Hot spot analysis based on network spatial weights to determine spatial statistics of traffic accidents in Rize, Turkey

ÇOLAK H. E., MEMİŞOĞLU T., Erbas Y. S., Bediroglu S.

ARABIAN JOURNAL OF GEOSCIENCES, vol.11, no.7, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 7
  • Publication Date: 2018
  • Doi Number: 10.1007/s12517-018-3492-8
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: Traffic accident, Hot spot analysis, Network spatial weights, Kernel, Rize, Turkey, KERNEL DENSITY-ESTIMATION, GIS, AFYONKARAHISAR, ATTRIBUTE, LOCATION, HIGHWAY, SYSTEM, TOOL
  • Karadeniz Technical University Affiliated: Yes


The increased numbers of vehicles using roads in the world today are cause of traffic-related problems, and in this respect, road traffic accidents are an important topic relating to public health. Especially on the road connecting two border provinces, traffic accidents are increasing substantially in parallel with the quantity of transport facilities. By determining areas where traffic accidents result in deaths or injuries, accident prevention strategies can be developed. This study applies the spatial statistics techniques using Geographical Information Systems (GIS) to determine the intensity of traffic accidents (hot-spot regions) over 45 km of main routes in Rize Province, Turkey. Traffic accidents recorded in data spanning 5 years are combined with a geographical dataset for evaluation using hot spot statistical analysis. Unlike other studies, this study used hot spot analysis based on network spatial weights (an innovative review in the methods of determining traffic accident hot spots: "novel application of GIScience") to identify black spots for traffic safety. To perform the analysis using Hot Spot Analysis: Getis-Ord Gi*, a generated network dataset and the spatial weights of the road data are used to generate network spatial weights. Then, Kernel Density method is used to define traffic accident black spots. Finally, these two methods are compared each other with visually.