涂伟, 曹劲舟, 高琦丽, 曹瑞, 方志祥, 乐阳, 李清泉. 融合多源时空大数据感知城市动态[J]. 武汉大学学报 ( 信息科学版), 2020, 45(12): 1875-1883. DOI: 10.13203/j.whugis20200535
引用本文: 涂伟, 曹劲舟, 高琦丽, 曹瑞, 方志祥, 乐阳, 李清泉. 融合多源时空大数据感知城市动态[J]. 武汉大学学报 ( 信息科学版), 2020, 45(12): 1875-1883. DOI: 10.13203/j.whugis20200535
TU Wei, CAO Jinzhou, GAO Qili, CAO Rui, FANG Zhixiang, YUE Yang, LI Qingquan. Sensing Urban Dynamics by Fusing Multi-sourced Spatiotemporal Big Data[J]. Geomatics and Information Science of Wuhan University, 2020, 45(12): 1875-1883. DOI: 10.13203/j.whugis20200535
Citation: TU Wei, CAO Jinzhou, GAO Qili, CAO Rui, FANG Zhixiang, YUE Yang, LI Qingquan. Sensing Urban Dynamics by Fusing Multi-sourced Spatiotemporal Big Data[J]. Geomatics and Information Science of Wuhan University, 2020, 45(12): 1875-1883. DOI: 10.13203/j.whugis20200535

融合多源时空大数据感知城市动态

Sensing Urban Dynamics by Fusing Multi-sourced Spatiotemporal Big Data

  • 摘要: 城市是人类活动的主要场所,是人流、物流、信息流和资金流的交换枢纽,具有高度的动态性和复杂性。智慧城市建设提供了卫星与无人机遥感、移动感知、社会感知、众包感知等多种时空感知大数据的数据获取手段,为分析城市空间、人类行为及其二者之间的交互等城市动态提供了新途径。介绍了城市动态感知的框架,论述了空间动态、人类行为动态、“空间-行为”交互动态感知等典型应用,讨论了融合多源时空大数据感知城市动态研究中存在的时空大数据不确定性、城市感知多视角学习、结果验证、城市多要素级联影响等问题。展望未来,城市动态研究应结合泛在物联网产生的实时数据,捕捉多维、多时空分辨率的多维城市动态,提升时空大数据在精细化城市治理中的应用深度,切实解决城市问题。

     

    Abstract: City is the place aggregated massive human activities. City is the exchange hub of population flow, goods flow, information flow and currency flow, which is highly dynamic and complex. Smart city provides various tools to acquire spatiotemporal big data, such as satellite and drone remote sensing, mobile sensing, social sensing, crowdsourcing sensing, etc., which enable us to sense urban dynamics. This paper introduces the framework of urban dynamic sensing, describes the typical applications of spatial dynamics, human behavior dynamics and space-behavior interaction dynamics, and discusses the problems, such as the uncertainty in spatiotemporal big data, the multi-view ensemble learning in urban sensing, the verification of the urban dynamic results and the cascading influence of multi-urban factors. Outlooking the future, the study of urban dynamics should combine with real-time Internet of things data to sense multi-dimensional, multi-spatiotemporal resolution urban dynamic to enable refined urban governance and to effectively solve urban problems.

     

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