Owing to their social and economic consequences, the spatial densities of traffic accidents need to be investigated to solve and prevent related problems. In this study, we aim to determine the spatial densities of traffic accidents over the long term and identify the spatiotemporal changes in the high-density areas of Kahramanmaraş City. Initially, a spatial database of accident features and locations was prepared. Between 2008 and 2015, 14,317 traffic accidents were identified. The hotspot and kernel density estimation (KDE) methods, which were developed to determine the spatial densities in geographical information systems, are commonly used to successfully detect high traffic-accident-density areas. In this study, z scores determined by hotspot analysis were used as weight value for weighted KDE. These areas were obtained separately for each year, and an accident time series was created. The spatiotemporal changes to these areas occurring between 2008 and 2015 were determined. Traffic accidents increased in density at important intersection points of the city, and these areas changed over time during urban development. The results of this study are expected to be beneficial for determining priority areas for preventing traffic accidents in Kahramanmaraş.

中文翻译：

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使用基于 GIS 的密度分析调查土耳其 Kahramanmaraş 交通事故发生率的时空变化

由于其社会和经济后果，需要调查交通事故的空间密度，以解决和预防相关问题。在这项研究中，我们旨在确定长期交通事故的空间密度，并确定 Kahramanmaraş 市高密度地区的时空变化。最初，准备了事故特征和位置的空间数据库。2008 年至 2015 年间，共发生了 14,317 起交通事故。热点和核密度估计 (KDE) 方法是为确定地理信息系统中的空间密度而开发的，通常用于成功检测高交通事故密度区域。在本研究中，通过热点分析确定的 z 分数用作加权 KDE 的权重值。每年分别获得这些区域，并创建事故时间序列。确定了 2008 年至 2015 年期间这些区域的时空变化。城市重要路口交通事故密度增加，这些区域在城市发展过程中随着时间的推移而发生变化。预计这项研究的结果将有助于确定 Kahramanmaraş 预防交通事故的优先领域。