The following publications are possibly variants of this publication:
- Big enterprise registration data imputation: Supporting spatiotemporal analysis of industries in ChinaFa Li, Zhipeng Gui, Huayi Wu, Jianya Gong, Yuan Wang, Siyu Tian, Jiawen Zhang. urban, 70:9-23, 2018. [doi]
- A topology-based approach to identifying urban centers in America using multi-source geospatial big dataZheng Ren, Stefan Seipel, Bin Jiang 0004. urban, 107:102045, January 2024. [doi]
- Causal Identification Based on Compressive Sensing of Air Pollutants Using Urban Big DataMingwei Li, Jinpeng Li, Shuangning Wan, Hao Chen, Chao Liu. access, 8:109207-109216, 2020. [doi]
- Using spatiotemporal patterns to optimize Earth Observation Big Data access: Novel approaches of indexing, service modeling and cloud computingJizhe Xia, Chaowei Yang, Qingquan Li. urban, 72:191-203, 2018. [doi]
- Portraying the spatial dynamics of urban vibrancy using multisource urban big dataWei Tu, Tingting Zhu, Jizhe Xia, Yulun Zhou, Yani Lai, Jincheng Jiang, Qingquan Li. urban, 80:101428, 2020. [doi]
- A Gaussian Bayesian model to identify spatio-temporal causalities for air pollution based on urban big dataJulie Yixuan Zhu, Yu Zheng, Xiuwen Yi, Victor O. K. Li. infocom 2016: 3-8 [doi]