Tianhong Zhao

According to our database, Tianhong Zhao authored at least 14 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Disentangling the hourly dynamics of mixed urban function: A multimodal fusion perspective using dynamic graphs.

Jinzhou Cao, Xiangxu Wang, Guanzhou Chen, Wei Tu, Xiaole Shen, Tianhong Zhao, Jiashi Chen, Qingquan Li

Inf. Fusion, 2025

2024

Graph convolutional networks for street network analysis with a case study of urban polycentricity in Chinese cities.

Ding Ma, Fangning He, Yang Yue, Renzhong Guo, Tianhong Zhao, Mingshu Wang

Int. J. Geogr. Inf. Sci., May, 2024

Deep online recommendations for connected E-taxis by coupling trajectory mining and reinforcement learning.

Wei Tu, Haoyu Ye, Ke Mai, Meng Zhou, Jincheng Jiang, Tianhong Zhao, Shengao Yi, Qingquan Li

Int. J. Geogr. Inf. Sci., February, 2024

ZenSVI: An Open-Source Software for the Integrated Acquisition, Processing and Analysis of Street View Imagery Towards Scalable Urban Science.

Koichi Ito, Yihan Zhu, Mahmoud Abdelrahman, Xiucheng Liang, Zicheng Fan, Yujun Hou, Tianhong Zhao, Rui Ma, Kunihiko Fujiwara, Jiani Ouyang, Matias Quintana, Filip Biljecki

CoRR, 2024

2023

Incorporating multimodal context information into traffic speed forecasting through graph deep learning.

Yatao Zhang, Tianhong Zhao, Song Gao, Martin Raubal

Int. J. Geogr. Inf. Sci., September, 2023

Sensitivity of measuring the urban form and greenery using street-level imagery: A comparative study of approaches and visual perspectives.

Filip Biljecki, Tianhong Zhao, Xiucheng Liang, Yujun Hou

Int. J. Appl. Earth Obs. Geoinformation, August, 2023

Sensing urban soundscapes from street view imagery.

Tianhong Zhao, Xiucheng Liang, Wei Tu, Zhengdong Huang, Filip Biljecki

Comput. Environ. Urban Syst., 2023

Developing a multiview spatiotemporal model based on deep graph neural networks to predict the travel demand by bus.

Tianhong Zhao, Zhengdong Huang, Wei Tu, Filip Biljecki, Long Chen

Int. J. Geogr. Inf. Sci., 2023

2022

Coupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction.

Tianhong Zhao, Zhengdong Huang, Wei Tu, Biao He, Rui Cao, Jinzhou Cao, Mingxiao Li

Comput. Environ. Urban Syst., 2022

Optimizing Living Material Delivery During the COVID-19 Outbreak.

Tianhong Zhao, Wei Tu, Zhixiang Fang, Xiaofan Wang, Zhengdong Huang, Shengwu Xiong, Meng Zheng

IEEE Trans. Intell. Transp. Syst., 2022

Correction: Yang et al. Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong-Hong Kong-Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data. Remote Sens. 2019, 11, 2215.

Chao Yang, Qingquan Li, Tianhong Zhao, Huizeng Liu, Wenxiu Gao, Tiezhu Shi, Minglei Guan, Guofeng Wu

Remote. Sens., 2022

2021

Collaboratively inspect large-area sewer pipe networks using pipe robotic capsules.

Yu Gu, Wei Tu, Qingquan Li, Tianhong Zhao, Dingyi Zhao, Song Zhu, Jiasong Zhu

Proceedings of the SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, 2021

2020

OCD: Online Crowdsourced Delivery for On-Demand Food.

Wei Tu, Tianhong Zhao, Baoding Zhou, Jincheng Jiang, Jizhe Xia, Qingquan Li

IEEE Internet Things J., 2020

2019

Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong-Hong Kong-Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data.

Chao Yang, Qingquan Li, Tianhong Zhao, Huizeng Liu, Wenxiu Gao, Tiezhu Shi, Minglei Guan, Guofeng Wu

Remote. Sens., 2019