Spatial accessibility analysis and location optimization of emergency shelters in Deyang

Abstract

The selection and planning of the location of emergency shelters have a crucial impact on the safety of residents and cities. In this paper, based on multivariate open geographic data, the Gaussian two-step floating catchment area method, K-means clustering, and particle swarm optimization algorithm methods are utilized to carry out a spatial accessibility analysis and location optimization of emergency shelters in Deyang City, Sichuan Province, China. The study shows that: (1) Deyang City’s emergency shelters are higher than the government’s relevant standard requirements in terms of major indicators such as single building area, total area and per capita shelter area. (2) The spatial distribution of emergency shelters in the study area is uneven and unreasonable, with accessibility from the urban center outwards, exhibiting a “high-low” distribution pattern. (3) The study suggests that 10 new emergency shelters can reduce the number of accessible blind areas by 43.31%. The study recommends that the assessment and construction of emergency shelter facilities in rural areas in China and globally should be emphasized. Reliable recommendations for improvement of emergency shelter planning in Deyang city are provided in the study results.

Keywords:

• Spatial accessibility
• Gaussian two-step floating catchment area method
• K-means clustering
• particle swarm optimization algorithm
• location optimization

Author contribution

Conceptualization: Yunfeng Hu; methodology: Zuopei Zhang, Yunfeng Hu; formal analysis and investigation: Zuopei Zhang; writing – original draft preparation: Zuopei Zhang; writing – review and editing: Zuopei Zhang, Yunfeng Hu, Wei Lu, Wei Cao; visualization: Zuopei Zhang; project administration: Yunfeng Hu; funding acquisition: Yufeng Hu; supervision: Yunfeng Hu. All authors have read and agreed to the published version of the manuscript.

Acknowledgments

We thank all authors for their contributions to this study. We thank the Network Security and Information Program of the Chinese Academy of Sciences (CAS-WX2021SF-0106),the National Natural Science Foundation of China (41977421) and the Key Project of Innovation LREIS(KPI011) for support.

Disclosure statement

The authors declare no conflict of interests.

Data deposition

The data used in the study are publicly available, and the way in which they were obtained is shown in Table 1.

Data availability statement

The data used in the study and the access to them are available in Table 1. The code used during the current study is available from the corresponding author on reasonable request.

Additional information

Funding

This research was supported by the Network Security and Information Program of the Chinese Academy of Sciences under Grant CAS-WX2021SF-0106, and National Natural Science Foundation of China under Grant 41977421 and Key Project of Innovation LREIS (KPI011).