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Author(s): Mesquitela, J.
Elvas, L. B.
Ferreira, J.
Nunes, L.
Date: 2022
Title: Data analytics process over road accidents data—A case study of Lisbon city
Volume: 11
Number: 2
ISSN: 2220-9964
DOI (Digital Object Identifier): 10.3390/ijgi11020143
Keywords: Road accidents
Black spots
Data analysis
Abstract: Traffic accidents in urban areas lead to reduced quality of life and added pressure in the cities’ infra-structures. In the context of smart city data is becoming available that allows a deeper analysis of the phenomenon. We propose a data fusion process from different information sources like road accidents, weather conditions, local authority reports tools, traffic, fire brigade. These big data analytics allow the creation of knowledge for local municipalities using local data. Data visualizations allow big picture overview. This paper presents an approach to the geo-referenced accident-hotspots identification. Using ArcGIS Pro, we apply Kernel Density and Hot Spot Analysis (Getis-Ord Gi*) tools, identifying the existence of black spots in terms of location and context conditions, and evaluate the possible human, environmental and circumstantial factors that may influence the severity of accidents. The results were validated by an expert committee. This approach can be applied to other cites wherever this data is available.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica

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