Our new paper identifying effective hurricane risk communication tools was published in the International Journal of Disaster Risk Reduction. Below please find the abstract:

"Coastal regions such as the U.S. Atlantic and Gulf Coasts are highly vulnerable to extreme coastal hazards such as tropical cyclones and major hurricanes. The effects of these hazards pose a threat now and are expected to increase in the future, which highlights the need for coastal communities to receive and understand information regarding risks involved with these hazards. Through this study, we identify points of improvement in the tools used to communicate the short and long-term risk associated with hurricane hazards through three surveys in Mobile, AL, Savannah, GA, and Houston TX. These surveys identify public response to hurricane descriptions, Cone of Uncertainty graphics, and long-term trend graphics. Analysis of trends in responses to these communication tools identifies relationships between risk perceptions and existing factors in each study location. Further, public response to these tools is identified and analyzed using structural equation models for each location with a “response” latent variable containing information from endogenous variables in the survey. Response was measured as action intent, concern for the scenario, reported evacuation likelihood, and interpretation of long-term trends. We identify points of improvement for all three communication tools to aid in public comprehension of the information provided as well as to increase response to hurricane hazards by more effectively communicating risk information. These would help to improve comprehension and increase different responses to tropical storm and hurricane damage from high winds and storm surge with the intent to improve resident response to hazards along the U.S. Atlantic and Gulf Coasts."

Our paper using participatory GIS to measure accessibility of people with movement disabilities has been published in Applied Geography. Below please find the abstract:

"Although evaluation of the accessibility of people with disability (PWDs) is necessary to design effective transportation policy measures to ensure better mobility for PWDs, little empirical research are available on this subject. This study thus aims to address this gap by developing a methodological framework and applying this framework to assessing the accessibility of earthquake evacuation routes for people with movement-related disabilities (PMDs), one type of PWDs, in the city of Dhaka, Bangladesh. Specifically, this comprehensive accessibility index is composed of four components including accessibility from home to shelter, perceived accessibility of evacuation route, accessibility of entrance of the shelter, perceived accessibility of internal circular space and entrance of the residential building. Participatory GIS approach is employed in the data collection 455 PMDs were surveyed from 13 wards of Dhaka. Accessibility of each considered parameter and the overall indicator are poor in most cases. 45.2% of the wards are found to have relatively poor conditions of overall accessibility during evacuation. Relations of various accessibility components with socio-economic factors and level of disability are examined as well. PMDs with higher levels of disabilities and older PMDs perceive lower accessibilities of evacuation routes, circulation space, and entrance gate of residence, while male and more educated PMDs perceive circular space and entrance gate of residence to be more accessible."

Our new paper examining the influence of carbon dependency, social capital, and political orientation on American public response to climate change has been published in Society & Natural Resources. Below is the abstract:

"Climate change is one major challenge that has brought substantial costs to the United States. To implement mitigation measures and gain public support, it is critical to understand Americans’ attitudes toward this issue. Our study investigates how carbon dependency, social capital, and political orientation influence public response to climate change by perceiving its threat, changing behaviors, and supporting policies. We first build an integrative paradigm to explore the theoretical connections. Next, we employ data from different sources to measure these key concepts at individual and state levels and then estimate the relationships empirically. Multilevel regression results show that carbon dependency inhibits public response while social capital enhances such response. Democrats and liberals are motivated to respond and residents of Democratic Party controlled states are also more likely to believe in climate change and perceive the risk than their counterparts. These factors can be leveraged to mobilize public engagement in climate activism."

Our paper analyzing how climate extremes along with COVID-19 impact residents' sentiments in water pollution complaints is published in npj Clean Water. Below please find the abstract:

"The COVID-19 pandemic and associated prevention policies can directly or indirectly alter the sentiment of individuals while registering water pollution complaints, but observational evidence remains limited. Here, we conducted a sentiment analysis on over 10,000 water pollution complaints from residents in Alabama, USA (2012–2021) to better understand how and to what extent COVID-19 has altered emotion (polarity score-based) and attitude (subjectivity) of water pollution complaints. We found that the 2017 state-wise drought significantly increased the percentage of negative water pollution complaints by +35%, with no significant alternation in attitude before the COVID-19 pandemic. Since COVID-19, the percentage of negative and subjective water pollution complaints significantly decreased and increased by −30 and +20%, respectively, and these sentiment alternations were maintained by 2021. This study provides a new direction for environmental governance and management, requiring a timely response to changes in the public’s emotions and attitudes during the next climate extremes and pandemics."

My research group Hazards, Vulnerability, and Risk Decision Making at the Department of Geography at the University of Alabama is accepting applications for a Ph.D student with assistantship who will start in Fall, 2023. The assistantship provides a stipend plus tuition remission. The successful applicant will work with me and will be involved in projects focused on the intersection of water hazards, community vulnerability, and risk decision making.
 
Qualified candidates should have a Master’s degree in Geography, Environmental Studies/Sciences, Planning or a related discipline. Candidates should have a strong interest in the intersection of social and physical dimensions of hazards and be eager to work in an interdisciplinary environment. Experience in geographic information systems (GIS), remote sensing, quantitative data analysis are desired. Strong oral and written communication skills are required.
 
For more information about this assistantship, please contact me at wshao1@ua.edu as soon as possible. Please include a copy of your CV, unofficial academic transcripts, and a brief personal statement that highlights skills relevant to the position.
 
For more information about the department, please see https://geography.ua.edu/. 

Our new paper titled "Toward reduction of detrimental effects of hurricanes using a social media data analytic approach: How climate change is perceived?" has been published in Climate Risk Management. Below please find the abstract:

"​During natural disasters, there is a noticeably increased use of social media sites such as Twitter. Substantial research on social media data use during disasters has been conducted in the past decade since various social media platforms have emerged and gained popularity. This research highlights a thorough examination of the textual content of users’ posts shared on Twitter across the 48 contiguous U.S. states (CONUS) during hurricanes Harvey (2017) and Dorian (2019). We processed and analyzed 35 million tweets by classifying them into the main topics of concern discussed on Twitter over the CONUS. Sentiment analysis, topic modeling, and topic classification are a few of the Artificial Intelligence techniques from Natural Language Processing (NLP) that we employed in this work to analyze the Twitter data. Applying the NLP techniques on this large volume of data, made it possible to classify the tweet content into distinct categories in order to reveal valuable information on social response to hurricanes and assist crisis management agencies and disaster responders during and post disasters. Furthermore, this study offers helpful insights on the way climate change is discussed on Twitter before, during and after hurricane Harvey and Dorian. The outcome of this study uncovers detailed information on social response to hurricanes which benefits disaster managers and responders in reducing the detrimental effects of such extreme events and enhancing community readiness when these events occur."