Spatial accessibility analysis and location optimization of emergency shelters in Deyang

Abstract

AbstractThe 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