Scientific journal paper Q1
Data analytics process over road accidents data—A case study of Lisbon city
Joao Mesquitela (Mesquitela, J.); Luís B. Elvas (Elvas, L. B.); Joao C Ferreira or Joao Ferreira (Ferreira, J.); Luís Nunes (Nunes, L.);
Journal Title
ISPRS International Journal of Geo-Information
Year (definitive publication)
2022
Language
English
Country
Switzerland
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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.
Acknowledgements
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Keywords
Road accidents,Black spots,GIS,Data analysis
  • Computer and Information Sciences - Natural Sciences
  • Earth and related Environmental Sciences - Natural Sciences
  • Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
Funding Records
Funding Reference Funding Entity
UIDB/04466/2020 Fundação para a Ciência e a Tecnologia

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