World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
13005
World Ranking
5025
National Ranking
675

Overview

Yu Liu is a researcher affiliated with Peking University in China, specializing primarily in social sciences with significant contributions to transportation and urban studies.

Their research spans several subfields, including:

  • Transportation
  • Global and Planetary Change
  • Building and Construction
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition

Yu Liu's work extensively covers topics such as:

  • Human Mobility and Location-Based Analysis
  • Urban Transport and Accessibility
  • Transportation Planning and Optimization
  • Land Use and Ecosystem Services
  • Impact of Light on Environment and Health
  • Geographic Information Systems Studies
  • Traffic Prediction and Management Techniques

They have published frequently in venues including:

  • arXiv (Cornell University)
  • International Journal of Geographical Information Systems
  • SSRN Electronic Journal
  • Computers Environment and Urban Systems
  • Cities

Recent notable publications by Yu Liu include:

  • "A review of urban physical environment sensing using street view imagery in public health studies," 2020, Annals of GIS
  • "Understanding Place Characteristics in Geographic Contexts through Graph Convolutional Neural Networks," 2020, Annals of the American Association of Geographers
  • "Spatial Origin-Destination Flow Imputation Using Graph Convolutional Networks," 2020, IEEE Transactions on Intelligent Transportation Systems
  • "Access to hospitals: Potential vs. observed," 2020, Cities
  • "A national-scale assessment of land subsidence in China's major cities," 2024, Science

Yu Liu frequently collaborates with several researchers, including:

  • Zhou Huang
  • Fan Zhang
  • Chaogui Kang
  • Yongxi Gong
  • Xiaojian Chen

Best Publications

  • T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction

    Ling Zhao;Yujiao Song;Chao Zhang;Yu Liu

  • Social Sensing: A New Approach to Understanding Our Socioeconomic Environments

    Yu Liu;Xi Liu;Song Gao;Li Gong

  • Measuring human perceptions of a large-scale urban region using machine learning

    Fan Zhang;Fan Zhang;Fan Zhang;Bolei Zhou;Liu Liu;Yu Liu

  • DASNet: Dual Attentive Fully Convolutional Siamese Networks for Change Detection in High-Resolution Satellite Images

    Jie Chen;Ziyang Yuan;Jian Peng;Li Chen

  • Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

    Yu Liu;Zhengwei Sui;Chaogui Kang;Yong Gao

  • Understanding intra-urban trip patterns from taxi trajectory data

    Yu Liu;Chaogui Kang;Song Gao;Yu Xiao

  • Correlating mobile phone usage and travel behavior – A case study of Harbin, China

    Yihong Yuan;Martin Raubal;Martin Raubal;Yu Liu

  • Discovering Spatial Interaction Communities from Mobile Phone Data

    Song Gao;Yu Liu;Yaoli Wang;Xiujun Ma

  • Inferring trip purposes and uncovering travel patterns from taxi trajectory data

    Li Gong;Xi Liu;Lun Wu;Yu Liu

  • Intra-urban human mobility and activity transition: evidence from social media check-in data.

    Lun Wu;Ye Zhi;Zhengwei Sui;Yu Liu

  • A review of urban physical environment sensing using street view imagery in public health studies

    Yuhao Kang;Fan Zhang;Song Gao;Hui Lin

  • Understanding Urban Traffic-Flow Characteristics: A Rethinking of Betweenness Centrality

    Song Gao;Yaoli Wang;Yong Gao;Yu Liu

  • Everyday space–time geographies: using mobile phone-based sensor data to monitor urban activity in Harbin, Paris, and Tallinn

    R. Ahas;A. Aasa;Y. Yuan;M. Raubal

  • Automatic Pavement Crack Detection by Multi-Scale Image Fusion

    Haifeng Li;Dezhen Song;Yu Liu;Binbin Li

  • Incorporating spatial interaction patterns in classifying and understanding urban land use

    Xi Liu;Chaogui Kang;Li Gong;Yu Liu

  • ModEco: an integrated software package for ecological niche modeling

    Qinghua Guo;Yu Liu

  • Spatial interpolation using conditional generative adversarial neural networks

    Di Zhu;Di Zhu;Ximeng Cheng;Fan Zhang;Fan Zhang;Xin Yao

  • Representing place locales using scene elements

    Fan Zhang;Fan Zhang;Ding Zhang;Yu Liu;Hui Lin

  • Exploring human movements in Singapore: a comparative analysis based on mobile phone and taxicab usages

    Chaogui Kang;Stanislav Sobolevsky;Yu Liu;Carlo Ratti

  • Social sensing from street-level imagery: A case study in learning spatio-temporal urban mobility patterns

    Fan Zhang;Lun Wu;Di Zhu;Di Zhu;Yu Liu

  • Understanding Place Characteristics in Geographic Contexts through Graph Convolutional Neural Networks

    Di Zhu;Fan Zhang;Fan Zhang;Shengyin Wang;Yaoli Wang

  • Towards Estimating Urban Population Distributions from Mobile Call Data

    Chaogui Kang;Yu Liu;Xiujun Ma;Lun Wu

  • Analyzing and geo-visualizing individual human mobility patterns using mobile call records

    Chaogui Kang;Song Gao;Xing Lin;Yu Xiao

  • Difference of urban development in China from the perspective of passenger transport around Spring Festival

    Jun Xu;Aoyong Li;Dong Li;Yu Liu

  • Pervasive location acquisition technologies: Opportunities and challenges for geospatial studies

    Yongmei Lu;Yu Liu

  • Spatial Origin-Destination Flow Imputation Using Graph Convolutional Networks

    Xin Yao;Yong Gao;Di Zhu;Ed Manley

Frequent Co-Authors

Song Gao
Song Gao University of Wisconsin–Madison
Qinghua Guo
Qinghua Guo Chinese Academy of Sciences
Fahui Wang
Fahui Wang Louisiana State University
Hui Lin
Hui Lin Jiangxi Normal University
Xinyue Ye
Xinyue Ye Texas A&M University
Mei-Po Kwan
Mei-Po Kwan Chinese University of Hong Kong
Martin Raubal
Martin Raubal ETH Zurich
Michael F. Goodchild
Michael F. Goodchild University of California, Santa Barbara
Tom K. Hei
Tom K. Hei Columbia University

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