Visualizing Temporal and Spatial Distribution Characteristic of Traffic Accidents in China

Yingliu Yang and Lianghai Jin ()
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Yingliu Yang: Department of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
Lianghai Jin: Department of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China

Sustainability, 2022, vol. 14, issue 21, 1-16

Abstract: The interaction among social economy, geography, and environment leads to the occurrence of traffic accidents, which shows the relationship between time and space. Therefore, it is necessary to study the temporal and spatial correlation and provide a theoretical basis for formulating traffic accident safety management policies. This paper aims to explore the traffic accident patterns in 31 provinces of China by using statistical analysis and spatial clustering analysis. The results show that there is a significant spatial autocorrelation among traffic accidents in various provinces and cities in China, which means that in space, the number of traffic accidents and deaths is high with high aggregation and low with low aggregation. Positive spatial autocorrelation is primarily concentrated in the southeast coastal areas, while negative spatial autocorrelation is mainly concentrated in the western areas. Jiangsu, Anhui, Fujian, and Shandong are typical areas of traffic accidents, which deviate from the overall positive spatial autocorrelation trend. Traffic accidents in Sichuan are much more serious than those in neighboring provinces and cities; however, in recent years, this situation has disappeared.

Keywords: road traffic accidents; temporal and spatial characteristics; spatial clustering; accident analysis; spatial autocorrelation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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