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Using spatial point process models, clustering and space partitioning to reconfigure fire stations layout

2023-10-04Artigo científico Acesso aberto
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dc.contributor.authorBispo, Regina
dc.contributor.authorVieira, Francisca G.
dc.contributor.authorYokochi, Clara
dc.contributor.authorMarques, Filipe J.
dc.contributor.authorEspadinha-Cruz, Pedro
dc.contributor.authorPenha, Alexandre
dc.contributor.authorGrilo, António
dc.contributor.institutionDM - Departamento de Matemática
dc.contributor.institutionCMA - Centro de Matemática e Aplicações
dc.contributor.institutionUNIDEMI - Unidade de Investigação e Desenvolvimento em Engenharia Mecânica e Industrial
dc.contributor.institutionDEMI - Departamento de Engenharia Mecânica e Industrial
dc.contributor.institutionDCV - Departamento de Ciências da Vida
dc.contributor.pblSpringer International Publishing
dc.date.accessioned2024-03-06T23:52:43Z
dc.date.available2024-03-06T23:52:43Z
dc.date.issued2023-10-04
dc.descriptionPublisher Copyright: © 2023, The Author(s).
dc.description.abstractFire stations (FS) are typically non-uniformly distributed across space, and their service area is, in general, defined based on administrative boundaries. Since the location of FS may considerably influence the readiness and the effectiveness of the provided services, national and regional governments need research-based information to adequately plan where to establish firefighting facilities. In this study, we propose a method to reconfigure the fire stations layout using spatial point process models, clustering and space partitioning. First, modelling fire intensity variation across space through a point process model enables to replicate the process independently by simulation. Subsequently, for each simulation, the k-means algorithm is used to define a siting location, minimizing the total within distance between the fire occurrences and the new position. This method allows to obtain a set of locations from which the respective distribution is inferred. Assuming a bivariate normal spatial distribution, we further define confidence siting regions. Ultimately, new FS service areas are defined by Voronoi tessellation. To exemplify the application of the method, we apply it to reconfigure the fire station layout at Aveiro, Portugal.en
dc.description.versionpublishersversion
dc.description.versionepub_ahead_of_print
dc.format.extent11
dc.format.extent1695270
dc.identifier.doi10.1007/s41060-023-00455-z
dc.identifier.issn2364-415X
dc.identifier.otherPURE: 84397504
dc.identifier.otherPURE UUID: 9994509c-428d-403b-921d-448ede9e771c
dc.identifier.otherScopus: 85173095736
dc.identifier.otherWOS: 001080645200001
dc.identifier.otherORCID: /0000-0002-6045-9994/work/154847515
dc.identifier.otherORCID: /0000-0002-5337-0633/work/154847665
dc.identifier.otherORCID: /0000-0002-6723-2557/work/154848269
dc.identifier.urihttp://hdl.handle.net/10362/164570
dc.identifier.urlhttps://www.scopus.com/pages/publications/85173095736
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:001080645200001
dc.language.isoeng
dc.peerreviewedyes
dc.relationResearch and Development Unit for Mechanical and Industrial Engineering
dc.relationCenter for Mathematics and Applications
dc.relationCenter for Mathematics and Applications
dc.subjectFire
dc.subjectFire stations
dc.subjectK-means
dc.subjectPoisson point process
dc.subjectVoronoi tessellation
dc.subjectInformation Systems
dc.subjectModelling and Simulation
dc.subjectComputer Science Applications
dc.subjectComputational Theory and Mathematics
dc.subjectApplied Mathematics
dc.titleUsing spatial point process models, clustering and space partitioning to reconfigure fire stations layouten
dc.typejournal article
degois.publication.firstPage
degois.publication.lastPage
degois.publication.titleInternational Journal of Data Science and Analytics
degois.publication.volume20
dspace.entity.typePublication
oaire.awardNumberUIDB/00667/2020
oaire.awardNumberUIDB/00297/2020
oaire.awardNumberUIDP/00297/2020
oaire.awardTitleResearch and Development Unit for Mechanical and Industrial Engineering
oaire.awardTitleCenter for Mathematics and Applications
oaire.awardTitleCenter for Mathematics and Applications
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00667%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00297%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00297%2F2020/PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
relation.isProjectOfPublication1a4033c7-5add-4c00-8393-eb4bed8a7a8e
relation.isProjectOfPublicationd00ae22f-ec2b-47b2-935e-60cb44493cc6
relation.isProjectOfPublication65d392f7-8781-4d70-b9f3-069b07d4a311
relation.isProjectOfPublication.latestForDiscovery1a4033c7-5add-4c00-8393-eb4bed8a7a8e

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