A Geospatial Analysis of Motorcycle Accident Risk Factors in Khon Kaen Municipality, Thailand: Examining the Chain of Survival and Potential Strategies
Issued Date
2024-09-01
Resource Type
ISSN
16866576
eISSN
26730014
Scopus ID
2-s2.0-85207394830
Journal Title
International Journal of Geoinformatics
Volume
20
Issue
9
Start Page
71
End Page
82
Rights Holder(s)
SCOPUS
Bibliographic Citation
International Journal of Geoinformatics Vol.20 No.9 (2024) , 71-82
Suggested Citation
Tippayanate N., Impool T., Sujayanont P., Muttitanon W., Chemin Y.H., Som-Ard J. A Geospatial Analysis of Motorcycle Accident Risk Factors in Khon Kaen Municipality, Thailand: Examining the Chain of Survival and Potential Strategies. International Journal of Geoinformatics Vol.20 No.9 (2024) , 71-82. 82. doi:10.52939/ijg.v20i9.3547 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/101877
Title
A Geospatial Analysis of Motorcycle Accident Risk Factors in Khon Kaen Municipality, Thailand: Examining the Chain of Survival and Potential Strategies
Corresponding Author(s)
Other Contributor(s)
Abstract
The study utilizes a geospatial approach to analyze the risk of motorcycle accidents in Khon Kaen Municipality, Thailand. We focus on identifying high-crash areas involving motorcyclists and investigating factors contributing to the severity of accidents and potential survival rates. The analysis is framed within the "Chain of Survival" framework, specifically focusing on how the location of ambulance stations affects the Emergency Medical Service (EMS) response times. Additionally, we explore various traffic management strategies, with an emphasis on their effectiveness in reducing nighttime accidents. The primary goal of this research is to gain a comprehensive understanding of the spatial distribution of motorcycle accidents and to identify key factors influencing their outcomes. Our findings reveal that motorcycle accidents constitute the highest number of traffic accidents in the area, with a significant proportion occurring in the southwest of Khon Kaen Municipality during late night hours. Given the importance of early intervention within the EMS, we suggest locating EMS stations close to areas with a high incidence of accidents concerning the effective response time, as recommended at two specific points. However, due to limitations in the number of EMS teams available, these recommended points may experience delays in response times, particularly during late-night hours when traffic accidents peak. Ultimately, the insights gained from this study will inform data-driven recommendations aimed at optimizing both emergency response systems and traffic management strategies to enhance road safety in Khon Kaen Municipality.