Evaluating the community commercial vitality using multi-source data: a case study of Hangzhou, China

Abstract

“Urban vitality” is a crucial component in evaluating urban quality. However, current research rarely establishes specific vitality evaluation frameworks using multi-source data. Commercial activities at the community scale play a pivotal role in urban development. Therefore, this paper selected Hangzhou City in China as an example, and employed the nighttime light remote sensing data as well as the social sensing data, including Street View Feature (SVF) data, mobile signaling data, and Points of Interest (POI) data to assess the commercial vitality of communities in urban areas. A comprehensive vitality index assessment method for evaluating the commercial vitality of communities was proposed by the entropy weight method. The spatial distribution characteristics of the commercial vitality values in urban area of Hangzhou are explored. Then, the validation was conducted to reveal the reliability of the results. Finally, the relevant policy recommendations were proposed. Findings revealed that SVF and POI demonstrated superiority over mobile signaling data and nighttime light data in assessing commercial vitality. Moreover, significant disparities existed in individual vitality indices in which further highlight the spatial inequality among these indices. The results can provide valuable scientific references for urban planning and governance as well as achieving sustainable development within urban communities.