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https://doi.org/10.32909/kg.22.40.3

Application of Spatial Network Analysis in Road Accidents Based on Open Data

Maria Angelova orcid id orcid.org/0009-0006-4133-632X ; Odjel za geodeziju i geoinformatiku, Geodetski fakultet, Sveučilište za arhitekturu, građevinarstvo i geodeziju, Sofija, Bugarska


Puni tekst: hrvatski pdf 2.836 Kb

str. 66-83

preuzimanja: 42

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Puni tekst: engleski pdf 2.836 Kb

str. 66-83

preuzimanja: 35

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Sažetak

Performing spatial analysis based on a correct multifunctional geographically oriented model in the domain of road accident is an important part of the overall transport system management. The aim of the paper is to demonstrate a methodology for using a digital road model, defining optimal parameters for building a road graph and georeferencing occurred events to determine a spatial autocorrelation index of road accidents, entirely using open data. To achieve this goal, the foundation of international standardization laid down in ISO 19 100 – Geographic information is used in combination with the method for spatial autocorrelation, extended for a network, practically implemented through the capabilities of the Python programming language as an element of a Geoinformation system of road accidents. Open-source data from the OpenStreetMap geoportal were processed, as well as real archive data for 1 ,288 serious accidents on the territory of the city of Sofia, Bulgaria, and a spatial autocorrelation coefficient was calculated to determine the dependence or independence of the number of road accidents between individual areas with its accuracy and reliability. The result is the definition of a correct basis for carrying out spatial analysis with the laying of a foundation for the subsequent study of various factors and the definition of a complex of reasons, the establishment of which will lead to a reduction in traffic injuries.

Ključne riječi

digital road model; road graph; network spatial autocorrelation; spatial weight; road accidents GIS

Hrčak ID:

313533

URI

https://hrcak.srce.hr/313533

Datum izdavanja:

27.12.2023.

Podaci na drugim jezicima: hrvatski

Posjeta: 159 *