Determining the Spatial and Temporal Distribution of Traffic Accidents Using GIS-based Data in Tabriz

Iman  Dianat; Mohammad  Sadegh Masoumi; Homayoun Sadeghi  Bazargani; Gholam Hossein  Safari; Sepideh  Harzand-Jadidi

doi:10.18502/ijre.v20i4.18869

Iman Dianat Professor of Occupational Health Engineering, Department of Occupational Health, School of Health, Tabriz University of Medical Sciences, Tabriz, Iran
Mohammad Sadegh Masoumi M.sc of Health, Safety and Environment Management, Department of Occupational Health, School of Health, Tabriz University of Medical Sciences, Tabriz, Iran
Homayoun Sadeghi Bazargani Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
Gholam Hossein Safari Assistant Professor of Environmental Health Engineering, Department of Environmental Health, School of Health, Tabriz University of Medical Sciences, Tabriz, Iran
Sepideh Harzand-Jadidi M.sc of Health and Traffic Safety, Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran

DOI: https://doi.org/10.18502/ijre.v20i4.18869

Keywords: Accident, Spatial analysis, Tabriz, Geographic Information Systems

Abstract

Background and Objectives: One of the most important steps in reducing traffic accidents is the accurate recording of the spatial information of these incidents using Geographic Information Systems (GIS).The present study was conducted with the aim of geographically analyzing high-risk areas for traffic accidents in Tabriz and determining the spatial distribution pattern of traffic incidents based on accident outcomes.

Methods: In this descriptive-analytical study, data on property damage, injury, and fatal traffic accidents in Tabriz during 2017 were collected from various sources, and accident locations were identified using geographic addresses and coordinates. To analyze the geographical distribution of high-risk accident zones, spatial analysis methods including Moran’s Index, Kernel Density Estimation, Geographically Weighted Regression (GWR), and correlation analysis were employed.

Results: In this study, the cumulative pattern of accidents in Tabriz was confirmed, such that district 8, northeast of District 3, central and southern regions of District 1, and the entrance to District 5 of Tabriz city had dense accident distribution patterns. The religious, commercial, and service land-use layers had the highest correlation with accident density. High-traffic axes had fewer accidents; the highest was related to areas with low traffic volume. Autumn and winter have the most damage accidents, and the highest number of accidents leading to death was assigned to the spring season.

Conclusion: Given the concentration of traffic accidents in high-risk areas of Tabriz—particularly in District 8 and the eastern entrances—it is recommended that traffic infrastructure be improved, traffic regulations be strengthened, and monitoring be enhanced through intelligent systems to reduce accidents. Additionally, conducting public awareness campaigns can also be effective in decreasing traffic incidents.