Optimising citizen-driven air quality monitoring networks for cities

Detalhes bibliográficos
Autor(a) principal: Gupta, Shivam
Data de Publicação: 2018
Outros Autores: Pebesma, Edzer, Degbelo, Auriol, Costa, Ana Cristina
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.3390/ijgi7120468
Resumo: Gupta, S., Pebesma, E., Degbelo, A., & Costa, A. C. (2018). Optimising citizen-driven air quality monitoring networks for cities. ISPRS International Journal of Geo-Information, 7(12), [468]. DOI: 10.3390/ijgi7120468
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spelling Optimising citizen-driven air quality monitoring networks for citiesAir quality monitoringCitizen engagementCrowdsourcingLand use regressionSensor location optimisationSpatial simulated annealingVolunteered geographic informationGeography, Planning and DevelopmentComputers in Earth SciencesEarth and Planetary Sciences (miscellaneous)SDG 11 - Sustainable Cities and CommunitiesSDG 3 - Good Health and Well-beingSDG 15 - Life on LandGupta, S., Pebesma, E., Degbelo, A., & Costa, A. C. (2018). Optimising citizen-driven air quality monitoring networks for cities. ISPRS International Journal of Geo-Information, 7(12), [468]. DOI: 10.3390/ijgi7120468Air quality has had a significant impact on public health, the environment and eventually on the economy of countries for decades. Effectively mitigating air pollution in urban areas necessitates accurate air quality exposure information. Recent advancements in sensor technology and the increasing popularity of volunteered geographic information (VGI) open up new possibilities for air quality exposure assessment in cities. However, citizens and their sensors are put in areas deemed to be subjectively of interest (e.g., where citizens live, school of their kids or working spaces), and this leads to missed opportunities when it comes to optimal air quality exposure assessment. In addition, while the current literature on VGI has extensively discussed data quality and citizen engagement issues, few works, if any, offer techniques to fine-tune VGI contributions for an optimal air quality exposure assessment. This article presents and tests an approach to minimise land use regression prediction errors on citizen-contributed data. The approach was evaluated using a dataset (N = 116 sensors) from the city of Stuttgart, Germany. The comparison between the existing network design and the combination of locations selected by the optimisation method has shown a drop in spatial mean prediction error by 52%. The ideas presented in this article are useful for the systematic deployment of VGI air quality sensors, and can aid in the creation of higher resolution, more realistic maps for air quality monitoring in cities.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNGupta, ShivamPebesma, EdzerDegbelo, AuriolCosta, Ana Cristina2019-02-25T23:19:33Z2018-11-302018-11-30T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://doi.org/10.3390/ijgi7120468eng2220-9964PURE: 11663104http://www.scopus.com/inward/record.url?scp=85061380078&partnerID=8YFLogxKhttps://doi.org/10.3390/ijgi7120468info: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:RCAAP2024-03-11T04:29:18Zoai:run.unl.pt:10362/61648Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:33:39.994710Repositório 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 Optimising citizen-driven air quality monitoring networks for cities
title Optimising citizen-driven air quality monitoring networks for cities
spellingShingle Optimising citizen-driven air quality monitoring networks for cities
Gupta, Shivam
Air quality monitoring
Citizen engagement
Crowdsourcing
Land use regression
Sensor location optimisation
Spatial simulated annealing
Volunteered geographic information
Geography, Planning and Development
Computers in Earth Sciences
Earth and Planetary Sciences (miscellaneous)
SDG 11 - Sustainable Cities and Communities
SDG 3 - Good Health and Well-being
SDG 15 - Life on Land
title_short Optimising citizen-driven air quality monitoring networks for cities
title_full Optimising citizen-driven air quality monitoring networks for cities
title_fullStr Optimising citizen-driven air quality monitoring networks for cities
title_full_unstemmed Optimising citizen-driven air quality monitoring networks for cities
title_sort Optimising citizen-driven air quality monitoring networks for cities
author Gupta, Shivam
author_facet Gupta, Shivam
Pebesma, Edzer
Degbelo, Auriol
Costa, Ana Cristina
author_role author
author2 Pebesma, Edzer
Degbelo, Auriol
Costa, Ana Cristina
author2_role author
author
author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Gupta, Shivam
Pebesma, Edzer
Degbelo, Auriol
Costa, Ana Cristina
dc.subject.por.fl_str_mv Air quality monitoring
Citizen engagement
Crowdsourcing
Land use regression
Sensor location optimisation
Spatial simulated annealing
Volunteered geographic information
Geography, Planning and Development
Computers in Earth Sciences
Earth and Planetary Sciences (miscellaneous)
SDG 11 - Sustainable Cities and Communities
SDG 3 - Good Health and Well-being
SDG 15 - Life on Land
topic Air quality monitoring
Citizen engagement
Crowdsourcing
Land use regression
Sensor location optimisation
Spatial simulated annealing
Volunteered geographic information
Geography, Planning and Development
Computers in Earth Sciences
Earth and Planetary Sciences (miscellaneous)
SDG 11 - Sustainable Cities and Communities
SDG 3 - Good Health and Well-being
SDG 15 - Life on Land
description Gupta, S., Pebesma, E., Degbelo, A., & Costa, A. C. (2018). Optimising citizen-driven air quality monitoring networks for cities. ISPRS International Journal of Geo-Information, 7(12), [468]. DOI: 10.3390/ijgi7120468
publishDate 2018
dc.date.none.fl_str_mv 2018-11-30
2018-11-30T00:00:00Z
2019-02-25T23:19:33Z
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 https://doi.org/10.3390/ijgi7120468
url https://doi.org/10.3390/ijgi7120468
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2220-9964
PURE: 11663104
http://www.scopus.com/inward/record.url?scp=85061380078&partnerID=8YFLogxK
https://doi.org/10.3390/ijgi7120468
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.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
repository.mail.fl_str_mv
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