Hotspots Identification of Pedestrian Crashes using Kernel Density Estimation in GIS (Case Study: Mashhad City)

Based on recent literatures, 22% of fatality’s crashes have been categorized as pedestrian-related worldwide. In Iran, such a record is about 23.2. The analysis and evaluation of pedestrian accidents be turned to one of the major engineering challenges in the promotion of public health and safety. However in the most works undertaken the spatial parameters on the location of the accident, so spatial variations in the predictive have been neglected. In this paper considering pedestrian injury accidents for the city of Mashhad in Iran during time period of 3 years (1391-1393) by employing geo_statistical processing in GIS, sites with a high density of pedestrian accidents have been identified and prioritized. For this purpose, after preparing required raster layers with the pixel size of 20 meters in a spatial database containing 111,537 pixels has been prepared and using network Kernel Density Estimation, hotspots were identified. By implementing KDE to the study area of the city of Mashhad, it was revealed that Fajr square of the four region municipalities, beginning of Sarakhs Road in the six Municipality and Hemat-Resalat intersection, as hazardous areas of the city of Mashhad in the number of pedestrian injury accidents were identified. Therefore, prioritize safety audit in these areas is recommended.