Shi Beixiang, Simon Marvin, Yang Junyan

Keywords： High-density Urban Areas; Built Environment; Iterative Succession; Spatial Quality; Post Smart City

Abstract：

The high-density urban area is usually the most concentrated area of urban public facilities and public activities. However, high-density also causes problems such as poor ventilation, increased heat island effect, intensified pollution and broken walking space, which affect the normal crowd activities and even endanger human health. Under the development background of post smart city transformation, digital, information and artificial intelligence technology has begun to be deeply embedded in various urban systems, forming a new technology system supported by Robotics and Autonomous Systems (RAS), so as to solve the complex and diverse development problems of high-density urban areas and realize the sustainable development of people and cities. Based on this, according to the in-depth theoretical analysis of the characteristics of built environment and crowd activity, this paper reveals the high-intensity and high-height construction characteristics of high-density urban areas, as well as the spatial texture of small-scale and multi cluster, and finds the high-frequency dynamic interaction, cluster distribution, tidal surge and other activity characteristics. Thus, considered that even in the high-density built environment, through the optimization of spatial form, it could also play a positive role in promoting ventilation, reducing pollution and improving the comfort of physical environment. Therefore, this paper establishes the environmental quality improvement integration framework of “street landscape - physical environment - crowd activity”, and then through the coupling analysis of multi-source heterogeneous big data, explores the coupling mechanism of walking environment quality, physical environment quality, street landscape quality, and puts forward corresponding countermeasures to optimize and improve the quality of built environment according to different behavioral needs. On this basis, combined with the intervention of AI technology, this paper proposes feasible intelligent planning and automatic response strategy, which provides useful reference and guidance for the quality improvement of built environment in high-density urban areas.

Funds：

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