Di Zhu
Di Zhu
Assistant Professor, GeoDI Lab, University of Minnesota, Twin Cities | PKU | UCL
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Zitiert von
Zitiert von
Social sensing from street-level imagery: A case study in learning spatio-temporal urban mobility patterns
F Zhang, D Zhu, L Wu, Y Liu
ISPRS Journal of Photogrammetry and Remote Sensing 153, 48-58, 2019
Spatial interpolation using conditional generative adversarial neural networks
D Zhu, X Cheng, F Zhang, X Yao, Y Gao, Y Liu
International Journal of Geographical Information Science 34 (4), 735-758, 2020
Understanding place characteristics in geographic contexts through graph convolutional neural networks
D Zhu, F Zhang, S Wang, Y Wang, X Cheng, Z Huang, Y Liu
Annals of the American Association of Geographers 110 (2), 408-420, 2020
Uncovering inconspicuous places using social media check-ins and street view images
F Zhang, J Zu, M Hu, D Zhu, Y Kang, S Gao, Y Zhang, Z Huang
Computers, Environment and Urban Systems 81, 101478, 2020
Street as a big geo-data assembly and analysis unit in urban studies: A case study using Beijing taxi data
D Zhu, N Wang, L Wu, Y Liu
Applied Geography 86, 152-164, 2017
Spatial origin-destination flow imputation using graph convolutional networks
X Yao, Y Gao, D Zhu, E Manley, J Wang, Y Liu
IEEE Transactions on Intelligent Transportation Systems 22 (12), 7474-7484, 2020
Inferring spatial interaction patterns from sequential snapshots of spatial distributions
D Zhu, Z Huang, L Shi, L Wu, Y Liu
International Journal of Geographical Information Science 32 (4), 783-805, 2018
A framework for mixed-use decomposition based on temporal activity signatures extracted from big geo-data
L Wu, X Cheng, C Kang, D Zhu, Z Huang, Y Liu
International Journal of Digital Earth 13 (6), 708-726, 2020
A stepwise spatio-temporal flow clustering method for discovering mobility trends
X Yao, D Zhu, Y Gao, L Wu, P Zhang, Y Liu
Ieee Access 6, 44666-44675, 2018
Spatial regression graph convolutional neural networks: A deep learning paradigm for spatial multivariate distributions
D Zhu, Y Liu, X Yao, MM Fischer
GeoInformatica 26 (4), 645-676, 2022
Quantifying the scale effect in geospatial big data using semi-variograms
L Chen, Y Gao, D Zhu, Y Yuan, Y Liu
PloS one 14 (11), e0225139, 2019
Mapping human activity volumes through remote sensing imagery
X Xing, Z Huang, X Cheng, D Zhu, C Kang, F Zhang, Y Liu
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2020
Terrain feature-aware deep learning network for digital elevation model superresolution
Y Zhang, W Yu, D Zhu
ISPRS Journal of Photogrammetry and Remote Sensing 189, 143-162, 2022
Analytical methods and applications of spatial interactions in the era of big data
Y Liu, X Yao, Y Gong, C Kang, X Shi, F Wang, J Wang, Y Zhang, P Zhao, ...
Acta Geographica Sinica 75 (7), 1523-1538, 2020
Sensing population distribution from satellite imagery via deep learning: Model selection, neighboring effects, and systematic biases
X Huang, D Zhu, F Zhang, T Liu, X Li, L Zou
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021
Revealing the spatial shifting pattern of COVID-19 pandemic in the United States
D Zhu, X Ye, S Manson
Scientific reports 11 (1), 8396, 2021
Visualizing spatial interaction characteristics with direction-based pattern maps
X Yao, L Wu, D Zhu, Y Gao, Y Liu
Journal of Visualization, 1-15, 2019
刘瑜, 詹朝晖, 朱递, 柴彦威, 马修军, 邬伦
武汉大学学报 (信息科学版) 43 (3), 327-335, 2018
A generalized heterogeneity model for spatial interpolation
P Luo, Y Song, D Zhu, J Cheng, L Meng
International Journal of Geographical Information Science 37 (3), 634-659, 2023
The scale effect on spatial interaction patterns: An empirical study using taxi OD data of Beijing and Shanghai
S Zhang, D Zhu, X Yao, X Cheng, H He, Y Liu
Ieee Access 6, 51994-52003, 2018
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