Department of Human Geograhy and Spatial Planning, Faculty of Earth Sciences, Shahid Beheshti University, Tehran 1613778314, Iran.
Department of Human Geography, University of Tehran, Tehran 1613778314, Iran.
Int J Environ Res Public Health. 2021 Apr 23;18(9):4498. doi: 10.3390/ijerph18094498.
Official statistics demonstrate the role of traffic accidents in the increasing number of fatalities, especially in emerging countries. In recent decades, the rate of deaths and injuries caused by traffic accidents in Iran, a rapidly growing economy in the Middle East, has risen significantly with respect to that of neighboring countries. The present study illustrates an exploratory spatial analysis' framework aimed at identifying and ranking hazardous locations for traffic accidents in Zanjan, one of the most populous and dense cities in Iran. This framework quantifies the spatiotemporal association among collisions, by comparing the results of different approaches (including Kernel Density Estimation (KDE), Natural Breaks Classification (NBC), and Knox test). Based on descriptive statistics, five distance classes (2-26, 27-57, 58-105, 106-192, and 193-364 meters) were tested when predicting location of the nearest collision within the same temporal unit. The empirical results of our work demonstrate that the largest roads and intersections in Zanjan had a significantly higher frequency of traffic accidents than the other locations. A comparative analysis of distance bandwidths indicates that the first (2-26 m) class concentrated the most intense level of spatiotemporal association among traffic accidents. Prevention (or reduction) of traffic accidents may benefit from automatic identification and classification of the most risky locations in urban areas. Thanks to the larger availability of open-access datasets reporting the location and characteristics of car accidents in both advanced countries and emerging economies, our study demonstrates the potential of an integrated analysis of the level of spatiotemporal association in traffic collisions over metropolitan regions.
官方统计数据表明，交通事故在死亡人数的增加中起着重要作用，尤其是在新兴国家。近几十年来，在中东快速增长的经济体伊朗，交通事故造成的死亡和受伤人数与邻国相比显著上升。本研究展示了一个探索性空间分析框架，旨在确定和排名伊朗人口最多和最密集的城市之一赞詹的交通事故危险地点。该框架通过比较不同方法（包括核密度估计（KDE）、自然断点分类（NBC）和 Knox 检验）的结果，量化了碰撞的时空关联。基于描述性统计，在预测同一时间单位内最近的碰撞位置时，测试了五个距离类别（2-26、27-57、58-105、106-192 和 193-364 米）。我们工作的实证结果表明，赞詹最大的道路和交叉口的交通事故频率明显高于其他地点。对距离带宽的比较分析表明，第一个（2-26 米）类别集中了交通事故中最强烈的时空关联水平。通过自动识别和分类城市地区最危险的地点，可以预防（或减少）交通事故。由于先进国家和新兴经济体中越来越多的公开数据集报告了汽车事故的位置和特征，我们的研究展示了对大都市地区交通事故时空关联水平进行综合分析的潜力。
