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100			_aHuang, Bo _958390
245			_aEvaluating and characterizing urban vibrancy using spatial big data: _bshanghai as a case study/
260			_bSage, _c2020.
300			_aVol. 47, Issue 9, 2020, ( 1543–1559 p.)
520			_aAlthough people may recognize urban vibrancy when they see or sense it, developing direct and comprehensive measures of urban vibrancy remains a challenge. In the context of intense global competition, there is an increased realization that urban vibrancy is vital to the social and economic sustainability of cities. Such vibrancy may be significantly shaped by the urban built environment, yet we know little about the close connections between vibrancy and urban built environments. Empowered by newly available sources of spatial big data, which provide enormous amounts of information on both human dynamics and the built environment, this paper proposes a framework for evaluating and characterizing urban vibrancy. Thus far, vibrancy measures have mostly used single-source data that hardly reflect the multifaceted manifestations of urban vibrancy. Therefore, we propose a more comprehensive measure of urban vibrancy, extracted as the common latent factor from multiple surface attributes. Using the proposed framework, we evaluated and mapped the spatial dynamics of vibrancy in Shanghai, a typical large city in post-reform China, and investigated the associations between vibrancy and various urban built environment indicators. The evidence shows that the horizontal built-up density, rather than vertical height, is the leading generator of vibrancy in Shanghai, followed by the density and mixture of urban functions, accessibility, and walkability. In this vein, we contribute to current debates and future planning practices regarding vibrant spaces in large cities. This proposed evaluation framework, equipped with spatial big data, can benefit future urban studies.
700			_aZhou, Yulun _958391
700			_aLi, Zhigang _958392
700			_aSong, Yimeng _958393
700			_aCai, Jixuan _958394
700			_aTu, Wei _958395
773	0		_08876 _917104 _dLondon Pion Ltd. 2010 _tEnvironment and planning B: planning and design (Urban Analytics and City Science) _x1472-3417
856			_uhttps://doi.org/10.1177/2399808319828730
942			_2ddc _cEJR
999			_c14871 _d14871