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Volume 13, Issue 4 (Winter 2024)
Disaster Prev. Manag. Know. 2024, 13(4): 526-532 |
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Samia J, Ranjbar Shoubi M, Nikpour A. Spatial-Temporal Analysis of Road Accidents in Haraz Road Using Spatial Statistics and Geographical Information System. Disaster Prev. Manag. Know. 2024; 13 (4) :526-532
URL: http://dpmk.ir/article-1-633-en.html
URL: http://dpmk.ir/article-1-633-en.html
1- Department of Geography and Urban Planning, University of Mazandaran, Babolsar, Iran.
Abstract: (183 Views)
Background and Objective: Road accidents are one of the main causes of injury, disability and causalities in developing countries. In Iran, this is also a societal challenge that affects the physical and mental health of people. This is the main concern of tourists and passengers using the strategic and touristic mountainous Haraz road which connects the capital, Tehran to the north of Iran. To address this concern, we aim to study the spatial density distribution of road accidents and identify spatial clusters of accidents along Haraz road in a time period of 1395-1399.
Method: The location and time of Haraz road’s accidents were collected at the time of accidents occurrence using global position system (GPS) by relief and rescue organization of Red Crescent Society of Iran. We used kernel density estimation’s function in order to assess the spatial density of accidents. In this context, spatial density of accidents were estimated for yearly accidents from 1395 to 1399 and also sum of accidents in this five years period. Also, to detect spatial accidents clusters, we used the spatial statistics of Getis-Ord Gi* in Hot spot analysis. The spatial accidents clusters were also identified both for yearly accidents from 1395 to a1399 and sum of accidents in five years temporal scale. Both approaches were implemented using geographical information system (GIS).
Findings: Results from implementing the kernel density estimation indicate that the density of accidents varies spatially long the raod and temporarily from 1395 to 1399. The Kahroud Paeen region in Haraz road found to have the most density of accidents in the five years period. Hot spot analysis identified four spatial accidents clusters in the regions of Panjab, Kahroud Paeen, Gaznak and Polour along the Haraz road which are statistically significant with average Z-score of 4.49. The number of accident clusters, percentage of accidents in the clusters and also the length of road clusters varies spatio-temporaly with a decreasing trend.
Conclusion: We conclude that application of kernel density estimation and hot spot analysis are useful in order to investigate and analyze the spatio-temporal density distribution of road accidents and also identification of spatial clusters of road accidents along Haraz road. The results can be used to implement infrastructural and technical actions, preparation for relief quick actions and also increasing awareness of passengers from dangerous section of Haraz road.
Method: The location and time of Haraz road’s accidents were collected at the time of accidents occurrence using global position system (GPS) by relief and rescue organization of Red Crescent Society of Iran. We used kernel density estimation’s function in order to assess the spatial density of accidents. In this context, spatial density of accidents were estimated for yearly accidents from 1395 to 1399 and also sum of accidents in this five years period. Also, to detect spatial accidents clusters, we used the spatial statistics of Getis-Ord Gi* in Hot spot analysis. The spatial accidents clusters were also identified both for yearly accidents from 1395 to a1399 and sum of accidents in five years temporal scale. Both approaches were implemented using geographical information system (GIS).
Findings: Results from implementing the kernel density estimation indicate that the density of accidents varies spatially long the raod and temporarily from 1395 to 1399. The Kahroud Paeen region in Haraz road found to have the most density of accidents in the five years period. Hot spot analysis identified four spatial accidents clusters in the regions of Panjab, Kahroud Paeen, Gaznak and Polour along the Haraz road which are statistically significant with average Z-score of 4.49. The number of accident clusters, percentage of accidents in the clusters and also the length of road clusters varies spatio-temporaly with a decreasing trend.
Conclusion: We conclude that application of kernel density estimation and hot spot analysis are useful in order to investigate and analyze the spatio-temporal density distribution of road accidents and also identification of spatial clusters of road accidents along Haraz road. The results can be used to implement infrastructural and technical actions, preparation for relief quick actions and also increasing awareness of passengers from dangerous section of Haraz road.
Type of Study: Research |
Subject:
Special
Received: 2023/10/12 | Accepted: 2024/01/16 | ePublished: 2024/02/29
Received: 2023/10/12 | Accepted: 2024/01/16 | ePublished: 2024/02/29
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