Fahui Wang
Cyril & Tutta Vetter Alumni Professor Louisiana State University
- Baton Rouge LA
Dr. Wang’s current work focuses on spatially-integrated social sciences, public policy and planning (S3P3).
Biography
Areas of Expertise
Research Focus
Spatial Health Science & GIS-Based Spatial Econometrics
Dr. Wang’s research focuses on spatial health science and GIS-based spatial econometrics, probing how geography shapes access to healthcare, public services, and crime risk. He develops advanced spatial-accessibility models—such as the two-step floating catchment method—and merges big-data GIS with econometric analysis to guide equitable service planning and evidence-based public policy.
Education
The Ohio State University
Ph.D.
City & Regional Planning
1995
The Ohio State University
M.A.
Economics
1993
Peking University,
B.S.
Geography
1988
Accomplishments
International Association of Chinese Professionals in Geographic Information Science (CPGIS) Distinguished Scholar Award
2023
Distinguished Research Master Award, LSU
2022
Distinguished Faculty Award, LSU
2018
Articles
Travel Behaviors of Hand-Foot-and-Mouth Disease Patients Across Hospital Service Areas in Nanchang City, China
Chinese Geographical Science2025
This paper examines the travel behaviors of hand-foot-and-mouth disease (HFMD) patients in Nanchang City in central China. Based on the HFMD patients’ hospital visitation data from the Center of Disease Control (CDC) of Nanchang in 2018, a spatial network of patient-to-hospital trip flows is constructed. A Geographic Information Systems (GIS) automated network community detection method, termed ‘ScLeiden’, is utilized to delineate the study area into six hospital service areas (HSAs) to represent distinctive health care markets. Patients’ travel patterns across these HSAs are compared to highlight the geographic disparity. In two HSAs anchored by major hospitals in the regions, the volume of patients increased up to a travel range and then declined, and thus formed a single peak in the trip volume distribution curve across travel time.
Cancer incidence data at the ZIP Code Tabulation Area level in the United States interpolated by Monte Carlo simulation with multiple constraints
Scientific Data2025
High-quality cancer data are fundamental for public health research and policy, but cancer data for small geographic units and population subgroups in the United States are rarely available due to small-sample suppression rules, spatial coarsening, and data incompleteness. These limitations hinder high-resolution spatial analyses and precision public health interventions. This study provides a high-resolution cancer incidence dataset for the U.S., generated through a multi-constraint Monte Carlo simulation framework that reconstructs suppressed county-level cancer data and systematically disaggregates them to ZIP Code Tabulation Areas (ZCTAs), guided by demographic constraints. This method integrates population subgroup structures and macro-level incidence rates as constraints, ensuring consistency and reliability across spatial scales.
Detecting cross-boundary regional collaboration in China by network community scanning with human mobility data
Environment and Planning B: Urban Analytics and City Science2025
Accurately identifying and analyzing cross-boundary regional cooperation remains challenging due to administrative constraints and data limitations. This study utilizes high-resolution human mobility data, network community scanning (NCS), and association rule mining to examine trans-provincial cooperation across 369 Chinese cities, leveraging Location-Based Services (LBS) data from 1.3 billion users. The findings indicate that border-adjacent cooperation dominates trans-provincial interactions in China, while non-adjacent cooperation is embedded within broader cooperative networks formed through adjacent ties reinforcing the interwoven nature of cross-administrative collaborations. Additionally, emerging cooperative clusters extend beyond officially designated urban agglomerations, revealing unrecognized regional synergies not yet captured in planning frameworks.
Planning public electric vehicle charging stations to balance efficiency and equality: A case study in Wuhan, China
Sustainable Cities and Society2025
The strategic placement of electric vehicle charging stations (EVCS) is fundamental to the widespread adoption of electric vehicles and plays a crucial role in mitigating climate change. As an emerging public transportation infrastructure, balancing fairness and efficiency in EVCS deployment is essential. To address the challenge of optimizing both fairness and efficiency in EVCS planning, this study introduces a two-step optimization (2SO) model that incorporates dynamic spatiotemporal demand. The model's effectiveness is validated through an empirical analysis in Wuhan, China, using millions of charging records and dynamic population distribution data. Results show that the optimization enhances overall fairness by providing more equitable access to charging services across different regions.
A big data approach to modelling urban population density functions: from monocentricity to polycentricity
Annals of GIS2025
Urban studies have a long tradition of examining the regularity of urban structure by modelling urban population density functions and probing the theoretical or behavioural foundation behind it. Previous studies commonly used census data in areal units such as census tracts or census block groups, which varied a great deal in area size and shape and led to the zonal and scale effects, commonly referred to as the modifiable areal unit problem (MAUP). This study uses big data of individual vehicle trips in Tampa, Florida, to define the precise population and employment distribution locations, and then aggregates them with uniform areal units such as squares, triangles, and hexagons to examine and mitigate the scale and zonal effects. Both monocentric and polycentric models are employed in the analysis of urban population density functions.
Event Appearances
Four Methodological Themes in Spatial Health Sciences
2023 | 4th Annual National Big Data Health Science Conference, University of South Carolina Columbia, SC
A New Planning Paradigm: The Maximal Accessibility Equality Problem (MAEP)
2022 | New Urban Researcher Seminar Series, University of Hong Kong Hong Kong, China
Why Public Health Needs GIS
2021 | PhD Students Seminar, School of Public Health, The University of Texas Health Science Center at Houston Houston, TX
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