Image courtesy Computers, Environment and Urban Systems

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

Michal A. Niedzielski, Yujie Hu, Marcin Stepniak

Article first published online: 29 JUL 2020 Computers, Environment and Urban Systems

DOI: 10.1016/j.compenvurbsys.2020.101523

ABSTRACT: 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. Since people leave home and start their jobs at different times of the day and since traffic congestion varies throughout the day, neglecting hourly dynamics can misestimate commuting efficiency in a region and lead to erroneous policy implications. Another important issue often overlooked in the past is the modal disparity in commuting efficiency and how it evolves during the day. To overcome these limitations, this research examines the commuting efficiency variation by car and public transport by six one-hour periods between 5 AM and 11 AM in Warsaw, Poland, using travel survey data and travel times generated from GPS-based big data for cars and from GTFS for public transport. We develop four different groups of modeling scenarios: no disaggregation, disaggregation by time, disaggregation by mode, and disaggregation by time and mode. Therefore, excess commuting and modal disparity metrics are applied for a total of 21 specific time and mode combinations. The results suggest that commuting efficiency is worst during the 8–9 AM period for both modes, and that public transport users are more efficient after 7 AM. Hourly variations in the excess commuting metrics imply that policy makers should examine ways to encourage flexible work hours to distribute work starts and to increase public transport frequencies in the off-peak.

Read the full publication at Computers, Environment and Urban Systems

Image courtesy Environment and Planning B: Urban Analytics and City Science

HUA tale of two cities: Jobs–housing balance and urban spatial structures from the perspective of transit commuters

Jie Huang, Yujie Hu, Jiaoe Wang, Xiang Li

Article first published online: 10 JUL 2020 Environment and Planning B: Urban Analytics and City Science

DOI: 10.1177/2399808320938803

ABSTRACT: The jobs–housing balance and urban spatial structure are naturally connected, and understanding the connection is important for urban planning, geography, and transport studies. Using smartcard data in Beijing and Shanghai, this research employs a comparative approach to reveal spatial distribution patterns of jobs–housing balance in terms of transit commuters and derive the implied urban spatial structures for the two megacities in China. Results suggested that (1) the overall job–resident ratios estimated with smartcard data were 1.97 and 2.47 in Shanghai and Beijing, respectively; (2) compared to Beijing, Shanghai had greater intermixing of jobs and housing; (3) Beijing’s urban form followed a concentric spatial structure, whereas Shanghai followed a quasi-sector configuration. These findings show that the job–resident ratio can be used as an indicator to capture land-use patterns or functional zones, which is useful for urban planning and transit network design.

Read the full publication at Environment and Planning B: Urban Analytics and City Science

Course description

It is often the case that real-world systems can be represented as networks of many interacting components. This course teaches the fundamental concepts, models, and techniques for describing, visualizing, measuring, and analyzing networks. It also introduces their applications in geography, transportation, social science, etc. A series of labs using the popular network analysis package Gephi and GIS software ArcGIS are also designed to help students gain hands-on experience in visualizing and analyzing networks.

Course Objectives

After successful completion of this course students should be able to:

  • Have a solid grasp of the vocabulary, central concepts, measures and techniques relating to networks;
  • Conduct experiments within the Gephi and ArcGIS software environment;
  • Apply their knowledge to visualize and analyze a real network data set of their choosing.

Dr. Yujie Hu – yujiehu@ufl.edu

Image courtesy Journal of Fish and Wildlife Management

HUSpatial analysis of potential nesting habitat for Florida sandhill cranes

Joni Downs, Courtney Buck, Faisal Qarah, Yujie Hu

Article first published online: 30 JUN 2020 Journal of Fish and Wildlife Management

DOI: 10.3996/092019-JFWM-077

ABSTRACT: The Florida sandhill crane Antigone canadensis pratensis is state-listed as threatened in Florida, where there is an urgent need to map and quantify remaining habitat. First, we used habitat suitability index (HSI) modelling to map and assess potential nesting habitat for sandhill cranes in Florida. Second, we used spatial optimization approaches to calculate the maximum number of breeding pairs that can simultaneously occupy potential nests given that they both must be of some minimum quality and must be spaced some minimal distance apart. The mapping results reveal that nesting habitat is concentrated in the central portion of the state, with adequate brooding habitat appearing to be the most limiting factor affecting habitat suitability. Assuming nesting only occurs in habitat rated as high quality (HSI {greater than or equal to} 0.7) and spacing between adjacent nests is at least 1,000 m, we conservatively estimate that 5,540 nesting pairs of Florida sandhill cranes can potentially be supported. Additional nesting pairs may be supported in habitats of marginal (HSI {greater than or equal to} 0.3; 14,530) to moderate (HSI {greater than or equal to} 0.5; 8,723) quality. The suitability maps and breeding pair estimates can be used to identify important habitat areas to focus crane conservation efforts, determine potentially limiting habitat features across the landscape, and potentially guide future population monitoring efforts. For example, grassland/prairie restoration could be used to potential increase nesting pairs in the southern portion of the state where emergent wetlands are abundant but brooding habitat is lacking.

Read the full publication at Journal of Fish and Wildlife Management

Dr. Yujie Hu
Pronouns: he/him
University of Florida

Focus Areas:

Research Statement: I am a geographer with research and teaching interests in urban transportation, human mobility, and accessibility. My current research focuses on three main areas: 1) relationships between people’s mobility within cities—including commuting, healthcare-seeking, and crime—and the urban built environment, 2) accessibility to opportunities, such as jobs, healthcare, food, and transportation infrastructure, and how it is affected by natural hazards, and, 3) network flow analysis and optimization of travel patterns related to commuting, bike sharing, healthcare, and food delivery.

My main research approach is the development and application of GIS, spatial analysis, and network analysis techniques to reveal patterns of individual and group behaviors from big geospatial data associated with point patterns (traffic crashes, crime incidents) and networks (movement trajectory such as taxi cab GPS trajectory, smart card transaction data, and origin-destination flow such as commuting, bike sharing usage, and inpatient discharge). The goal is to convert data into knowledge to inform and evaluate place-based policies focused on transportation, land use, public health, and community safety.

“If you think in terms of a year, plant a seed; if in terms of ten years, plant trees; if in terms of one hundred years, teach the people.” Confucius
Hermann Park off Rice campus

Who is he?
Dr. Yujie Hu is an Assistant Professor in the Geography Department. He conducts interdisciplinary geospatial research and has worked with researchers in civil engineering, urban planning, computer science, statistics, economics, industrial engineering, political science, public health, environmental science and policy, and sociology – he welcomes researchers and students from these fields for collaborative research.

Yujie is also affiliated with the UF Informatics Institute and UF Transportation Institute, and is a Fellow with the Kinder Institute for Urban Research at Rice University. Prior to his current position, he was an Assistant Professor in the School of Geosciences at the University of South Florida and a Postdoctoral Fellow at Rice University. Yujie grew up in Yantai, China, a beautiful beach city where the Chinese national rail line terminates at a major port.

How did he get here?

Growing up in Yantai, Yujie benefited from excellent bicycle infrastructure. Despite heavy snow in the winter, it’s a great location for year-round bike riding – with low humidity and wide, safe bike lanes. Riding around Yantai, Yujie found himself wondering why roads are where they are and how planners make the location decisions – he started to bike or walk randomly on the road just to explore every corner of the city. “When you’re driving you don’t stop so you can’t look at things,’ he says. “When you’re biking and walking, you have the time to stop and look at the world around you.”

During his Master’s work, Yujie studied spatial patterns of road networks – asking what was present on the roads and analyzing road network structures. While earning his PhD in Geography at Louisiana State University, he explored commuting, travel behavior, healthcare seeking, and crime – adding movement to his work and asking how people use the roads that are present.
Yujie studies and understands spatial questions through applied studies. Using geospatial methods and techniques, he finds interesting problems and patterns, proposes mitigations, and then offers suggested courses of action.

Field work using a GPS unit on LSU campus

Yujie likes being a researcher because he can associate his questions with his personal interests like biking and transit. While a postdoctoral fellow at Rice University, he found Houston to be inhospitable to bicyclists and pedestrians. He identified and studied some particularly bad intersections and ultimately published a journal article Where are the Dangerous Intersections for Pedestrians and Cyclists: A Colocation-Based Approach in 2018. “To make things change, you have to get people’s attention and get them talking,” said Yujie. This work didn’t just yield a publication. Yujie was able to advocate for active transportation and safety – not just for vehicles but other kinds of road users – when he was interviewed by local TV stations in Houston, met with the Houston Police Department who analyze accidents and crashes, and engineers from the Department of Public Works.

What’s he been doing at UF?

Since joining the department in the Fall of 2019, Yujie has been keeping very busy. He has redesigned and taught GIS4113: Introduction to Spatial Networks, GIS6104: Spatial Networks, GEO3602: Urban and Business Geography, and has been developing GEO 4938/6938 Transportation Geography for Fall semester.

In addition to his teaching duties, Yujie has published 5 papers since joining the department: Impact of Coastal Hazards on Residents’ Spatial Accessibility to Health Services, Accessibility and Transportation Equity, Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach, Estimating road network accessibility during a hurricane evacuation: A case study of hurricane Irma in Florida, and Automated delineation of cancer service areas in northeast region of the United States: A network optimization approach. Currently he has a publication on food deserts offering a proposed solution to food insecurity for low income and socioeconomically disadvantaged neighborhoods in review.

Yujie has served as Guest Editor of the Accessibility and Transportation Equity special issue in Sustainability, serves on the Editorial Board of Southeastern Geographer, and is a Board Member of the Transportation Geography Specialty Group of the American Association of Geographers.

Additionally, Yujie has received the Ralph E. Powe Junior Faculty Enhancement Award from the Oak Ridge Associated Universities (ORAU) and won UFII COVID-19 Response SEED Funding for his project Socioeconomic Impacts of COVID-19: A Criminological Perspective (he’s hiring research assistants)

Finally, Yujie has been starting a lab – the Geospatial Network Analysis and Visualization Lab (GeoNAVI) and is preparing to welcome his new grad students in the fall.

How has he been holding up during the pandemic?

Although things may have been quiet on campus, Yujie has been busy with defenses and exams – he is a committee member on 2 PhD committees at LSU’s Geography & Anthropology Department – both students advanced to become PhD candidates. He’s also a committee member on 2 PhD dissertation defenses at USF – one in School of Geosciences and the other in the Department of Industrial and Management Systems Engineering – both students passed and earned their PhD!

Enjoying the nice weather with his family

Yujie has also been keeping busy at home. His children would really like their parents to stop working and play all day. So he has been trying hard to think of fun activities they can do together both inside and outside.

Sadly, Yujie left his beloved bicycle in his campus office when the lockdown happened, so he hasn’t been able to explore Gainesville from the back of a bike. He’s looking forward to reuniting with his bike and playing basketball, once that’s an option again.

College of Liberal Arts and Sciences
Follow Yujie on Twitter

A new course for Fall 2020!

Course description

Introduces a range of transportation concepts, theories, and models, including networks, modes, terminals, freight transportation, urban transportation, and environmental impacts. Also covers core methods and tools often used to study and analyze transportation systems, including spatial accessibility, spatial interaction, spatial networks, and GIS for transportation (GIS-T).

Course Objectives

After successful completion of this course students should be able to:
Have knowledge of the history and evolution of the U.S. transportation system;
Understand the geographic nature of transportation systems;
Investigate and solve various transportation problems using analytical methods and tools discussed in class and applied in labs.
prerequisites
Sophomore standing or higher. Entry level knowledge of GIS is preferred but not required.

Instructor: Dr. Yujie Hu – yujiehu@ufl.edu

Image courtesy Journal of Transport Geography

HUEstimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach

Yujie Hu, Changzhen Wang, Ruiyang Li, Fahui Wang

Article first published online: 15 JUN 2020 Journal of Transport Geography

DOI: 10.1016/j.jtrangeo.2020.102770

ABSTRACT: 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 including health information are compiled and distributed. The method (1) does not rely on intensive efforts in data preparation or access to advanced computing resources, (2) uses algorithms of varying complexity and computational time to estimate drive times of different trip lengths, and (3) accounts for both interzonal and intrazonal drive times. The core design samples ZIP code pairs with various intensities according to trip lengths and derives the drive times via Google Maps API, and the Google times are then used to adjust and improve some primitive estimates of drive times with low computational costs. The result provides a valuable resource for researchers.

Read the full publication at Journal of Transport Geography.

Image courtesy Sustainability

HUAccessibility and Transportation Equity

Anzhelika Antipova, Salima Sultana, Yujie Hu, & James P. Rhudy, Jr.

Article first published online: 30 APR 2020 Sustainability

DOI: 10.3390/su12093611

ABSTRACT: It is an honor to write an Editorial to this Special Issue (SI) of Sustainability. The SI addresses aspects of accessibility and equity and provides lessons from studies in various settings including the United States, China, Sweden, Poland, Peru, and Portugal to name a few, which collectively can contribute to a more sustainable and equitable transportation globally.
Accessibility is strongly tied to policymaking and thus has been extensively studied in a number of disciplines including transportation, geography, and urban planning. Accessibility can be defined in a variety of ways, recognizing influence by physical, political, economic, and social factors. It measures, for example, the potential of various opportunities for interaction, and the relative ease for people in an area to reach opportunities [1]. Various forms of accessibility are closely interdependent including transport availability and connectivity, communication, spatial, social, economic, physical, and temporal accessibility; thus, many novel measures are often taken to study different aspects and conceptualizations of accessibility. For example, as Moscicka et al. (2019) in this SI note, data from mobile phones can be used to study resident mobility, GPS-based location systems provide data on urban vehicle traffic, and the OpenStreetMap-based geospatial data are useful in research on urban public transportation networks, bicycle trails, as well as for studies on the availability of transportation for people with mobility restrictions. Additionally, Google Maps can provide an accurate measurement of travel times for different travel modes for various times of the day.
In this introduction to the Special Issue of Sustainability on accessibility and equity in transportation, we attempt to synthesize key lessons from the issue’s fifteen substantive articles. These involve accessibility-related lessons including accessibility improvement in railways; optimizations of cross-border road accessibility, intercity networks, and pedestrian access to public transportation; as well as various aspects in urban transportation planning such as urban mobility, integration of bike-sharing, and electronically powered personal mobility vehicles. Other lessons cover equity-related aspects of transportation including the provision of the maximally full information to underserved populations to lessen the burden of unequitable access to urban facilities, ensuring socially equitable transportation planning and reducing burdens in commuting cost among low-income commuters. Finally, remaining lessons link equity back to accessibility with discussions on accessibility to public transport for disabled as well as visually impaired people, and equitable job access by poor commuters.

Read the full publication at Sustainability.

 

 

Image courtesy Transportation Research Part D: Transport and Environment

HUEstimating road network accessibility during a hurricane evacuation: A case study of hurricane Irma in Florida

Yi-Jie Zhua, Yujie Hu, Jennifer M.Collins

Article first published online: 9 APR 2020 Transportation Research Part D: Transport and Environment

DOI: 10.1016/j.trd.2020.102334

ABSTRACT: Understanding the spatio-temporal road network accessibility during a hurricane evacuation—the level of ease of residents in an area in reaching evacuation destination sites through the road network—is a critical component of emergency management. While many studies have attempted to measure road accessibility (either in the scope of evacuation or beyond), few have considered both dynamic evacuation demand and characteristics of a hurricane. This study proposes a methodological framework to achieve this goal. In an interval of every six hours, the method first estimates the evacuation demand in terms of number of vehicles per household in each county subdivision (sub-county) by considering the hurricane’s wind radius and track. The closest facility analysis is then employed to model evacuees’ route choices towards the predefined evacuation destinations. The potential crowdedness index (PCI), a metric capturing the level of crowdedness of each road segment, is then computed by coupling the estimated evacuation demand and route choices. Finally, the road accessibility of each sub-county is measured by calculating the reciprocal of the sum of PCI values of corresponding roads connecting evacuees from the sub-county to the designated destinations. The method is applied to the entire state of Florida during Hurricane Irma in September 2017. Results show that I-75 and I-95 northbound have a high level of congestion, and sub-counties along the northbound I-95 suffer from the worst road accessibility. In addition, this research performs a sensitivity analysis for examining the impacts of different choices of behavioral response curves on accessibility results.

Read the full publication at Transportation Research Part D: Transport and Environment