Data analytics process over road accidents data—A case study of Lisbon city

Detalhes bibliográficos
Autor(a) principal: Mesquitela, J.
Data de Publicação: 2022
Outros Autores: Elvas, L. B., Ferreira, J., Nunes, L.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/24674
Resumo: 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.
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spelling Data analytics process over road accidents data—A case study of Lisbon cityRoad accidentsBlack spotsGISData analysisTraffic 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.MDPI2022-03-03T15:06:27Z2022-01-01T00:00:00Z20222022-03-03T15:05:38Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/24674eng2220-996410.3390/ijgi11020143Mesquitela, J.Elvas, L. B.Ferreira, J.Nunes, L.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:47:39Zoai:repositorio.iscte-iul.pt:10071/24674Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:23:08.904669Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Data analytics process over road accidents data—A case study of Lisbon city
title Data analytics process over road accidents data—A case study of Lisbon city
spellingShingle Data analytics process over road accidents data—A case study of Lisbon city
Mesquitela, J.
Road accidents
Black spots
GIS
Data analysis
title_short Data analytics process over road accidents data—A case study of Lisbon city
title_full Data analytics process over road accidents data—A case study of Lisbon city
title_fullStr Data analytics process over road accidents data—A case study of Lisbon city
title_full_unstemmed Data analytics process over road accidents data—A case study of Lisbon city
title_sort Data analytics process over road accidents data—A case study of Lisbon city
author Mesquitela, J.
author_facet Mesquitela, J.
Elvas, L. B.
Ferreira, J.
Nunes, L.
author_role author
author2 Elvas, L. B.
Ferreira, J.
Nunes, L.
author2_role author
author
author
dc.contributor.author.fl_str_mv Mesquitela, J.
Elvas, L. B.
Ferreira, J.
Nunes, L.
dc.subject.por.fl_str_mv Road accidents
Black spots
GIS
Data analysis
topic Road accidents
Black spots
GIS
Data analysis
description 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.
publishDate 2022
dc.date.none.fl_str_mv 2022-03-03T15:06:27Z
2022-01-01T00:00:00Z
2022
2022-03-03T15:05:38Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/24674
url http://hdl.handle.net/10071/24674
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2220-9964
10.3390/ijgi11020143
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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