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Research on Time-Space Behavior of Big Data City Based on Cloud Computing Concept

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DOI: 10.25236/IIICEC.2019.061


Liu Ming, Gao Wenjin, Qi Guixia

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Gao Wenjin


understanding the movement behavior and spatial structure of urban population is of great significance to urban planning, traffic management and emergency response. As an important component of smart cities, smart travel can provide effective behavioral planning countermeasures for reducing urban traffic volume and optimizing travel time-space distribution, and provide effective technical support for optimizing urban planning and traffic planning theories and methods. This paper holds that the change of research methods of urban spatio-temporal behavior in the era of big data based on cloud computing mainly depends on the mining, processing and application of network or mobile information equipment data reflecting residents' spatio-temporal behavior. The application prospect of the new human-oriented urban planning and management based on time-space behavior guides the intelligent and sustainable development of the city.


Cloud Computing; Big Data; Research Methods of Urban Temporal and Spatial Behavior