Zhenlong Li

Zhenlong Li
University of South Carolina | USC · Department of Geography

Ph.D.

About

176
Publications
69,660
Reads
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3,388
Citations
Citations since 2016
136 Research Items
3135 Citations
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Introduction
Dr. Zhenlong Li conducts interdisciplinary research on geospatial big data analytics, high-performance spatial computing and geospatial Cyberinfrastructure/CyberGIS within the area of data and computational intensive GIScience. By synthesizing advanced computing technologies, geospatial methods and spatiotemporal principles, Li's research aims to advance knowledge discovery and decision making to support domain applications including disaster management, climate change, human mobilities, and public health. More information about Dr. Li's research can be found at his lab website: http://gis.cas.sc.edu/gibd
Additional affiliations
August 2020 - present
University of South Carolina
Position
  • Professor (Associate)
August 2015 - August 2020
University of South Carolina
Position
  • Professor (Assistant)
September 2012 - May 2015
George Mason University
Position
  • Graduate Research and Teaching Assistant
Education
September 2012 - May 2015
George Mason University
Field of study
  • GIScience
September 2008 - January 2010
George Mason University
Field of study
  • GIScience and Earth Science
September 2002 - June 2006
Wuhan University
Field of study
  • GIS and Remote Sensing

Publications

Publications (176)
Article
Full-text available
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 peopl...
Article
Full-text available
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 mix...
Preprint
Full-text available
The COVID-19 pandemic has imposed catastrophic impacts on the restaurant industry as a crucial socioeconomic sector that contributes immensely to the global economy. However, what remains incomplete is our quantitative understanding of how the restaurant industry was recovered from COVID-19 in terms of restaurant visitations and revenue, customers'...
Preprint
Full-text available
BACKGROUND Suicide has been particularly concerning in the United States (US), but the risk assessment has been challenging because of its dependence on psychometric evaluations at the clinics. Growing attention has been paid to the role of social media since existing literature indicates that social media users disclose their suicide ideation and...
Article
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Black communities in the U.S. 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 U.S. during this challenging time. In this paper, we assess the circumstances of Black-owned restaurants during the entire year of 2020 through a...
Article
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Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various persp...
Preprint
Full-text available
Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility data has been an emerging data source to reveal fine-grained human mobility, which can be used to estimate the intensity of physical contact surrounding different locations. Our study applied smartphone mobility data to simulate the second wave spreading of COVID-1...
Preprint
Full-text available
Human movements in urban areas are essential for understanding the human-environment interactions. However, activities and associated movements are full of uncertainties due to the complexity of a city. In this paper, we propose an optimal sensors-based simulation method for spatiotemporal event detection using human activity signals derived from t...
Article
Full-text available
Social media analysis provides an alternate approach to monitoring and understanding risk perceptions regarding COVID‐19 over time. Our current understandings of risk perceptions regarding COVID‐19 do not disentangle the three dimensions of risk perceptions (perceived susceptibility, perceived severity, and negative emotion) as the pandemic has evo...
Article
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Despite ongoing efforts to improve childhood vaccination coverage, including in hard-to-reach and hard-to-vaccinate communities, many children in sub-Saharan Africa (SSA) remain unvaccinated. Considering recent goals set by the Immunization Agenda 2030 (IA2030), including reducing the number of zero-dose children by half, research that goes beyond...
Article
Full-text available
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...
Preprint
Full-text available
Concentrated disadvantaged areas have been disproportionately affected by COVID-19 outbreak in the United States (US). Meanwhile, highly connected areas may contribute to higher human movement, leading to higher COVID-19 cases and deaths. This study examined whether place connectivity moderated the association between concentrated disadvantage and...
Article
Population mobility and aging at local areas contributed to the geospatial disparities in the coronavirus disease 2019 (COVID-19) transmission among 418 counties in the Deep South. In predicting the incidence of COVID-19, a significant interaction was found between mobility and the proportion of older adults. Effective disease control measures shou...
Article
Full-text available
This study aims to investigate the impacts of shallow flood spreading on vegetation density using a time-series collection of Landsat images spanning 2012-2020. To do this, Support Vector Machine (SVM), Random Forest (RF), Classification and Regression tree (CART) and Deep Learning Convolutional Neural Network (DL-CNN) algorithms were employed for...
Article
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In this paper, we aim to compare the suitability of Sentinel-2 and Landsat 8 OLI images for detecting and mapping soil salinity distribution (SSD) using a deep learning convolutional neural network (DL-CNN) approach. We first identified and selected six SSD predisposing variables to train the models. These variables are the normalized difference ve...
Article
Full-text available
In this paper, we aim to compare the suitability of Sentinel-2 and Landsat 8 OLI images for detecting and mapping soil salinity distribution (SSD) using a deep learning convolutional neural network (DL-CNN) approach. We first identified and selected six SSD predisposing variables to train the models. These variables are the normalized difference ve...
Article
Full-text available
Vaccination remains the most promising mitigation strategy for the COVID-19 pandemic. However, existing literature shows significant disparities in vaccination uptake in the United States. Using publicly available national-level data, we aimed to explore if county-level social capital can further explain disparities in vaccination uptake rates when...
Article
Full-text available
Street view images are now widely used in web map services, providing on-site photos of street scenes for users to explore without physically being in the field. These photos record detailed visual information of the street environment with geospatial control; therefore, they can be used for metric mapping purposes. In this study, we present a meth...
Poster
Full-text available
Aims and Scope: Public health is inextricably linked to geospatial context. Where, when, and how people interact with natural, social, built, economic and cultural environments directly influences human health outcomes, policy making, planning and implementation, especially for infectious diseases such as COVID-19, HIV, and influenza. Geospatial da...
Article
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In this study, we aim to reveal hidden patterns and confounders associated with policy implementation and adherence by investigating the home-dwelling stages from a data-driven perspective via Bayesian Inference with weakly informative priors and by examining how home-dwelling stages in the U.S. varied geographically, using fine-grained, spatial-ex...
Preprint
Vaccination remains the most promising mitigation strategy for the COVID-19 pandemic. However, existing literature shows significant disparities in vaccination uptake in the United States. Using publicly available national-level data, we aimed to explore if county-level social capital can further explain disparities in vaccination uptake rate adjus...
Article
Full-text available
Without a widely distributed vaccine, controlling human mobility has been identified and promoted as the primary strategy to mitigate the transmission of COVID-19. Many studies have reported the relationship between human mobility and COVID-19 transmission by utilizing the spatial-temporal information of mobility data from various sources. To bette...
Article
Full-text available
This study aims to investigate the moderating effects of various distance measures on the relationship between relative pandemic severity and bilateral tourism demand. After confirming its validity using actual hotel and air demand measures, we leveraged data from Google Destination Insights to understand daily bilateral tourism demand between 148...
Article
Full-text available
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 mob...
Article
Full-text available
Background Given the importance of viral suppression in ending the HIV epidemic in the US and elsewhere, an optimal predictive model of viral status can help clinicians identify those at risk of poor viral control and inform clinical improvements in HIV treatment and care. With an increasing availability of electronic health record (EHR) data and s...
Article
Full-text available
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 a...
Article
Full-text available
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. Drawing on 244 406 geotagged tweets i...
Preprint
Full-text available
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 applied machine learning classifiers. This study seeks to explore the feasibility for using a U-Net deep learning arch...
Article
Full-text available
Accessibility is a topic of interest to multiple disciplines for a long time. In the last decade, the increasing availability of data may have exceeded the development of accessibility modeling approaches, resulting in a modeling gap. In part, this modeling gap may have resulted from the differences needed for single versus multimodal opportunities...
Conference Paper
Background: Traditional longitudinal regression models only estimate the average impact of time-varying covariates on outcome. Such impact may be different by time. Time-varying effect model(TVEM) could explore the way associations between variables of interest change over time. It has been applied into behavioral health research and intensive long...
Article
Full-text available
Street view imagery such as Google Street View is widely used in people's daily lives. Many studies have been conducted to detect and map objects such as traffic signs and sidewalks for urban built-up environment analysis. While mapping objects in the horizontal dimension is common in those studies, automatic vertical measuring in large areas is un...
Article
Full-text available
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 association...
Article
Full-text available
Effective quantification of visitation is important for understanding many impacts of the COVID-19 pandemic on national parks and other protected areas. In this study, we mapped and analyzed the spatiotemporal patterns of visitation for six national parks in the western U.S., taking advantage of large mobility records sampled from mobile devices an...
Article
Full-text available
In response to the soaring needs of human mobility data, especially during disaster events such as the COVID-19 pandemic, and the associated big data challenges, we develop a scalable online platform for extracting, analyzing, and sharing multi-source multi-scale human mobility flows. Within the platform, an origin-destination-time (ODT) data model...
Preprint
Full-text available
Introduction: Disparities and their geospatial patterns exist in coronavirus disease 2019 (COVID-19) morbidity and mortality for people who are engaged with clinical care. However, studies centered on viral infection cases are scarce. It remains unclear with respect to the disparity structure, its geospatial characteristics, and the pre-infection d...
Article
Full-text available
Shaped by human movement, place connectivity is quantified by the strength of spatial interactions among locations. For decades, spatial scientists have researched place connectivity, applications, and metrics. The growing popularity of social media provides a new data stream where spatial social interaction measures are largely devoid of privacy i...
Article
Full-text available
The COVID-19 pandemic poses unprecedented challenges around the world. Many studies have applied mobility data to explore spatiotemporal trends over time, investigate associations with other variables, and predict or simulate the spread of COVID-19. Our objective was to provide a comprehensive overview of human mobility open data to guide researche...
Article
Full-text available
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 censu...
Article
Full-text available
The COVID-19 pandemic poses unprecedented challenges around the world. Many studies indicate that human mobility data provide significant support for public health actions during the pandemic. Researchers have applied mobility data to explore spatiotemporal trends over time, investigate associations with other variables, and predict or simulate the...
Preprint
Full-text available
Background: The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the United States (US) and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for...
Preprint
Full-text available
BACKGROUND The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the US and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, pub...
Article
Full-text available
Background: The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the US and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, pu...
Article
Full-text available
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...
Article
Full-text available
It is important to reconstruct the hidden network structure from the infection status change of an information propagation process for evidence‐based spatial decision‐making. Unlike previous work, we not only consider the heterogeneity of the propagation agents, but also incorporate the heterogeneity of the text contents of information within the p...
Article
Full-text available
Evacuation is an effective and commonly taken strategy to minimize death and injuries from an incoming hurricane. For decades, interdisciplinary research has contributed to a better understanding of evacuation behavior. Evacuation destination choice modeling is an essential step for hurricane evacuation transportation planning. Multiple factors are...
Article
Full-text available
Background: Population mobility is closely associated with COVID-19 transmission, and it could be used as a proximal indicator to predict future outbreaks, which could inform proactive nonpharmaceutical interventions for disease control. South Carolina is one of the US states that reopened early, following which it experienced a sharp increase in C...
Article
Full-text available
Objective: The aim of this study was to examine the geospatial variation of retention in care (RIC) across the counties in South Carolina (SC) from 2010 to 2016 and identify the relevant county-level predictors. Design: Aggregated data on county-level RIC among HIV patients from 2010 to 2016 were retrieved from an electronic HIV/AIDS reporting syst...
Article
Full-text available
Objective: Analysis of geolocation-based social media Big Data provides unprecedented opportunities for a broad range of domains including health as health is intrinsically linked to the geographic characteristics of places. HIV infection is largely driven by HIV risk behaviors, such as unsafe sexual behavior and drug abuse/addiction. This study e...
Preprint
Full-text available
In response to the soaring needs of human mobility data, especially during disaster events such as the COVID-19 pandemic, and the associated big data challenges, we develop a scalable online platform for extracting, analyzing, and sharing multi-source multi-scale human mobility flows. Within the platform, an origin-destination-time (ODT) data model...