Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018

Autores
Represa, Natacha Soledad; Palomar Vázquez, Jesús; Porta, Atilio Andrés; Fernández Sarría, Alfonso
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Fine particulate matter (PM2.5) is a global problem that affects the population health and contributes to climate change. Remote sensing provides useful information for the development of air quality models. This work aims to obtain a daily model of PM2.5 levels in the Valencian Community with a resolution of 1 km for the period 2008–2018. MODIS-MAIAC images, meteorological parameters of the MERRA-2 project, land cover information and ground level measurements of PM2.5 levels were analysed with Random Forest. The verification of the model was carried out using cross-validation repeated ten times, and an evaluation of a test set with 20% of the collected information. The final model was used to generate maps of the daily concentrations of PM2.5 for the area of the Valencian Community throughout the study period.
Centro de Investigaciones del Medioambiente
Materia
Química
PM2.5
LUR
Random Forest
MODIS
MERRA-2
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/125389
Acceder
id SEDICI_f4fe5ff7fe3353ea7d46b9d61f4752c5
oai_identifier_str oai:sedici.unlp.edu.ar:10915/125389
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018Represa, Natacha SoledadPalomar Vázquez, JesúsPorta, Atilio AndrésFernández Sarría, AlfonsoQuímicaPM2.5LURRandom ForestMODISMERRA-2Fine particulate matter (PM2.5) is a global problem that affects the population health and contributes to climate change. Remote sensing provides useful information for the development of air quality models. This work aims to obtain a daily model of PM2.5 levels in the Valencian Community with a resolution of 1 km for the period 2008–2018. MODIS-MAIAC images, meteorological parameters of the MERRA-2 project, land cover information and ground level measurements of PM2.5 levels were analysed with Random Forest. The verification of the model was carried out using cross-validation repeated ten times, and an evaluation of a test set with 20% of the collected information. The final model was used to generate maps of the daily concentrations of PM2.5 for the area of the Valencian Community throughout the study period.Centro de Investigaciones del Medioambiente2019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/125389enginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2504-3900/19/1/13info:eu-repo/semantics/altIdentifier/issn/2504-3900info:eu-repo/semantics/altIdentifier/doi/10.3390/proceedings2019019013info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:30:03Zoai:sedici.unlp.edu.ar:10915/125389Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:30:03.554SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018
title Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018
spellingShingle Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018
Represa, Natacha Soledad
Química
PM2.5
LUR
Random Forest
MODIS
MERRA-2
title_short Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018
title_full Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018
title_fullStr Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018
title_full_unstemmed Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018
title_sort Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018
dc.creator.none.fl_str_mv Represa, Natacha Soledad
Palomar Vázquez, Jesús
Porta, Atilio Andrés
Fernández Sarría, Alfonso
author Represa, Natacha Soledad
author_facet Represa, Natacha Soledad
Palomar Vázquez, Jesús
Porta, Atilio Andrés
Fernández Sarría, Alfonso
author_role author
author2 Palomar Vázquez, Jesús
Porta, Atilio Andrés
Fernández Sarría, Alfonso
author2_role author
author
author
dc.subject.none.fl_str_mv Química
PM2.5
LUR
Random Forest
MODIS
MERRA-2
topic Química
PM2.5
LUR
Random Forest
MODIS
MERRA-2
dc.description.none.fl_txt_mv Fine particulate matter (PM2.5) is a global problem that affects the population health and contributes to climate change. Remote sensing provides useful information for the development of air quality models. This work aims to obtain a daily model of PM2.5 levels in the Valencian Community with a resolution of 1 km for the period 2008–2018. MODIS-MAIAC images, meteorological parameters of the MERRA-2 project, land cover information and ground level measurements of PM2.5 levels were analysed with Random Forest. The verification of the model was carried out using cross-validation repeated ten times, and an evaluation of a test set with 20% of the collected information. The final model was used to generate maps of the daily concentrations of PM2.5 for the area of the Valencian Community throughout the study period.
Centro de Investigaciones del Medioambiente
description Fine particulate matter (PM2.5) is a global problem that affects the population health and contributes to climate change. Remote sensing provides useful information for the development of air quality models. This work aims to obtain a daily model of PM2.5 levels in the Valencian Community with a resolution of 1 km for the period 2008–2018. MODIS-MAIAC images, meteorological parameters of the MERRA-2 project, land cover information and ground level measurements of PM2.5 levels were analysed with Random Forest. The verification of the model was carried out using cross-validation repeated ten times, and an evaluation of a test set with 20% of the collected information. The final model was used to generate maps of the daily concentrations of PM2.5 for the area of the Valencian Community throughout the study period.
publishDate 2019
dc.date.none.fl_str_mv 2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/125389
url http://sedici.unlp.edu.ar/handle/10915/125389
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2504-3900/19/1/13
info:eu-repo/semantics/altIdentifier/issn/2504-3900
info:eu-repo/semantics/altIdentifier/doi/10.3390/proceedings2019019013
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844616179909394432
score 13.070432

Publicaciones similares