Multiperspective Evaluation Model for the Spatial Distribution of Public Service Facilities Based on Service Capability and Subjective Preferences
Publication: Journal of Urban Planning and Development
Volume 148, Issue 2
Abstract
Optimizing the spatial distribution of public service facilities (PSF) is important to promote the quality of life and the equitable distribution of public services. The spatial distribution of PSF is not only related to public service capability but also related to individual preference, so it is essential to integrate residents’ preferences and the service capability of PSF for PSF evaluation. This study proposes a new evaluation model for the spatial distribution of PSF by integrating four indicators. We perceive subjective preferences from Sina Weibo data to construct the online popularity indicator and construct three indicators including service area ratio, service population ratio, and service coordination to characterize the service capability of PSF by using land cover data, nighttime light data, road network data, and demographic data. We take Wuhan for example and show the veracity of results and the model’s superiority through field investigation and comparative analysis. The results show that the model has high accuracy and timeliness, and it is free from the influence of administrative boundaries. This study is expected to provide the auxiliary basis of PSF evaluation and decision-making for urban planning and relative departments of management.
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Acknowledgments
The authors thank the National Natural Fund Project (Project No. 71673268), the project of Urban Remote Sensing Data Processing and Multi-Source Integration in Central China (Project No. 111/611508101), and the Industry-University Cooperation Collaborative Education Project (PIE) for their support.
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Journal of Urban Planning and Development
Volume 148 • Issue 2 • June 2022
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© 2022 American Society of Civil Engineers.
History
Received: Apr 10, 2021
Accepted: Dec 17, 2021
Published online: Feb 22, 2022
Published in print: Jun 1, 2022
Discussion open until: Jul 22, 2022
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