چکیده:
Background and objective: Traffic accidents are one of the important causes of death and serious injuries to life and money, and their heavy social, cultural and economic consequences have seriously threatened human societies. While the statistics in many developed countries show a stabilized or declining trend in traffic death rates, the number of traffic injuries in recent decades in developing countries is still increasing. Although some road safety measures have been taken by some departments and organizations in recent years, statistics show that driving injuries are still a serious threat to people's health in Iran. Therefore, more serious measures and joint efforts among organizations are necessary to strengthen road safety. Therefore, a better understanding of the relationship between vehicle accidents and the geographical environment is an important step in predicting accidents and providing useful solutions that can reduce the occurrence or severity of accidents by adopting preventive policies.Methodology: This study is of an applied research type that was conducted using a descriptive and analytical approach. Also, in order to model the spatial relationships of pedestrian accidents, geographic weighted regression (GWR) analysis was used in the geographic information system (GIS) environment, which is one of the newest methods of modeling spatially heterogeneous processes. In this method, along with the involvement of independent variables of precipitation, temperature and wind in the model, spatial analysis of accidents has also been done.Findings: The results show the fact that 88% of the dependent variable (pedestrian accidents) is explained by the precipitation parameter, 78% by the temperature variable and 84% by the wind speed variable. Also, in 1183 accidents registered from 2015 to 2019 out of a total of 2518 cases, the role of climatic factors (wind, rain, temperature) is very clear, and the above-mentioned accidents are mostly concentrated in the center of District 5 of Tehran.Results: Based on this, the areas of Second Shahran Square, North Shaheen Blvd. towards Abshanasan Highway, Ferdous neighborhood (intersection of Salimi Jahormi St. and Ferdous Blvd.), Program Organization St. (intersection of Allameh Jafari and Bakri highways), South Janat Abad Blvd. (35m East Laleh St.) and South Shahin Blvd. and around Chahar Bagh Square) have the highest coefficient of determination and correlation of accidents with the climate component, in this regard, the analysis indicates the fact that with more rainfall, higher temperature and higher wind speed, accidents in these areas are more severe. All these results confirm the initial hypothesis of the research, except for the temperature variable, whose decrease was predicted to increase the number of accidents.
خلاصه ماشینی:
The main issue of this research is the modeling and spatial analysis of the influence of climatic factors (temperature, precipitation, and wind) as independent variables in accidents using the Geographically Weighted Regression method in District 5 of Tehran.
Thus, based on this, the objective of writing this article is the spatial analysis of the role of climatic factors in pedestrian accidents using Geographic Information Systems (GIS) and the GWR model in District 5 of Tehran.
In point pattern analysis, several methods are used to diagnose the deviation from spatial randomness of point features related to pedestrian-related traffic accidents, which describe the distribution of their locations as follows 110 below (Cloutier, Apparicio and Thouez, 2007).
Hypothesis: Given what was previously mentioned, based on the geographic location and demographic characteristics of District 5 of Tehran city, it is assumed that climatic factors such as precipitation, temperature, and wind, as independent variables of this research, have a significant correlation with pedestrian accidents occurring in the region as the dependent variable.
(District 5 Municipality, 1399) Figure No. 2- Geographic location of the study area (Authors) Research Findings To obtain information on pedestrian accidents as the dependent variable, statistics from the Greater Tehran Traffic Police from the beginning of 1395 to the end of 1399 were used.
Dee, Uppala, Simmons, Berrisford, Poli, Kobayashi, Andrae, Balmaseda, Balsamo, Bauer, Bechtold, Beljaars, van de Berg, Bidlot, Bormann, Delsol, Dragani, Fuentes, Geer, Haimberger, Healy, Hersbach, H´olm, Isaksen, Kallberg, Kohler, Matricardi, McNally, Monge-Sanz, Morcrette, Park, Peubey, de Rosnay, Tavolato, Th´epaut, and Vitart.
Balsamo, Albergel, Beljaars, Boussetta, Brun, Cloke, Dee, Dutra, Muñoz-Sabater, Pappenberger, de Rosnay, Stockdale, and Vitart.
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