| Multiscale dynamic human mobility flow dataset in the US during the COVID-19 epidemic Y Kang, S Gao, Y Liang, M Li, J Rao, J Kruse Scientific data 7 (1), 390, 2020 | 218 | 2020 |
| A ST-CRF map-matching method for low-frequency floating car data X Liu, K Liu, M Li, F Lu IEEE Transactions on Intelligent Transportation Systems 18 (5), 1241-1254, 2016 | 92 | 2016 |
| Reconstruction of human movement trajectories from large-scale low-frequency mobile phone data M Li, S Gao, F Lu, H Zhang Computers, Environment and Urban Systems 77, 101346, 2019 | 76 | 2019 |
| Fine-grained prediction of urban population using mobile phone location data J Chen, T Pei, SL Shaw, F Lu, M Li, S Cheng, X Liu, H Zhang International Journal of Geographical Information Science 32 (9), 1770-1786, 2018 | 70 | 2018 |
| Predicting future locations of moving objects with deep fuzzy-LSTM networks M Li, F Lu, H Zhang, J Chen Transportmetrica A: Transport Science 16 (1), 119-136, 2020 | 50 | 2020 |
| Prediction of human activity intensity using the interactions in physical and social spaces through graph convolutional networks M Li, S Gao, F Lu, K Liu, H Zhang, W Tu International Journal of Geographical Information Science 35 (12), 2489-2516, 2021 | 40 | 2021 |
| Predicting the spatiotemporal legality of on-street parking using open data and machine learning S Gao, M Li, Y Liang, J Marks, Y Kang, M Li Annals of GIS 25 (4), 299-312, 2019 | 35 | 2019 |
| Coupling graph deep learning and spatial-temporal influence of built environment for short-term bus travel demand prediction T Zhao, Z Huang, W Tu, B He, R Cao, J Cao, M Li Computers, Environment and Urban Systems 94, 101776, 2022 | 28 | 2022 |
| Dynamic estimation of individual exposure levels to air pollution using trajectories reconstructed from mobile phone data M Li, S Gao, F Lu, H Tong, H Zhang International journal of environmental research and public health 16 (22), 4522, 2019 | 28 | 2019 |
| A privacy‐preserving framework for location recommendation using decentralized collaborative machine learning J Rao, S Gao, M Li, Q Huang Transactions in GIS 25 (3), 1153-1175, 2021 | 26 | 2021 |
| Predicting future locations with deep fuzzy-LSTM network LI Mingxiao, Z Hengcai, QIU Peiyuan, C Shifen, C Jie, LU Feng Acta Geodaetica et Cartographica Sinica 47 (12), 1660, 2018 | 12 | 2018 |
| Automatic urban road network extraction from massive GPS trajectories of taxis S Gao, M Li, J Rao, G Mai, T Prestby, J Marks, Y Hu Handbook of Big Geospatial Data, 261-283, 2021 | 11 | 2021 |
| Relationships between building attributes and COVID-19 infection in London H Tong, M Li, J Kang Building and Environment 225, 109581, 2022 | 10 | 2022 |
| Optimization on arrangement of precaution areas serving for ships’ routeing in the Taiwan strait based on massive AIS data J Chen, F Lu, M Li, P Huang, X Liu, Q Mei Data Mining and Big Data: First International Conference, DMBD 2016, Bali …, 2016 | 9 | 2016 |
| Using multi-sourced big data to correlate sleep deprivation and road traffic noise: A US county-level ecological study H Tong, JL Warren, J Kang, M Li Environmental research 220, 115029, 2023 | 8 | 2023 |
| Fine-grained crowd distribution forecasting with multi-order spatial interactions using mobile phone data M Li, S Gao, P Qiu, W Tu, F Lu, T Zhao, Q Li Transportation Research Part C: Emerging Technologies 144, 103908, 2022 | 8 | 2022 |
| An enhanced model for evacuation vulnerability assessment in urban areas J Chen, T Pei, M Li, C Song, T Ma, F Lu, SL Shaw Computers, Environment and Urban Systems 84, 101540, 2020 | 8 | 2020 |
| Fine-grained dynamic population mapping method based on large-scale sparse mobile phone data M Li, H Zhang, J Chen 2019 20th IEEE International Conference on Mobile Data Management (MDM), 473-478, 2019 | 8 | 2019 |
| The near-real-time prediction of urban population distributions based on mobile phone location data C Lina, WU Sheng, C Jie, LI Mingxiao, LU Feng Journal of Geo-Information Science 20 (4), 523-531, 2018 | 8 | 2018 |
| A data-driven approach to understanding and predicting the spatiotemporal availability of street parking M Li, S Gao, Y Liang, J Marks, Y Kang, M Li Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances …, 2019 | 6 | 2019 |
Song GaoAssociate Professor of Geographic Information Science, University of Wisconsin-Madison在 wisc.edu 的电子邮件经过验证
