News

23

Sep 22

Diverged landscape of restaurant recovery: the effect of COVID-19 on the restaurant industry in the United States

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' origins as well as the relationship between restaurant visitations and travel distances. Existing studies in the context of COVID-19 mainly reply on survey data and cannot reveal the changing spectrum of the restaurant industry at a large spatial and temporal scale. Here we construct a spatially explicit evaluation of the effect of...
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19

Sep 22

Check out our new study of using neighborhood- level simulation with human mobility data and SEIR model to reveal geographic transmission pattern of COVID-19

A new preprint article titled "Revealing geographic transmission pattern of COVID-19 using neighborhood- level simulation with human mobility data and SEIR model: A Case Study of South Carolina", led by our student Huan Ning is now available on medRxiv. Abstract: 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-19 in January 2021 in three major metropolitan statistical areas (Columbia, Greenville,...
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4

Sep 22

Check out the news release about our recent publication about the COVID-19 impact on the black-owned restaurants

Check out the news release about our recent publication about the COVID-19 impact on the black-owned restaurants, led by Dr. Xiao Huang, our lab alumnus and now the Assistant Professor at the Department of Geosciences, University of Arkansas. https://www.eurekalert.org/news-releases/963549 Full article: https://www.researchgate.net/publication/361780077_Black_businesses_matter_A_longitudinal_study_of_black-owned_restaurants_in_the_COVID-19_pandemic_using_geospatial_big_data
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20

Aug 22

New review article: Social media mining under the COVID-19 context – Progress, challenges, and opportunities

Our new collaborative review article titled "Social media mining under the COVID-19 context: Progress, challenges, and opportunities" is published in the Special Issue "Harnessing Geospatial Big Data for Infectious Diseases" in the International Journal of Applied Earth Observation and Geoinformation. Abstract: 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 perspectives. This review summarizes the progress of social media...
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20

Jul 22

GIBD receives new funding to develop a network-based big data approach to measure healthcare utilization disparity

GIBD receives $30,000 from the USC BDHSC Pilot Project Program to conduct a pilot study of developing a novel network-based big data approach to measure healthcare utilization disparity. The project team include Drs. Zhenlong Li, Shan Qiao, Bankole Olatosi, and Jiajia Zhang. Project summary: Healthcare utilization is a critical factor that influences population health and wellbeing. To identify, explain, and address disparities and inequities in healthcare utilization, it is necessary to develop a valid measurement approach that can accurately capture the disparities and explore the factors that contribute to the disparities in a timely manner. Increasing attention is being paid...
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19

Jul 22

Black businesses matter: A longitudinal study of black-owned restaurants in the COVID-19 pandemic using geospatial big data

Check out our new article titled "Black businesses matter: A longitudinal study of black-owned restaurants in the COVID-19 pandemic using geospatial big data " published in Annals of the American Association of Geographers . Abstract: 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 longitudinal quantitative analysis of restaurant patronage. Using multiple sources of geospatial big data,...
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19

Jul 22

Our new preprint article “An optimal sensors-based simulation method for spatiotemporal event detection” is made to the public

Check out the full article at https://www.researchgate.net/publication/362751541_An_optimal_sensors-based_simulation_method_for_spatiotemporal_event_detection  Abstract: 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 taxi trip data. A sensor here is an abstract concept such that only the true observation data at the sensor location will be treated as known data for the simulation. Specifically, we first identify the optimal number of sensors and their locations that have...
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2

Jun 22

New preprint: Does place connectivity moderate the association between concentrated disadvantage and COVID-19 fatality in the United States?

Access the full article here.  Abstract: 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 COVID-19 fatality. Using COVID-19 fatality over four time periods, we performed mixed-effect negative binomial regressions to examine the association between concentrated disadvantage, Twitter-based place connectivity, and county-level COVID-19 fatality, considering potential state-level variations. Results revealed that concentrated disadvantage was significantly associated with an increased COVID-19 fatality. More importantly, moderation...
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20

May 22

Yuqin Jiang successfully defended her dissertation “Quantifying Human Mobility Patterns During Disruptive Events with Big Data”

GIBD lab member Yuqin Jiang successfully defended her dissertation titled "Quantifying Human Mobility Patterns During Disruptive Events with Big Data" on May 18, 2022.  Big thanks to her committee, Professors Susan Cutter, Michael Hodgson, and Qunying Huang (University of Wisconsin-Madison). Yuqin has accepted an offer to join Texas A&M University as a Postdoctoral Researcher in July 2022 to start her academic career! Congratulations, Yuqin!
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15

May 22

Two articles published in the Canadian Journal of Remote Sensing investigating the usage of deep learning for environmental issues

Learning-Based Methods for Detection and Monitoring of Shallow Flood-Affected Areas: Impact of Shallow-Flood Spreading on Vegetation Density 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 flood-affected areas mapping and monitoring. The models were trained by using 214, 235, 230, and 219 ground truth data for years 2012, 2014, 2017 and 2020 respectively. Our accuracy assessment via the area under...
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21

Apr 22

Huan Ning successfully defended his dissertation proposal “Neighborhood Mobility Assessment for Wheelchair Users Based on Street View Imagery and Deep Learning”

GIBD lab member Huan Ning successfully defended his dissertation proposal "Neighborhood Mobility Assessment for Wheelchair Users Based on Street View Imagery and Deep Learning" on April 20, 2022.  Huan's dissertation committee consists of Professors Zhenlong Li (Chair),  Susan Wang, Michael Hodgson, Shan Qiao (Arnold School of Public Health). Congratulations, Huan!
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11

Apr 22

New article accepted by CEUS: Converting street view images to land cover maps for metric mapping: a case study on sidewalk network extraction for the wheelchair users

Our new article titled "Converting street view images to land cover maps for metric mapping: a case study on sidewalk network extraction for the wheelchair users", led by GIBD member Huan Ning is accepted for publication by Computers, Environment and Urban Systems (acceptance rate: 12%, Impact Factor: 5.3). Abstract: 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...
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2

Apr 22

Yuqin Jiang will join the Civil Engineering Department at the Texas A&M University as a Postdoctoral Researcher in July 2022

GIBD lab member Yuqin Jiang has accepted an academic job offer to join the Civil Engineering Department at the Texas A&M University as Postdoctoral Researcher in July 2022.  Yuqin will defend his dissertation proposal titled "Quantifying Human Mobility Patterns During Disruptive Events with Big Human Mobility Data" in May. Congratulations, Yuqin!
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18

Mar 22

Call for Papers on Special Issue: “Harnessing Geospatial Big Data for Infectious Diseases” in the International Journal of Applied Earth Observation and Geoinformation (Elsevier) 

We are launching a new Special Issue "Harnessing Geospatial Big Data for Infectious Diseases" in the International Journal of Applied Earth Observation and Geoinformation (Elsevier) (Impact factor of 5.933). https://www.journals.elsevier.com/international-journal-of-applied-earth-observation-and-geoinformation/call-for-papers/call-for-papers-on-special-issue-harnessing-geospatial-big-data-for-infectious-diseases  Guest Editors: Dr. Zhenlong Li, University of South Carolina, USA Dr. Shengjie Lai, University of Southampton, UK Dr. Kathleen Stewart, University of Maryland, USA Dr. Bo Huang, Chinese University of Hong Kong, China Dr. Xiaoming Li, University of South Carolina, USA   Submission deadline: December 31, 2022 Planned publication date: Spring 2023 Aims and Scope: Public health is inextricably linked to geospatial context. Where, when, and how people interact with natural,...
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15

Mar 22

GIBD lab receives funding from South Carolina Sea Grant Consortium to develop a GIS-based siting tool for South Carolina mariculture site selection

GIBD members receive $34,993 in funding from South Carolina Sea Grant Consortium to develop a GIS-based siting tool for South Carolina mariculture site selection. The project team includes Dr. Zhenlong Li (PI), Dr. Cuizhen Wang (Co-PI), and Huan Ning. The shellfish industry in coastal South Carolina (SC) weighs heavily in culturing and harvesting eastern oyster (Crassostrea virginica) and hard clam (Mercenaria spp.) in tidal creeks and estuaries. Oyster farming in SC is relatively new and is in a smaller scale than those well-established mariculture industries in other Atlantic and Gulf coastal states. However, its economic and public benefits deserve to...
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10

Mar 22

Yuqin Jiang won the 1st place of the 2022 Robert Raskin Student Paper Competition at the American Association of Geographers Annual Meeting!

Congratulations, Yuqin!   More details about the Competition: https://aagcisg.wordpress.com/robert-raskin-student-competition-2022/
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7

Mar 22

New article “Human mobility and COVID-19 transmission: a systematic review and future directions” is published in the Annuals of GIS

The article is open access available at: https://www.tandfonline.com/doi/full/10.1080/19475683.2022.2041725  Zhang, M., Wang, S., Hu, T., Fu, X., Wang, X., Hu, Y., Halloran B., Li Z. … & Bao, S. (2022). Human mobility and COVID-19 transmission: A systematic review and future directions. Annals of GIS, 1-14. Abstract: 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 better understand the role of human mobility in the...
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21

Feb 22

GIBD members co-organized 5 sessions and delivered a number of presentations at the 2022 AAG Annual Meeting

GIBD lab members have co-organized 5 sessions and will deliver 6 presentations in 2022 AAG related to geospatial big data, human mobility, and public health. See more information below. Sessions organized Harnessing Geospatial Big Data for Infectious Diseases Type: Virtual Paper Day: 2/26/2022 Start Time: 9:40 AM End Time: 11:00 AM Organizer(s): Zhenlong Li , Shengjie Lai, Bo Huang, Kathleen Stewart Chairs(s): Zhenlong Li, University of South Carolina https://aag-annualmeeting.secure-platform.com/a/solicitations/19/sessiongallery/2952   Symposium on Human Dynamics Research: Human mobility in Big Data Era I Type: Virtual Paper Day: 2/27/2022 Start Time: 3:40 PM End Time: 5:00 PM Organizer(s): Yuqin Jiang, Zhenlong Li , Xiao Huang Chairs(s):...
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10

Feb 22

The Big Data Health Science Center’s Geospatial Core announced the second annual Geographic Information Science (GIS) Scholars Program.

The Big Data Health Science Center’s Geospatial Core is pleased to announce the second annual Geographic Information Science (GIS) Scholars Program. This program is being launched to recognize and support three outstanding undergraduate or graduate students who have demonstrated interest, potential, and/or experience in GIS and health research. GIS and health research is broadly defined, and includes, but is not limited to, using GIS to evaluate the social determinants of health, health behaviors, health outcomes, access to health care and social services, utilization of health services, environmental exposures, built environment, and other health-related factors through mapping and spatial analysis. Anyone...
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9

Feb 22

Grayson Morgan passed his dissertation defense on February 9 titled “sUAS and Deep Learning for High-resolution Monitoring of Tidal Marshes in Coastal South Carolina”

GIBD lab member Grayson Morgan successfully defended his dissertation, “sUAS and Deep Learning for High-resolution Monitoring of Tidal Marshes in Coastal South Carolina”. His research committee includes Dr. Susan Wang (Chair), Dr. Michael Hodgson (co-Chair), Dr. Zhenlong Li, and Dr. Steve Schill from the Nature Conservancy. Big congratulations to the soon-to-be Dr. Morgan!  Excellent job, Grayson!
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8

Feb 22

Our new review paper “Human mobility and COVID-19 transmission: a systematic review and future directions” is accepted for publication by Annals of GIS.

Our new collaborative review paper titled "Human mobility and COVID-19 transmission: a systematic review and future directions" has been accepted for publication by the Annals of GIS. Abstract:  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 better understand the role of human mobility in the pandemic, we conducted a systematic review of articles that measure the relationship between human mobility and...
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4

Feb 22

Welcome to join the 3rd annual National Big Data Health Science Conference on February 11-12, 2022!

Welcome to join the 3rd annual National Big Data Health Science Conference on February 11-12, 2022 (virtual) organized by the UofSC Big Data Health Science Center. The theme of the conference this year is “Unlocking the Power of Big Data in Health: Developing an Interdisciplinary Response for Health Equity”. This conference will bring together leaders from academia, government, industry, and healthcare systems to focus on and forge new discussions about the role of interdisciplinary collaboration in Big Data applications and advancements in the health sciences. Register here: https://lnkd.in/eXC_JYJc The program agenda can be found here: https://www.sc-bdhs-conference.org/program-2022/  
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29

Jan 22

Article “Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection: A Comparative Study” accepted for publication in IJGI

Our new article titled “Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection: A Comparative Study“ is accepted for publication in the ISPRS International Journal of Geo-Information. Abstract: 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 architecture to classify bi-temporal high resolution county scale aerial images to determine the spatial extent and changes of land cover classes that...
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19

Jan 22

Population mobility and aging accelerate the outbreaks of COVID-19 in the Deep South: a county-level longitudinal analysis

Our new article titled "Population mobility and aging accelerate the outbreaks of COVID-19 in the Deep South: a county-level longitudinal analysis", authored by Chengbo Zeng, Jiajia Zhang, Zhenlong Li, Xiaowen Sun, Xueying Yang, Bankole Olatosi, Sharon B Weissman, and Xiaoming Li, has been accepted for publication by Clinical Infectious Diseases (Impact Factor: 9.1). We find that population mobility and aging at local areas contributed to the geospatial disparities in COVID-19 outbreaks among 418 counties in the Deep South. A significant interaction between mobility and proportion of older adults in predicting COVID-19 incidence was found. Effective disease control measures should be...
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18

Jan 22

New Award: A novel data-driven approach to empirically link structural racism and healthcare access and utilization in South Carolina

Dr. Zhenlong Li, collaborated with Dr. Shan Qiao from public health, has been awarded a project titled “A novel data-driven approach to empirically link structural racism and health access and utilization in South Carolina” by the UofSC OVPR Racial Justice and Equity Research Program. Other team members include Drs. Xiaoming Li, Bankole Olatosi, and Jiajia Zhang. Leveraging large place visitation records with high granularity sampled from mobile devices and census data, we propose an integrative big data approach to examine the association between structural racism and disparities in health care access in South Carolina. The proposed research will develop innovative...
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15

Jan 22

“Studying patterns and predictors of HIV viral suppression using A Big Data approach: A research protocol” accepted for publication

Our new article titled "Studying patterns and predictors of HIV viral suppression using A Big Data approach: A research protocol", co-authored by Zhang J., Olatosi B., Yang X., Weissman S., Li Z., Hu J., Li X, is accepted for publication by BMC Infectious Diseases. This is a peer-reviewed protocol article where the study has received ~3.5 million funding from NIH. 2021-2026, Patterns and Predictors of Viral Suppression: A Big Data Approach, National Institutes of Health (NIH), R01AI164947, MPI: Bankole Olatosi and Jiajia Zhang; Co-Investigators:  Zhenlong Li, Sharon Weissman, Jianjun Hu, Xiaoming Li,  $3,500,000
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3

Jan 22

Welcome our new Postdoc Scholar Dr. Fengrui Jing to join GIBD team!

Dr. Fengrui Jing received his PhD in GIScience from Sun Yat-sen University in 2021. He also holds a master’s degree in Physical Geography and two undergraduate degrees in Social Work and Psychology. His research focuses on using massive social media data to map neighborhood disorder and fear of crime, and to examine the causal relationship between micro built environment and fear of crime. Dr. Jing will work with Dr. Zhenlong Li and other team members in GIBD and USC Big Data Health Science Center (BDHSC, https://bigdata.sc.edu) to conduct cutting-edge and innovative interdisciplinary research on geospatial big data analytics (e.g., analyzing...
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20

Dec 21

Exploring international travel patterns and connected communities for understanding the spreading risk of VOC Omicron

The novel SARS-CoV-2 variant of concern (VOC) Omicron (lineage B.1.1.529), together with four existing VOC variants, has raised serious concerns about the effectiveness of vaccines and the potential for a new wave of the pandemic (Figures 1 and 2) . This new strain was first detected in in November 2021 in South Africa and among international cases with a travel history from southern African countries. However, community transmission with associated clusters has now been reported in several countries. According to the COVID-19 Weekly Epidemiological Update published by the WHO, a total of 76 countries have reported confirmed cases of the...
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18

Dec 21

Does distance still matter? Moderating effects of distance measures on the relationship between pandemic severity and bilateral tourism demand

New article titled "Does distance still matter? Moderating effects of distance measures on the relationship between pandemic severity and bilateral tourism demand", authored by Yang Y., Zhang L., Wu L. and Li Z., has been accepted for publication by Journal of Travel Research (Impact factor: 10.982). 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 origin countries and 109 destination...
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10

Dec 21

“The times, they are a-changin’: tracking the shifts in mental health signals in Australia from the early to later phase of the COVID-19 pandemic” accepted by BMJ Global Health

Our new article titled "The times, they are a-changin’: tracking the shifts in mental health signals in Australia from the early to later phase of the COVID-19 pandemic" has been accepted for publication by BMJ Global Health (Impact Factor: 5.558). ----Abstract---- 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 January 1, 2020 to May 31,...
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8

Dec 21

Check out our new preprint: Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection: A Comparative Study

Please check out our new preprint titled "Deep Learning of High-Resolution Aerial Imagery for Coastal Marsh Change Detection: A Comparative Study". 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 architecture to classify bi-temporal high resolution county scale aerial images to determine the spatial extent and changes of land cover classes that directly or indirectly impact tidal marsh. The image set...
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8

Dec 21

“Exploring the spatial disparity of home-dwelling time patterns in the U.S. during the COVID-19 pandemic via Bayesian inference” accepted by Transactions in GIS

Our paper titled "Exploring the spatial disparity of home-dwelling time patterns in the U.S. during the COVID-19 pandemic via Bayesian inference" has been accepted for publication by the Transactions in GIS.  Abstract: 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-explicit home-dwelling time records from a multi-scale perspective. At the U.S. national level, two changepoints are identified, with the former corresponding to...
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7

Dec 21

“The promise of excess mobility analysis: measuring episodic-mobility with geotagged social media data” accepted by Cartography and Geographic Information Science

Our new paper titled "The promise of excess mobility analysis: measuring episodic-mobility with geotagged social media data" is accepted for publication in the Cartography and Geographic Information Science. Abstract: 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....
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28

Nov 21

The book “Manual of Digital Earth” published by the International Society for Digital Earth reached a total of 856,000 downloads

The Manual of Digital Earth, an eBook published by International Society for Digital Earth and co-edited by Prof. Huadong Guo, Prof. Mike Goodchild, and Dr. Alessandro has reached a total of 856000 downloads since its publication in November 2019. This open access book offers a summary of the development of Digital Earth over the past twenty years. By reviewing the initial vision of Digital Earth, the evolution of that vision, the relevant key technologies, and the role of Digital Earth in helping people respond to global challenges, this publication reveals how and why Digital Earth is becoming vital for acquiring, processing,...
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15

Nov 21

Special Issue call for papers: Spatial Analytics for COVID-19 Studies in the International Journal of Environmental Research and Public Health

Zhenlong Li is co-guest editing a Special Issue entitled “Spatial Analytics for COVID-19 Studies” for the International Journal of Environmental Research and Public Health (ISSN 1660-4601, IF 3.390, http://www.mdpi.com/journal/ijerph). IJERPH is an open access journal indexed by SCI, SSCI, Scopus, and PubMed. According to Web of Science, IJERPH ranks 118/274 (Q2) in “Environmental Sciences” (SCIE), 68/203 (Q2) in “Public, Environmental, and Occupational Health” (SCIE), and 41/176 (Q1) in “Public, Environmental, and Occupational Health” (SSCI). The median processing time for submissions is less than 45 days, which includes a free English editing service after acceptance of the paper. The article processing...
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31

Oct 21

GIBD is organizing a series of sessions on geospatial big data and spatial computing in the 2022 AAG annual meeting

GIBD is organizing a series of sessions on the topics of big data computing, disaster management, human mobility, and public health in the 2022 AAG annual meeting Harnessing Geospatial Big Data for Infectious Diseases Type: Virtual Paper Sponsor Group(s):  Cyberinfrastructure Specialty Group Organizer(s): Zhenlong Li, Shengjie Lai, Bo Huang, Kathleen Stewart Public health is inextricably linked to geospatial context. Where, when, and how people interact with natural, social, built, economic and cultural environments directly influence human health outcomes, policy making, planning and implementation, especially for infectious diseases such as COVID-19, HIV, and influenza. Geospatial data has long been used in health...
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11

Oct 21

Final Call for Papers: Special Issue “GIScience for Risk Management in Big Data Era” in ISPRS International Journal of Geo-Information

GIScience for Risk Management in Big Data Era Deadline for manuscript submissions: 31 October 2021. This Special Issue aims to capture recent efforts and advancements in harnessing the power of GIScience for risk management in the big data era. The first group of possible topics is to inspire potential authors to deal with basic and new trends related to the big data era. The contribution of novel approaches to spatial data collection (social networks, sensors, citizen science, VGI, etc.), disaster big data processing and sharing, real-time data-centric intelligence based on sensors, harmonization of heterogeneous data into a single structure, cybersecurity of...
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14

Sep 21

New paper published in the International Journal of Environmental Research and Public Health

Our paper entitled "Temporal Geospatial Analysis of COVID-19 Pre-infection Determinants of Risk in South Carolina", co-authored by Tianchu Lyu, Nicole Hair, Nicholas Yell, Zhenlong Li, Shan Qiao, Chen Liang , and Xiaoming Li, is published in the International Journal of Environmental Research and Public Health. Abstract: 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...
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18

Aug 21

Manuscript accepted for publication by the International Journal of Geographical Information Science, a flagship journal in GIScience!

A new article led by Huan Ning, titled "Exploring the Vertical dimension of Street View Image Based on Deep Learning: A Case Study on Large-scale Building Flooding Risk Assessment", has been accepted for publication in the International Journal of Geographical Information Science, a flagship journal in GIScience. Congratulations, Huan!
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19

Jul 21

“Measuring Global Multi-Scale Place Connectivity using Geotagged Social Media Data” published in nature Scientific Reports

Our article "Measuring Global Multi-Scale Place Connectivity using Geotagged Social Media Data" has published nature Scientific Reports. Read the article at https://www.nature.com/articles/s41598-021-94300-7  Abstract: 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 issues, easily assessable, and harmonized. In this study, we introduced a global multi-scale place connectivity index (PCI) based on spatial interactions among places revealed by geotagged tweets as a...
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17

Jul 21

“ODT FLOW: Extracting, analyzing, and sharing multi-source multi-scale human mobility” accepted for publication by Plos One

Abstract: 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 is proposed to work with scalable query engines to handle heterogenous mobility data in large volumes with extensive spatial coverage, which allows for efficient extraction, query, and aggregation of billion-level origin-destination (OD) flows in parallel at the server-side. An interactive spatial web portal, ODT Flow Explorer, is developed to allow...
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3

Jul 21

“Human Mobility Data in the COVID-19 Pandemic: Characteristics, Applications, and Challenges” accepted for publication by International Journal of Digital Earth

Review article entitled "Human Mobility Data in the COVID-19 Pandemic: Characteristics, Applications, and Challenges" accepted for publication by the International Journal of Digital Earth (2020 Impact Factor: 3.538) Read preprint here. Abstract: 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 spread of COVID-19. Our objective was to provide a comprehensive overview of human mobility open data to guide researchers and policymakers...
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25

Jun 21

Zhenlong Li gave an invited presentation at the Oak Ridge National Laboratory

Zhenlong Li gave an invited presentation titled "Measuring Human Mobility Dynamics and Place Connectivity Using Big Social Media Data" at Geospatial Science and Human Security Division Director Seminar Series of the Oak Ridge National Laboratory on June 24, 2021. Abstract: Understanding human mobility dynamics among places provides fundamental knowledge regarding their interactive gravity, benefiting a wide range of applications in need of knowledge in human spatial interactions. The ongoing COVID-19 pandemic uniquely highlights the need for monitoring, measuring, and predicting human movement at various geographic scales from local to global. This talk first introduces our recent effort in quantifying global...
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17

Jun 21

Article “A novel big data approach to measure and visualize urban accessibility” is published in Computational Urban Science

A new article titled "A novel big data approach to measure and visualize urban accessibility", authored by Yuqin Jiang, Diansheng Guo, Zhenlong Li, and Michael Hodgson, is published in Computational Urban Science. Abstract: 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 for access to services. With a focus on large volumes of transportation data, a...
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14

Jun 21

Article “Introducing Twitter Daily Estimates of Residents and Non-Residents at the County Level” published in Social Sciences

A new article titled "Introducing Twitter Daily Estimates of Residents and Non-Residents at the County Level", authored by Yago Martin, Zhenlong Li, Yue Ge, and Xiao Huang, is published in Social Sciences. Abstract: 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...
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30

May 21

Staying at home is a privilege: evidence from fine-grained mobile phone location data in the U.S. during the COVID-19 pandemic

A new article "Staying at home is a privilege: evidence from fine-grained mobile phone location data in the U.S. during the COVID-19 pandemic" led by Dr. Xiao Huang is published in the Annals of the American Association of Geographers.  Congratulations to Xiao and his team!! Abstract: The coronavirus disease 2019 (COVID-19) has exposed and, to some degree, exacerbated social inequity in the United States. This study reveals the correlation between demographic and socioeconomic variables and home-dwelling time records derived from large-scale mobile phone location tracking data at the U.S. census block group (CBG) level in the twelve most populated Metropolitan...
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18

May 21

“Spatiotemporal patterns of human mobility and its association with land use types during COVID-19 in New York City” published in IJGI

The paper titled "Spatiotemporal patterns of human mobility and its association with land use types during COVID-19 in New York City", led by Yuqin Jiang, is published in ISPRS International Journal of Geo-Information. Abstract: 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 New York...
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May 21

Zhenlong Li will give a presentation on “Measuring Global Multi-Scale Place Connectivity using Geotagged Social Media Data”

Invited by SafeGraph, Zhenlong Li will be giving a presentation to the SafeGraph/Placekey Slack community — a community of over 8000 researchers and data scientists on Tuesday, June 22 at 1:00 PM - 1:45 PM EDT. Place connectivity - shaped by human movement - is quantified by the strength of spatial interactions among locations. Using social media data, they introduce a global multi-scale place connectivity index (PCI) based on spatial interactions among places that have been geotagged in tweets. This analysis can enable modeling the spread of COVID-19 and hurricane evacuation destination choices, helping with future policy and planning procedures.
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Apr 21

Call for papers: Special Issue “Spatial Analytics for COVID-19 Studies” by the International Journal of Environmental Research and Public Health

Dear Colleagues, Coronavirus disease 2019 (COVID-19) is a global threat that has led to many health, economic, and social challenges. The spread of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that caused the COVID-19 pandemic is inherently a spatial process. Therefore, geospatial data, algorithms, models, tools, and platforms play an irreplaceable role in providing situational awareness that benefits decision making. The notable advances in Geographical Information Sciences (GIScience) have encouraged the incorporation of spatial analytics into various epidemiological studies over the past decade. In this Special Issue, we focus on the development and application of advanced spatial analytics towards understanding...
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