Yongxi Gong

ORCID: 0000-0002-7395-3334
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About
Contact & Profiles
Research Areas
  • Urban Transport and Accessibility
  • Human Mobility and Location-Based Analysis
  • Transportation Planning and Optimization
  • Urban and Freight Transport Logistics
  • Impact of Light on Environment and Health
  • Geographic Information Systems Studies
  • Data Management and Algorithms
  • Computational Geometry and Mesh Generation
  • Constraint Satisfaction and Optimization
  • Remote Sensing and Land Use
  • Environmental Impact and Sustainability
  • Video Analysis and Summarization
  • Educational Environments and Student Outcomes
  • Regional Development and Environment
  • Pharmaceutical and Antibiotic Environmental Impacts
  • Urban, Neighborhood, and Segregation Studies
  • Evaluation Methods in Various Fields
  • Smart Cities and Technologies
  • Medical Research and Treatments
  • Environmental Changes in China
  • Urban and spatial planning
  • Sustainable Supply Chain Management
  • Evacuation and Crowd Dynamics
  • Vehicle emissions and performance
  • Wireless Communication Networks Research

Harbin Institute of Technology
2012-2025

Urban Planning & Design Institute of Shenzhen (China)
2018-2021

Ministry of Natural Resources
2018-2019

University Town of Shenzhen
2015

Peking University
2008-2012

State Key Laboratory of Remote Sensing Science
2012

10.1016/j.jtrangeo.2015.01.016 article EN Journal of Transport Geography 2015-02-01

Public medical service facilities are among the most basic needs of public and directly related to residents' health. The balanced development is great significance. can be divided into different levels according their equipment, catchment, quality, which very important but has been ignored for a long time in accessibility evaluations. In this research, based on hospital population datasets Shenzhen, we propose hierarchical two-step floating catchment area (H2SFCA) method evaluate spatial...

10.3390/ijerph16071150 article EN International Journal of Environmental Research and Public Health 2019-03-30

Dockless bike-sharing (DBS) plays a crucial role in solving the “last-mile” problem for metro trips. However, bike–metro transfer usage varies by time and flows. This study explores nonlinear relationship between built environment Shenzhen, considering different times flows while incorporating spatial dependence to improve model accuracy. We integrated smart card records DBS data identify trips categorized them into four types: morning access, egress, evening egress. Using random forest...

10.3390/su17010251 article EN Sustainability 2025-01-01

This study addresses the growing mental health challenges among university students, with a particular focus on depression, by examining role of campus greenness in mitigating its effects. In contrast to majority studies that concentrate environments Western countries, this research uniquely investigates how variations density and form within Chinese context influence depression students. By analyzing three distinct types campuses Macau, also reflects broader implications for across China. A...

10.1186/s12889-025-21356-9 article EN cc-by-nc-nd BMC Public Health 2025-03-06

10.1016/j.scitotenv.2019.05.459 article EN The Science of The Total Environment 2019-06-04

Bike-sharing improves individual mobility, considerably reshaping the landscape of job accessibility and commuting time. Existing empirical studies in urban transportation involving usually collect survey data at aggregate level. A comprehensive understanding influence bike-sharing on city level is still missing developing countries. Using mobile phone Beijing, this study addresses these questions with a mode model cumulative model. The results indicate that could lead to decrease time an...

10.1080/23249935.2022.2043950 article EN Transportmetrica A Transport Science 2022-03-25

Residents’ activity space reflects multiple aspects of human life related to space, time, and type activity. How measure the at geographic scales remains a problem be solved. Recently, emergence big data such as mobile phone point interest has brought access massive geo-tagged datasets identify explore relationship with built environment. In this research, we propose new method three types urban residents’ spaces—i.e., maintenance commuting recreational space—using data. The proposed...

10.3390/ijgi9040241 article EN cc-by ISPRS International Journal of Geo-Information 2020-04-12

Understanding the characteristics of intra-urban trips is essential to get a deep insight dynamic aspects urban system and make planning. We explore spatiotemporal patterns human using metro smartcard records Shenzhen city. Through statistics millions records, we found that trips: (a) have two significant peak hours over day; (b) are different between weekday weekend; (c) periodicity. The temporal owe living working habit inhabitants. result also shows passengers' volumes, as well patterns,...

10.1109/geoinformatics.2012.6270316 article EN 2012-06-01

10.1007/s11390-009-9246-z article EN Journal of Computer Science and Technology 2009-05-01

Locality description is the most common spatial activity in everyday life, and decided by cognition. In cognition, knowledge often structured hierarchically results hierarchical locality descriptions. this paper, we propose structural hierarchy of based on landmarks topological relationship disjoint, present two types from point view Cognitive computational aspects are provided to generate Finally, use three cases demonstrate proposed methods.

10.1109/geoinformatics.2010.5567818 article EN 2010-06-01

Cycling has gained global popularity for its health benefits and positive urban impacts. To effectively promote cycling, early studies have extensively investigated the relationship between cycling behaviors environmental factors, especially cyclists' preferences when making route decisions. However, these often struggle to comprehensively describe detailed procedures at a large scale due data limitations, they tend overlook complex nature of preferences. address issues, we propose novel...

10.48550/arxiv.2409.03148 preprint EN arXiv (Cornell University) 2024-09-04
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