Exploring the Relationship between Potential and Actual of Urban Waterfront Spaces in Wuhan Based on Social Networks

Jing Wu, Jingwen Li and Yue Ma
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Jing Wu: School of Urban Design, Wuhan University, Wuhan 430072, China
Jingwen Li: School of Urban Design, Wuhan University, Wuhan 430072, China
Yue Ma: School of Urban Design, Wuhan University, Wuhan 430072, China

Sustainability, 2019, vol. 11, issue 12, 1-18

Abstract: The geographical location of residents and the distribution of points of interest (POI) are key factors affecting the spatial value of urban waterfronts. This study designed an association scheme based on tourists’ geographical location information (obtained from social networks) and the distribution of facilities around lakes to evaluate the spatial value of urban waterfronts. Accordingly, it explored the causes of the current condition of the waterfronts. Using the distribution status of eight types of facilities, a multivariate regression model was established to predict the number of tourists that the lakes attract. Predicted results were compared with the actual condition. The clustering degree of various POI in the waterfronts was graded by using the kernel density estimation, and the difference between the predicted results and actual value was analyzed to reveal the current condition of the urban waterfronts and the reasons for their formation. On the basis of this survey, the situation of 21 major lakes within the third ring road in Wuhan, China was investigated. Results show that existing waterfronts in some areas have a considerable number of users, but the facilities fail to meet their needs. Thus, Wuhan city’s waterfront space needs to be used more effectively. This study can help with making targeted recommendations with reference to future city waterfront planning.

Keywords: waterfronts; social networks; point of interest; multiple linear regression; kernel density estimation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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