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• W4384930600 startingPage "1446" @default.
• W4384930600 abstract "The analysis and evaluation of the service capacity of an urban public space is of great importance for optimizing spatial design and ensuring sustainable regeneration of the space. Point-of-interest (POI) data analysis is a common method for evaluating the performance of public space since it contains various geographical information about specific facilities. However, this method is incapable of providing intuitive and clear feedback on the usage of the space, such as visitor experience and satisfaction levels. In this paper, we present a hybrid approach that combines POI data with questionnaire surveys to comprehensively analyze and evaluate the service capacity of the facilities in a waterfront public space. By taking the Changning section of the Suzhou Creek in Shanghai as an example, we evaluate and verify the utilization rate and satisfaction level of public facilities based on this hybrid approach with three satisfaction factors: accessibility, landscape visual quality, and service functions. The results reveal that the service space that can be reached on foot provides the most satisfaction in terms of accessibility, followed by the space that can be reached by bicycle. When it comes to landscape visual quality, visitors are more concerned with the view around the facility than with the greenery. Regarding service functions, the service facility with beverage outlets, fitness, and small gatherings is more appealing. The proposed approach will be useful for further developing advanced public space evaluation strategies with real-time feedback capabilities, as well as for the intelligent design and long-term regeneration of future public spaces." @default.
• W4384930600 created "2023-07-22" @default.
• W4384930600 creator A5089933241 @default.
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• W4384930600 date "2023-07-20" @default.
• W4384930600 modified "2023-09-25" @default.
• W4384930600 title "Analysis and Evaluation of the Service Capacity of a Waterfront Public Space Using Point-of-Interest Data Combined with Questionnaire Surveys" @default.
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• W4384930600 doi "https://doi.org/10.3390/land12071446" @default.
• W4384930600 hasPublicationYear "2023" @default.
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