast on 29 October 2012…
Economics over Risk
We analyzed the migration consideration factors of residents from the Mississippi River Delta in southern Louisiana, which is under the influence of rising sea levels, subsiding land, and increasing flood risks. Through the use of a telephone survey of 1,125 adult individuals in twenty-four parishes, we gathered the demographic data and flood risk experiences and perceptions of each respondent. The data were analyzed through descriptive statistic…
VictimFinder
Social media for emergency rescue
Algorithmic uncertainties in geolocating social media data for disaster management
The rapid development of information and communications technology has turned individuals into sensors, fostering the growth of human-generated geospatial big data. In disaster management, geospatial big data, mainly social media data, have opened new avenues for observing human responses to disasters in near real-time. Previous research relies on geographical information in geotags, content, and user profiles to locate social media messages. How…
Understanding the disparate impacts of the 2021 Texas winter storm and power outages through mobile phone location data and nighttime light images
Prime
Deciphering spatial-temporal dynamics of flood exposure in the United States
Sensing the pulse of the pandemic
Social media offers a unique lens to observe large-scale, spatial-temporal patterns of users' reactions toward critical events. However, social media use varies across demographics, with younger users being more prevalent compared to older populations. This difference introduces biases in data representativeness, and analysis based on social media without proper adjustment will lead to overlooking the voices of digitally marginalized communities …
Learners’ motivation caught between the interplay of policy and practice
The past few decades have seen a boom in English-medium instruction (EMI) in Chinese universities. Despite growing research interest in EMI policy and practices in China, little is known about how students' motivation to study in the EMI programs is influenced by EMI policy and its implementation at the meso and micro levels. This study addresses this gap by examining an EMI program at a Chinese medical college. Through a survey of 118 students a…
From seismic signals to urban sensing
Rapid Disaster Response and Damage Estimation with Social Media and Pretrained Large Language Models
Computer Science (12 works) · Disaster Management and Resilience (11 works) · Geography (10 works) · Flood Risk Assessment and Management (6 works) · Data science (5 works) · Social media (5 works) · World Wide Web (5 works) · Cartography (4 works) · Demography (4 works) · Environmental Science (4 works)