Volume 17, Issue 2 (4-2025)
jorar 2025, 17(2): 96-109 |
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Mousavi B S, Argany M, Neysani Samany N, Soltani A. Spatial-Temporal Analysis of the Relationship Between Fatal Road Accidents and Environmental Factors in order to Improve RCS Rescue & Relief Operations (Study Area: Mazandaran and Alborz Provinces). jorar 2025; 17 (2) :96-109
URL: http://jorar.ir/article-1-1016-en.html
URL: http://jorar.ir/article-1-1016-en.html
Department of Remote Sensing and GIS, Faculty of Geography, University of Tehran, Tehran, Iran
Abstract: (18 Views)
INTRODUCTION: Road traffic accidents are a critical global issue, especially in developing countries such as Iran. Mazandaran and Alborz provinces, due to their diverse climatic and topographic characteristics, experience a high rate of fatal accidents, especially on mountainous roads that are often affected by weather and traffic conditions. Therefore, in this study, we investigate
METHODS: This study analyzed fatal road accidents from March 2017 to January 2024 using data from the Red Crescent Society (RCS) and the Road Maintenance and Transportation Organization. Accident data were converted into monthly raster files via Kernel Density Estimation and examined using the Space-Time Cube model and Hot Spot Analysis in ArcGIS Pro to identify spatial-temporal accident patterns and their relation to environmental and traffic factors.
FINDINGS: Four hot spots and three cold spots patterns were detected across 83 months. Rainfall and flooding significantly affected 16.04% of oscillating and sporadic hot spots. Smooth and semi-heavy traffic conditions were associated with the highest accident percentages (19.45% and 14.01%), while blocked and heavy traffic showed lower accident intensity. Major accident hotspots appeared along the Chalous and Haraz roads and in specific rural districts. Emerging hot spots revealed new risk areas, demonstrating the dynamic nature of accident patterns.
CONCLUSION: The Spatio-temporal analysis highlights high-risk areas and provides important insights for improving road safety. These findings can help the Red Crescent Society optimize rescue and relief operations and inform policymakers on infrastructure and traffic management strategies to reduce casualties
METHODS: This study analyzed fatal road accidents from March 2017 to January 2024 using data from the Red Crescent Society (RCS) and the Road Maintenance and Transportation Organization. Accident data were converted into monthly raster files via Kernel Density Estimation and examined using the Space-Time Cube model and Hot Spot Analysis in ArcGIS Pro to identify spatial-temporal accident patterns and their relation to environmental and traffic factors.
FINDINGS: Four hot spots and three cold spots patterns were detected across 83 months. Rainfall and flooding significantly affected 16.04% of oscillating and sporadic hot spots. Smooth and semi-heavy traffic conditions were associated with the highest accident percentages (19.45% and 14.01%), while blocked and heavy traffic showed lower accident intensity. Major accident hotspots appeared along the Chalous and Haraz roads and in specific rural districts. Emerging hot spots revealed new risk areas, demonstrating the dynamic nature of accident patterns.
CONCLUSION: The Spatio-temporal analysis highlights high-risk areas and provides important insights for improving road safety. These findings can help the Red Crescent Society optimize rescue and relief operations and inform policymakers on infrastructure and traffic management strategies to reduce casualties
Keywords: Fatal road accidents, Environmental factors, Space-time cube analysis, Hot spot analysis, RCS Rescue & Relief Operations.
Article Type: Research article |
Subject:
Crisis management in disasters
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