Zhenlong Li

Pennsylvania State University | Penn State · Department of Geography

Forecasting infectious respiratory diseases is crucial for effective prevention and intervention strategies. However, existing time series forecasting models that incorporate human mobility data have faced challenges in making localized predictions on a large scale across the country due to data costs and constraints. Using the COVID-19 pandemic as...

Recent advancements in Generative AI offer promising capabilities for spatial analysis. Despite their potential, the integration of generative AI with established GIS platforms remains underexplored. In this study, we propose a framework for integrating LLMs directly into existing GIS platforms, using QGIS as an example. Our approach leverages the...

Numerous researchers have utilized GPS-enabled vehicle data and SafeGraph mobility data to analyze human movements. However, the comparison of their ability to capture human mobility remains unexplored. This study investigates differences in human mobility using taxi trip records and the SafeGraph dataset in New York City neighborhoods. The analysi...

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...

Background: The rapidly accumulating scientific literature in HIV presents a significant challenge in accurately and efficiently assessing the relevant literature. This study explores the potential capabilities of using large language models (LLMs), such as ChatGPT, for selecting relevant studies for a systematic review. Method: Scientific papers w...

The resurgence and rapid advancement of Generative Artificial Intelligence (GenAI) in 2023 has catalyzed transformative shifts across numerous industry sectors, including urban transportation and logistics. This study investigates the evaluation of Large Language Models (LLMs), specifically GPT-4 and Phi-3-mini, to enhance transportation planning....

Deep learning (DL) has demonstrated strong potential in addressing key challenges in spatiotemporal forecasting across various Earth system science (ESS) domains. This review examines 69 studies applying DL to forecasting tasks within climate modeling and weather prediction, disaster management, air quality modeling, hydrological modeling, renewabl...

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)...

Historical narratives and the "model minority" myth have obscured the realities of anti-Asian racism in the United States. The escalation of prejudice and hate crimes against Asian Americans during the COVID-19 pandemic further underscored the need for robust measures to quantify this phenomenon. This study proposes a novel county-level index speci...

Powered by the emerging large language models (LLMs), autonomous geographic information systems (GIS) agents have the potential to accomplish spatial analyses and cartographic tasks. However, a research gap exists to support fully autonomous GIS agents: how to enable agents to discover and download the necessary data for geospatial analyses. This s...

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...

Urban parks are essential to maintaining healthy, livable, and sustainable cities. It is vital to ensure urban parks serve the communities equally, particularly during the pandemic and for traditionally disadvantaged groups. This study examined how the COVID-19 pandemic changed urban dwellers’ visitation patterns to urban parks and assessed whether...

Aims and Scope: Over the last decade, GIScience has witnessed significant transformations with the advent of deep learning and artificial intelligence (AI). The rapid development in AI prompted a moonshot by Janowicz et al. (2020) 'Can we develop an artificial GIS analyst that passes a domain-specific Turing Test by 2030?'. The recent advancements...

Information on the depth of floodwater is crucial for rapid mapping of areas affected by floods. However, previous approaches for estimating floodwater depth, including field surveys, remote sensing, and machine learning techniques, can be time-consuming and resource-intensive. This paper presents an automated and rapid approach for estimating floo...

The launch of large language models (LLMs) like ChatGPT in late 2022 and the anticipated arrival of future GPT-x iterations have marked the beginning of the generative artificial intelligence (GAI) era. We conducted a systematic review of how to integrate LLMs including GPT and other GAI models into geospatial science, based on 293 papers obtained...

The elucidation of neighborhood-level mental illness is pivotal to effective community need assessment and public health interventions. However, aggregating individual behaviors linked to mental health at the neighborhood level has proven to be a challenge. In this study, we collected place visitation data from extensive mobile phone records as a p...

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. Specifical...

Geographically weighted regression (GWR) offers a local approach to modeling spatial data, considering geographical location and spatial relationships between observations. A salient feature of GWR is the emphasis on geographical proximity, in accordance with Tobler's First Law of Geography, which assumes that closer entities have a greater influen...

The Canadian wildfires in June 2023 significantly impacted the northeastern United States, particularly in terms of worsened air pollution and environmental justice concerns. While advancements have been made in low-cost sensor deployments and satellite observations of atmospheric composition, integrating dynamic human mobility with wildfire PM2.5...

Multiple Geographical Feature Label Placement (MGFLP) has been a fundamental problem in geographic information visualization for decades. Moreover, the nature of label positioning has proven to be an Nondeterministic polynomial-time hard (NP-hard) problem. Although advances in computer technology and robust approaches have addressed the problem of...

Information on the depth of floodwater is crucial for rapid mapping of areas affected by floods. However, previous approaches for estimating floodwater depth, including field surveys, remote sensing, and machine learning techniques, can be time-consuming and resource-intensive. This paper presents an automated and fast approach for estimating flood...

The transformation from authoritative to user-generated data landscapes has garnered considerable attention, notably with the proliferation of crowdsourced geospatial data. Facilitated by advancements in digital technology and high-speed communication, this paradigm shift has democratized data collection, obliterating traditional barriers between d...

Mobile location data has emerged as a valuable data source for studying human mobility patterns in various contexts, including virus spreading, urban planning, and hazard evacuation. However, these data are often anonymized overviews derived from a panel of traced mobile devices, and the representativeness of these panels is not well documented. Wi...

Recent decades have witnessed several infectious disease outbreaks, including the coronavirus disease (COVID-19) pandemic, which had catastrophic impacts on societies around the globe. At the same time, the twenty-first century has experienced an unprecedented era of technological development and demographic changes: exploding population growth, in...

Introduction Health disparities exist at every step of the HIV care continuum (HCC) among racial/ethnic minority population. Such racial/ethnic disparities may have significantly delayed the progress in HCC in the Southern US states that are strongly represented among geographic focus areas in the 2019 federal initiative titled ‘Ending the HIV Epid...

Background: COVID-19 had a greater impact in the Deep South compared with other regions in the United States. While vaccination remains a top priority for all eligible individuals, data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age are sparse. Despite existing evidence of racial and ethni...

The prevalence of cardiometabolic diseases in the United States is presumably linked to an obesogenic retail food environment that promotes unhealthy dietary habits. Past studies, however, have reported inconsistent findings about the relationship between the two. One underexplored area is how humans interact with food environments and how to integ...

Large Language Models (LLMs), such as ChatGPT, demonstrate a strong understanding of human natural language and have been explored and applied in various fields, including reasoning, creative writing, code generation, translation, and information retrieval. By adopting LLM as the reasoning core, we introduce Autonomous GIS as an AI-powered geograph...

Background COVID-19 testing is essential for pandemic control, and insufficient testing in areas with high disease burdens could magnify the risk of poor health outcomes. However, few area-based studies on COVID-19 testing disparities have considered the disease burden (e.g., confirmed cases). The current study aims to investigate socioeconomic dri...

Background: The COVID-19 pandemic has posed unprecedented pressure to health care systems, and interrupted health care delivery and access including HIV care in the United States’ Deep South, which endures a double epidemic of HIV and COVID-19. Ryan White programs cover HIV care services for over half of PLWH in the Deep South. Given the important...

The global COVID-19 pandemic has imposed unprecedented pressure on health systems and has interrupted public health efforts for other major health conditions, including HIV. It is critical to comprehensively understand how the pandemic has affected the delivery and utilization of HIV-related services and what are the effective strategies that may m...

The degree to which many benefits of national parks are realized hinges on public access. Traditional methods in estimating park visitation can be time-consuming, costly, and labor-intensive. Fortunately, the growing availability of ‘big data’ offers new opportunities for rapid and large-scale estimation. This study investigated the spatiotemporal...

Immigrants (foreign-born United States [US] citizens) generally have lower utilization of mental health services compared with US-born counterparts, but extant studies have not investigated the disparities in mental health service utilization within immigrant population nationwide over time. Leveraging mobile phone-based visitation data, we estimat...

Background Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people’s expressions on social media. However, there is not enough evidence to conclude that social media provides public surveilla...

Background Timely linkage to care (LTC) is key in the HIV care continuum, as it enables people newly diagnosed with HIV (PNWH) to benefit from HIV treatment at the earliest stage. Previous studies have found LTC disparities by individual factors, but data are limited beyond the individual level, especially at the county level. This study examined t...

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 t...

Large Language Models (LLMs), such as ChatGPT, demonstrate a strong understanding of human natural language and have been explored and applied in various fields, including reasoning, creative writing, code generation, translation, and information retrieval. By adopting LLM as the reasoning core, we introduce Autonomous GIS (AutoGIS) as an AI-powere...

Although rural communities have been hard-hit by the COVID-19 pandemic, there is limited evidence on COVID-19 outcomes in rural America using up-to-date data. This study aimed to estimate the associations between hospital admissions and mortality and rurality among COVID-19 positive patients who sought hospital care in South Carolina. We used all-p...

The COVID-19 pandemic has imposed catastrophic impacts on the restaurant industry as a crucial socioeconomic sector that contributes to the global economy. However, the understanding of how the restaurant industry was recovered from COVID-19 remains underexplored. This study constructs a spatially explicit evaluation of the effect of COVID-19 on th...

With the ongoing development of information and communications technology, geospatial technologies have become increasingly important in monitoring, managing, and predicting tourism activities. These tools can also uncover tourism’s social, economic, cultural, environmental, and political impacts. In this viewpoint article, we discuss applications...

BACKGROUND Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people’s expressions in social media space. However, there is less assertive to conclude that social media provides public surveill...

Mobile location data has emerged as a valuable data source for studying human mobility patterns in various contexts, including virus spreading, urban planning, and hazard evacuation. However, these data are often anonymized overviews derived from a panel of traced mobile devices, and the representativeness of these panels is not well documented. Wi...

Direct human physical contact accelerates COVID-19 transmission. Smartphone mobility data has emerged as a valuable data source for revealing 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 o...

COVID-19 cripples the restaurant industry as a crucial socioeconomic sector that contributes immensely to the global economy. However, what the current literature less explored is to quantify the effect of COVID-19 on restaurant visitation and revenue at different spatial scales, as well as its relationship with the neighborhood characteristics of...

The community food environment has potential influences on community members' dietary health outcomes, such as obesity and Type II diabetes. However, most existing studies evaluating such health effects neglect human mobility. In food patrons' daily travels, certain locations may be preferred and patronized more frequently than others. This behavio...

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 suppress...

Geospatial social media (GSM) data has been increasingly used in public health due to its rich, timely, and accessible spatial information, particularly in infectious disease research. This review synthesized 86 research articles that use GSM data in infectious diseases published between December 2013 and March 2022. These articles cover 12 infecti...

Mobile location data has emerged as a valuable data source for studying human mobility patterns in various contexts, including virus spreading, urban planning, and hazard evacuation. However, these data are often anonymized overviews derived from a panel of traced mobile devices, and the representativeness of these panels is not well documented. Wi...

Background 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 the associations between concentrated disadvantage, place connectivity, and COVI...

Rapid detection and mapping of landforms are crucially important to improve our understanding of past and presently active processes across the earth, especially, in complex and dynamic volcanoes. Traditional landform modeling approaches are labor-intensive and time-consuming. In recent years, landform mapping has increasingly been digitized. This...

Background Existing research and national surveillance data suggest an increase of the prevalence of mental disorders during the COVID-19 pandemic. Social media platforms, such as Twitter, could be a source of data for estimation owing to its real-time nature, high availability, and large geographical coverage. However, there is a dearth of studies...

Determining the perception and sentiment of public's opinion of telemedicine and telecare has benefits to healthcare organizations, physicians and patients. Determining a relationship between opinion and demographic elements will aid in developing ways to close the gap between perception and readiness to implement healthcare technology for patients...

Multiple geographical feature label placement (MGFLP) has been a fundamental problem in geographic information visualization for decades. The nature of label positioning is proven an NP-hard problem, where the complexity of such a problem is directly influenced by the volume of input datasets. Advances in computer technology and robust approaches h...

BACKGROUND COVID-19 had a greater impact in the Deep South compared with other regions in the United States. While vaccination remains a top priority for all eligible individuals, data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age are sparse. Despite existing evidence of racial and ethnic...

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...

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...

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'...

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...

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...

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...