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Spatiotemporal Analysis of Property Damage-only Accident Hotspots Using GIS in Sharjah, UAE

Autor(en):
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Jordan Journal of Civil Engineering, , n. 2, v. 18
DOI: 10.14525/jjce.v18i2.13
Abstrakt:

Recent research on road-traffic accidents (RTAs) has become a focal point for safety and transportation experts, focusing on understanding their rates, characteristics, causes and effects. A significant development in this field is using Geographic Information Systems (GISs) to analyze RTAs. The primary objective of this study is to introduce a GIS-based approach for the comprehensive analysis of the spatial and temporal distribution of RTAs, specifically Property Damage-only (PDO) accidents. This research also endeavors to pinpoint accident-prone areas, commonly called ‘hotspots,’ and high-density accident clusters. This was achieved through spatialautocorrelation analysis, incorporating techniques, including inverse distance weighting, Moran’s index and the Getis Ord Gi* statistic. By focusing on eight years of accident data (2015-2022) in the Sharjah Emirate of the United Arab Emirates, this study contributes to a deeper understanding of the distribution of traffic accidents. The analysis of temporal patterns revealed that the monthly distribution of PDO accidents showed the lowest frequencies of incidents in July, August and September throughout the study period. Furthermore, PDO accident frequencies peaked in 2015, followed by a decline until 2018, after which there was a slight increase until the conclusion of the analysis in 2022. Spatial analysis highlighted significant clustering of PDO-related RTAs. Hotspot analysis specifically identified downtown areas of Sharjah city as more prone to PDO accidents than other regions. The findings underscore the effectiveness of the analytical methods employed, which can be utilized for identifying and prioritizing accident hotspots. Keywords: Road-traffic accidents, Property Damage Only (PDO), Spatial analysis, Hotspot analysis, GIS.

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.14525/jjce.v18i2.13.
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  • Reference-ID
    10773032
  • Veröffentlicht am:
    29.04.2024
  • Geändert am:
    17.05.2024
 
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