Author:
Deng Zikun,Weng Di,Liu Shuhan,Tian Yuan,Xu Mingliang,Wu Yingcai
Abstract
AbstractDeveloping effective visual analytics systems demands care in characterization of domain problems and integration of visualization techniques and computational models. Urban visual analytics has already achieved remarkable success in tackling urban problems and providing fundamental services for smart cities. To promote further academic research and assist the development of industrial urban analytics systems, we comprehensively review urban visual analytics studies from four perspectives. In particular, we identify 8 urban domains and 22 types of popular visualization, analyze 7 types of computational method, and categorize existing systems into 4 types based on their integration of visualization techniques and computational models. We conclude with potential research directions and opportunities.
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition
Reference218 articles.
1. Zheng, Y.; Capra, L.; Wolfson, O.; Yang, H. Urban computing. ACM Transactions on Intelligent Systems and Technology Vol. 5, No. 3, Article No. 38, 2014.
2. Pan, Z.; Liang, Y.; Wang, W.; Yu, Y.; Zheng, Y.; Zhang, J. Urban traffic prediction from spatio-temporal data using deep meta learning. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 1720–1730, 2019.
3. Zheng, Y.; Yi, X.; Li, M.; Li, R.; Shan, Z.; Chang, E.; Li, T. Forecasting fine-grained air quality based on big data. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2267–2276, 2015.
4. He, T. F.; Bao, J.; Ruan, S. J.; Li, R. Y.; Li, Y. H.; He, H.; Zheng, Y. Interactive bike lane planning using sharing bikes’ trajectories. IEEE Transactions on Knowledge and Data Engineering Vol. 32, No. 8, 1529–1542, 2020.
5. Weng, D.; Chen, R.; Zhang, J. H.; Bao, J.; Zheng, Y.; Wu, Y. C. Pareto-optimal transit route planning with multi-objective Monte-Carlo tree search. IEEE Transactions on Intelligent Transportation Systems Vol. 22, No. 2, 1185–1195, 2021.
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