Yujie Hu

Associate Professor

yujiehu@ufl.edu 352-294-7514

Gainesville FL UNITED STATES
College of Liberal Arts and Sciences

Yujie Hu is a geographer with research and teaching interests in urban transportation, human mobility and accessibility.

Contact

Biography

Yujie Hu's research is the development and application of GIS, network analysis and machine learning/AI techniques to reveal patterns of individual and group behaviors from big geospatial data. He is an associate professor of geography in the College of Liberal Arts and Sciences.

Areas of Expertise

GIScience

Health Services Research

Human Mobility

Network Science

Spatial Accessibility

Urban Transportation

Social

Articles

Modeling and Analysis of Excess Commuting with Trip Chains

Annals of the American Association of Geographers

Yujie Hu and Xiaopeng Li

2021-01-04

Commuting, like other types of human travel, is complex in nature, such as trip-chaining behavior involving making stops of multiple purposes between two anchors. According to the 2001 National Household Travel Survey, about half of weekday U.S. workers made a stop during their commute. In excess commuting studies that examine a region’s overall commuting efficiency, commuting is, however, simplified as nonstop travel from homes to jobs.

Temporal dynamics of the impact of land use on modal disparity in commuting efficiency

Computers, Environment and Urban Systems

Michał A.Niedzielski, et. al

2020-07-29

Urban land use is known to affect commuting efficiency according to the excess commuting framework. However, most studies do not include temporal dynamics, and those that do, focus on decadal, yearly, or daily temporal resolutions. However, commuting is not a stationary spatial process.

Estimating a Large Travel Time Matrix Between Zip Codes in the United States: A Differential Sampling Approach

Journal of Transport Geography

Yujie Hu, et. al

2020-06-15

Estimating a massive drive time matrix between locations is a practical but challenging task. The challenges include availability of reliable road network (including traffic) data, programming expertise and access to high-performance computing resources. This research proposes a method for estimating a nationwide drive time matrix between ZIP code areas in the U.S.-a geographic unit at which many national datasets such as health information are compiled and distributed.