Zhenlong Li
Dados Biográficos
| ID | 3584313 |
|---|---|
| NOME | Zhenlong Li |
| PRENOMES | Zhenlong |
| SOBRENOME | Li |
| ASSINATURA | LI Z |
| AFILIAÇÕES | University of South Carolina |
| ORCID | 0000-0002-8938-5466 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 50 |
| TOTAL DE CITAÇÕES | 64 |
| TOTAL COMO AUTOR | 50 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2017 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 5 |
GeoAI and AI Copilot
Generative artificial intelligence (GenAI) is transforming various domains, including geographic information systems (GIS), by enabling AI copilots that assist users in performing geospatial tasks through natural language interaction. These systems automate geoprocessing tasks, generate code, and support map creation. Examples include GIS Copilot, ArcGIS AI Assistant, and Earth Copilot. Key benefits include enhanced accessibility to GIS, increase…
A directional latent demand index for city links
Current public transit planning often optimizes services based on realized ridership, which can systematically miss suppressed or unmet travel needs and thereby reinforce transportation inequity. This demand–supply misalignment often manifests as directional asymmetries, such as underserved reverse commutes, that traditional place-based metrics fail to capture. To address this gap, this study proposes a directional Latent Demand Index, a novel me…
Do We Care Enough About Child Maltreatment?—Analyzing Social Media Discourse on Child Maltreatment in the United States
Sentiment expressions related to child maltreatment (CM) in public discourse are influenced by demographic, economic, and cultural factors and individual characteristics. Using 188,429 geotagged CM-related tweets during 2018–2022, we explored public sentiment expression about CM across the contiguous U.S. We applied multiscale geographically weighted regression (MGWR) to examine how contextual factors relate to the percentage of CM-related tweets…
County-Level New HIV Diagnoses, Social Determinants of Health, and Residential Segregation by U.S. Region 2013 to 2023
Health disparities persist along the HIV care continuum. As new HIV diagnoses are a key indicator of the HIV epidemic, we aimed to assess associations of the social determinants of health (SDOH; non-medical factors that are related to health outcomes) and residential segregation, as a proxy for systemic racism, with new HIV diagnosis rates across the major regions of the United States. Publicly available county-level data (i.e., 2013–2023) from a…
Exponential distance decay in urban park visitation
Urban parks are essential infrastructure for public health and environmental resilience, yet systematic comparative evidence on how distance constrains recreational access across metropolitan areas remains scarce. This study analyzes 60 million park visits across 20 U.S. metropolitan areas to establish mathematical relationships governing park visitation and their determinants. Park visitation universally follows exponential decay (V = αe -βd ) r…
Comparing connected vehicle and mobile phone data for urban mobility analysis
Connected vehicle (CV) data are increasingly available and widely used in transportation engineering for traffic monitoring, safety analysis, and infrastructure planning. However, the representativeness of CV data in general urban mobility analysis remains underexplored, raising concerns about potential biases between observed mobility patterns in CV data and actual travel behaviors, particularly across different demographic and socioeconomic gro…
Spatial Associations of Anti-Asian Hate on Social Media in the USA During Covid-19
Chlamydia and gonorrhea incidence and residential segregation
This study found that residential segregation was associated with race-specific differences in chlamydia and gonorrhea transmission, especially during the COVID-19 pandemic.How this study might affect research, practice or policy: Study findings suggest that interventions aiming to reduce chlamydia and gonorrhea incidence rates in the United States should also include intervention activities that address adversities associated with residential se…
Examining Racial Discrimination Index and Black-Years of Potential Life Lost (YPLL) in South Carolina
Digital racial discrimination was highly associated with Black YPLL rates, confirming the importance of racial discrimination in health disparity, especially premature deaths. Addressing explicit and implicit racism in highly affected counties is crucial for reducing persistent health inequities and promoting equity in communities
Nationwide analysis of the association between nature park visits and adult asthma risk in urbanized neighborhoods
Impacts of Residential Segregation and Comorbidity on Racial Disparities in Acute Care Utilization
A Sensor-Based Simulation Method for Spatiotemporal Event Detection
Human movements in urban areas are essential to understand human–environment interactions. However, activities and associated movements are full of uncertainties due to the complexity of a city. In this paper, we propose a novel sensor-based approach for spatiotemporal event detection based on the Discrete Empirical Interpolation Method. Specifically, we first identify the key locations, defined as “sensors”, which have the strongest correlation …
Exploring flood mitigation governance by estimating first-floor elevation via deep learning and google street view in coastal Texas
Flood mitigation governance is critical for coastal regions where flooding has caused considerable damage. Raising the First-Floor Elevation (FFE) above the base flood elevation (BFE) is an effective mitigation measure for buildings with a high risk of flooding. In the U.S., measuring FFE is necessary to obtain an Elevation Certificate (E.C.) for the National Flood Insurance Program (NFIP) and has traditionally required labor-consuming field surv…
Association of Racial Residential Segregation and Other Social Determinants of Health with HIV Late Presentation
Understanding social determinants of HIV late presentation with advanced disease (LPWA) beyond individual-level factors could help decrease LPWA and improve population-level HIV outcomes. This study aimed to examine county-level social determinants of health (SDOH) with HIV late presentation. We aggregated datasets for analysis by linking statewide HIV diagnosis data from the South Carolina (SC) Enhanced HIV/AIDS Reporting System and multiple soc…
Multi-level Factors Associated with HIV Late Presentation with Advanced Disease and Delay Time of Diagnosis in South Carolina, 2005–2019
This study explored individual- and county-level risk factors of late presentation with advanced disease (LPAD) among people with HIV (PWH) and their longer delay time from infection to diagnosis in South Carolina (SC), using SC statewide Enhanced HIV/AIDS Reporting System (eHARS). LPAD was defined as having an AIDS diagnosis within three months of initial HIV diagnosis, and delay time from HIV infection to diagnosis was estimated using CD4 deple…
Big data insights into urban park use in the pandemic
From neighborhood contexts to human behaviors
Structural Racism and HIV Pre-exposure Prophylaxis Use in the Nationwide US
Background Structural racism contributes to geographical inequalities in pre-exposure prophylaxis (PrEP) coverage in the United States (US). This study aims to investigate county-level variability in PrEP utilization across diverse dimensions of structural racism. Methods The 2013-2021 nationwide county-level PrEP rate and PrEP-to-need ratio (PNR) data were retrieved from AIDSVu. PrEP rate was defined as the number of PrEP users per 100,000 popul…
Moderation effect of community health on the relationship between racial/ethnic residential segregation and HIV viral suppression in South Carolina
Background: Viral suppression is the ultimate goal of the HIV treatment cascade and a primary endpoint of antiretroviral therapy. Empirical evidence found racial/ethnic disparities in viral suppression among people living with HIV (PWH), but the evidence of the relationship between racial/ethnic residential segregation and place-based viral suppression is scarce. Further exploring potential structural moderators in this relationship has substanti…
Rural-Urban Disparities in Hospital Admissions and Mortality Among Patients with Covid-19
A data-driven investigation on park visitation and income mixing of visitors in New York City
It is crucial to understand the current pattern of urban park visitation to achieve environmental justice. Current discussions of environmental equity of parks mainly focus on the inequality provision measured by park accessibility, park area, park quality, and park congestion, ignoring the inequity of social benefits through interactions among mixed-income groups. Based on fine-grained mobile phone location data at the census block group level i…
Exploring large-scale spatial distribution of fear of crime by integrating small sample surveys and massive street view images
A tremendous amount of research use questionnaires to obtain individuals’ fear of crime and aggregate it to the neighborhood level to measure the spatial distribution of fear of crime. However, the cost of using questionnaires to measure the large-scale spatial distribution of fear of crime is high. The built environment is known to influence people’s perceptions, including fear of crime. This study develops a machine learning model to link built…
Understanding social risk factors of county-level disparities in Covid-19 tests per confirmed case in South Carolina using statewide electronic health records data
County-level disparities in CTPC and their predictors are dynamic across the pandemic. These results highlight the systematic inequalities in COVID-19 testing resources and accessibility, especially in the early stage of the pandemic. Counties with greater social vulnerability and those with fewer health care resources should be paid extra attention in the early and later phases, respectively. The current study provided empirical evidence for pub…
The Impacts of HIV-Related Service Interruptions During the Covid-19 Pandemic
Place Visitation Data Reveals the Geographic and Racial Disparities of Covid-19 Impact on HIV Service Utilization in the Deep South
Understanding demographic and socioeconomic biases of geotagged Twitter users at the county level
Massive social media data produced from microblog platforms provide a new data source for studying human dynamics at an unprecedented scale. Meanwhile, population bias in geotagged Twitter users is widely recognized. Understanding the demographic and socioeconomic biases of Twitter users is critical for making reliable inferences on the attitudes and behaviors of the population. However, the existing global models cannot capture the regional vari…
Delineating and modeling activity space using geotagged social media data
It has become increasingly important in spatial equity studies to understand activity spaces – where people conduct regular out-of-home activities. Big data can advance the identification of activity spaces and the understanding of spatial equity. Using the Los Angeles metropolitan area for the case study, this paper employs geotagged Twitter data to delineate activity spaces with two spatial measures: first, the average distance between users’ h…
Topic modeling and sentiment analysis of global climate change tweets
A novel approach to leveraging social media for rapid flood mapping
Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the st…
Black Businesses Matter
Black communities in the United States have been disproportionately affected by the COVID-19 pandemic; however, few empirical studies have been conducted to examine the conditions of Black-owned businesses in the United States during this challenging time. In this article, we assess the circumstances of Black-owned restaurants during the entire year of 2020 through a longitudinal quantitative analysis of restaurant patronage. Using multiple sourc…
A graph-based approach to detecting tourist movement patterns using social media data
Understanding the characteristics of tourist movement is essential for tourist behavior studies since the characteristics underpin how the tourist industry management selects strategies for attraction planning to commercial product development. However, conventional tourism research methods are not either scalable or cost-efficient to discover underlying movement patterns due to the massive datasets. With advances in information and communication…
Using geotagged tweets to track population movements to and from Puerto Rico after Hurricane Maria
Social Network, Activity Space, Sentiment, and Evacuation
Hurricanes are one of the most common natural hazards in the United States. To reduce fatalities and economic losses, coastal states and counties take protective actions, including sheltering in place and evacuation away from the coast. Not everyone adheres to hurricane evacuation warnings or orders. In reality, evacuation rates are far less than 100 percent and are estimated using posthurricane questionnaire surveys to residents in the affected …
Big data insights into urban park use in the pandemic
Association between immigrant concentration and mental health service utilization in the United States over time
Urban-regional disparities in mental health signals in Australia during the Covid-19 pandemic
This study establishes a novel empirical framework using machine learning techniques to measure the urban-regional disparity of the public’s mental health signals in Australia during the pandemic, and to examine the interrelationships amongst mental health, demographic and socioeconomic profiles of neighbourhoods, health risks and healthcare access. Our results show that the public’s mental health signals in capital cities were better than those …
Introducing Twitter Daily Estimates of Residents and Non-Residents at the County Level
The study of migrations and mobility has historically been severely limited by the absence of reliable data or the temporal sparsity of available data. Using geospatial digital trace data, the study of population movements can be much more precisely and dynamically measured. Our research seeks to develop a near real-time (one-day lag) Twitter census that gives a more temporally granular picture of local and non-local population at the county leve…
Social media data as a proxy for hourly fine-scale electric power consumption estimation
Accurate forecasting of electric demand is essential for the operation of modern power system. Inaccurate load forecasting will considerably affect the power grid efficiency. Forecasting the electric demand for a small area, such as a building, has long been a well-known challenge. In this research, we examined the association between geotagged tweets and hourly electric consumption at a fine scale. All available geotagged tweets and electric met…
A novel approach to leveraging social media for rapid flood mapping
Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the st…
A graph-based approach to detecting tourist movement patterns using social media data
Understanding the characteristics of tourist movement is essential for tourist behavior studies since the characteristics underpin how the tourist industry management selects strategies for attraction planning to commercial product development. However, conventional tourism research methods are not either scalable or cost-efficient to discover underlying movement patterns due to the massive datasets. With advances in information and communication…
Understanding demographic and socioeconomic biases of geotagged Twitter users at the county level
Massive social media data produced from microblog platforms provide a new data source for studying human dynamics at an unprecedented scale. Meanwhile, population bias in geotagged Twitter users is widely recognized. Understanding the demographic and socioeconomic biases of Twitter users is critical for making reliable inferences on the attitudes and behaviors of the population. However, the existing global models cannot capture the regional vari…
Social media data as a proxy for hourly fine-scale electric power consumption estimation
Accurate forecasting of electric demand is essential for the operation of modern power system. Inaccurate load forecasting will considerably affect the power grid efficiency. Forecasting the electric demand for a small area, such as a building, has long been a well-known challenge. In this research, we examined the association between geotagged tweets and hourly electric consumption at a fine scale. All available geotagged tweets and electric met…
Topic modeling and sentiment analysis of global climate change tweets
Social Network, Activity Space, Sentiment, and Evacuation
Hurricanes are one of the most common natural hazards in the United States. To reduce fatalities and economic losses, coastal states and counties take protective actions, including sheltering in place and evacuation away from the coast. Not everyone adheres to hurricane evacuation warnings or orders. In reality, evacuation rates are far less than 100 percent and are estimated using posthurricane questionnaire surveys to residents in the affected …
Evacuation Departure Timing during Hurricane Matthew
This study investigates evacuation behaviors associated with Hurricane Matthew in October of 2016. It assesses factors influencing evacuation decisions and evacuation departure times for Florida, Georgia, and South Carolina from an online survey of respondents. Approximately 62% of the Florida sample, 77% of the Georgia sample, and 67% of the South Carolina sample evacuated. Logistic regression analysis of the departures in the overall time perio…
Time-Series Clustering for Home Dwell Time during Covid-19
In this study, we investigate the potential driving factors that lead to the disparity in the time-series of home dwell time in a data-driven manner, aiming to provide fundamental knowledge that benefits policy-making for better mitigation strategies of future pandemics. Taking Metro Atlanta as a study case, we perform a trend-driven analysis by conducting Kmeans time-series clustering using fine-grained home dwell time records from SafeGraph. Fu…
Introduction to Big Data Computing for Geospatial Applications
The convergence of big data and geospatial computing has brought challenges and opportunities to GIScience with regards to geospatial data management, processing, analysis, modeling, and visualization. This special issue highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates the opportunities for using big data for …
Prototyping a Social Media Flooding Photo Screening System Based on Deep Learning
This article aims to implement a prototype screening system to identify flooding-related photos from social media. These photos, associated with their geographic locations, can provide free, timely, and reliable visual information about flood events to the decision-makers. This screening system, designed for application to social media images, includes several key modules: tweet/image downloading, flooding photo detection, and a WebGIS applicatio…
Bridging Twitter and Survey Data for Evacuation Assessment of Hurricane Matthew and Hurricane Irma
Evacuations are the most effective protective strategy adopted to minimize the deadly threat of an incoming hurricane. The study of evacuations has a long history in the United States, and the scientific community has acquired an in-depth understanding of the associated processes. However, there are limitations in the traditional methods of studying evacuation behavior, such as survey questionnaires and traffic counts, which sometimes fail to eff…
Disparity in HIV Service Interruption in the Outbreak of Covid-19 in South Carolina
Delineating and modeling activity space using geotagged social media data
It has become increasingly important in spatial equity studies to understand activity spaces – where people conduct regular out-of-home activities. Big data can advance the identification of activity spaces and the understanding of spatial equity. Using the Los Angeles metropolitan area for the case study, this paper employs geotagged Twitter data to delineate activity spaces with two spatial measures: first, the average distance between users’ h…
Using geotagged tweets to track population movements to and from Puerto Rico after Hurricane Maria
Spatiotemporal Patterns of Human Mobility and Its Association with Land Use Types during Covid-19 in New York City
The novel coronavirus disease (COVID-19) pandemic has impacted every facet of society. One of the non-pharmacological measures to contain the COVID-19 infection is social distancing. Federal, state, and local governments have placed multiple executive orders for human mobility reduction to slow down the spread of COVID-19. This paper uses geotagged tweets data to reveal the spatiotemporal human mobility patterns during this COVID-19 pandemic in N…
Temporal Geospatial Analysis of Covid-19 Pre-Infection Determinants of Risk in South Carolina
Disparities and their geospatial patterns exist in morbidity and mortality of COVID-19 patients. When it comes to the infection rate, there is a dearth of research with respect to the disparity structure, its geospatial characteristics, and the pre-infection determinants of risk (PIDRs). This work aimed to assess the temporal-geospatial associations between PIDRs and COVID-19 infection at the county level in South Carolina. We used the spatial er…
Introducing Twitter Daily Estimates of Residents and Non-Residents at the County Level
The study of migrations and mobility has historically been severely limited by the absence of reliable data or the temporal sparsity of available data. Using geospatial digital trace data, the study of population movements can be much more precisely and dynamically measured. Our research seeks to develop a near real-time (one-day lag) Twitter census that gives a more temporally granular picture of local and non-local population at the county leve…
Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection
Deep learning techniques are increasingly being recognized as effective image classifiers. Aside from their successful performance in past studies, the accuracies have varied in complex environments, in comparison with the popularly of applied machine learning classifiers. This study seeks to explore the feasibility of using a U-Net deep learning architecture to classify bi-temporal, high-resolution, county-scale aerial images to determine the sp…
The times, they are a-changin’
INTRODUCTION: Widespread problems of psychological distress have been observed in many countries following the outbreak of COVID-19, including Australia. What is lacking from current scholarship is a national-scale assessment that tracks the shifts in mental health during the pandemic timeline and across geographic contexts. METHODS: Drawing on 244 406 geotagged tweets in Australia from 1 January 2020 to 31 May 2021, we employed machine learning …
Converting street view images to land cover maps for metric mapping
Investigating the relationships between concentrated disadvantage, place connectivity, and Covid-19 fatality in the United States over time
Populations living in counties with both high concentrated disadvantage and high place connectivity may be at risk of a higher COVID-19 fatality. Greater COVID-19 fatality that occurs in concentrated disadvantaged counties may be partially due to higher human movement through place connectivity. In response to COVID-19 and other future infectious disease outbreaks, policymakers are encouraged to take advantage of historical disadvantage and place…
Urban-regional disparities in mental health signals in Australia during the Covid-19 pandemic
This study establishes a novel empirical framework using machine learning techniques to measure the urban-regional disparity of the public’s mental health signals in Australia during the pandemic, and to examine the interrelationships amongst mental health, demographic and socioeconomic profiles of neighbourhoods, health risks and healthcare access. Our results show that the public’s mental health signals in capital cities were better than those …
The promise of excess mobility analysis
Human mobility studies have become increasingly important and diverse in the past decade with the support of social media big data that enables human mobility to be measured in a harmonized and rapid manner. However, what is less explored in the current scholarship is episodic mobility as a special type of human mobility defined as the abnormal mobility triggered by episodic events excess to the normal range of mobility at large. Drawing on a lar…
Moderation effect of community health on the relationship between racial/ethnic residential segregation and HIV viral suppression in South Carolina
Background: Viral suppression is the ultimate goal of the HIV treatment cascade and a primary endpoint of antiretroviral therapy. Empirical evidence found racial/ethnic disparities in viral suppression among people living with HIV (PWH), but the evidence of the relationship between racial/ethnic residential segregation and place-based viral suppression is scarce. Further exploring potential structural moderators in this relationship has substanti…
Rural-Urban Disparities in Hospital Admissions and Mortality Among Patients with Covid-19
Geography (34 obras) · Medicine (22 obras) · Computer Science (20 obras) · Demography (19 obras) · Public health (15 obras) · Sociology (15 obras) · Demography (14 obras) · Cartography (13 obras) · Environmental health (13 obras) · Human Mobility and Location-Based Analysis (13 obras)