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Open AccessArticle

Urban Vitality Area Identification and Pattern Analysis from the Perspective of Time and Space Fusion

by Shaojun Liu 1,2,3, Ling Zhang 1,2,3,* and Yi Long 1,2,3
1
Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
2
State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China
3
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(15), 4032; https://doi.org/10.3390/su11154032
Received: 28 June 2019 / Revised: 22 July 2019 / Accepted: 23 July 2019 / Published: 25 July 2019
(This article belongs to the Section Sustainable Urban and Rural Development)
Urban vitality provides an important basis for evaluating urban development and spatial balance. In the era of big data, the quantitative analysis of urban vitality has become a research hotspot in the field of urban sustainability and planning research. However, time variation characteristics are often neglected, which leads to one-sidedness in the pattern analysis of urban vitality. In this paper, a method for extracting vitality areas and integrating spatiotemporal features clustering is proposed. The method is used to divide urban space into multiple vitality areas scientifically. The spatial and temporal distribution patterns of urban vitality areas are found, and the driving factors of various vitality patterns are analyzed by combining points of interest (POI)-based land use characteristics. To illustrate this method, this paper takes Nanjing city as an example. One week’s worth of mobile phone data indicated that Nanjing has 10 and 8 vitality areas on weekdays and weekends, respectively. The spatial and temporal distribution patterns of the vitality areas and their correlation with land use were analyzed, which proved that POI density and entropy have strong correlations with urban vitality. View Full-Text
Keywords: urban vitality; mobile phone data; self-organizing map (SOM); spatiotemporal pattern analysis urban vitality; mobile phone data; self-organizing map (SOM); spatiotemporal pattern analysis
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Liu, S.; Zhang, L.; Long, Y. Urban Vitality Area Identification and Pattern Analysis from the Perspective of Time and Space Fusion. Sustainability 2019, 11, 4032.

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