Exposure to parks through the lens of urban mobility

Autores
Salgado Corrado, Ariel Olaf; Yuan, Ziyun; Caridi, Délida Inés; González, Marta C.
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This work presents a portable framework to estimate potential park demand and park exposure through bipartite weighted networks. We use mobility information and open spatial information. Mobility information comes in the form of daily activities sampled from a model based on Call Detail Records (CDR). Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. The framework summarizes each city’s information into one bipartite weighted network with the link weights representing the number of potential visits to a park from each census tract on an average weekday. We compare park exposure and park demand in Greater Los Angeles and Greater Boston in a pre-pandemic scenario. The park exposure of a census tract is calculated as the number of parks surrounding the daily activities of its inhabitants. The demand of a park is calculated as the number of daily activities surrounding it. We find that both cities’ distribution of park exposure have similar shape with Boston having a higher average. On the other hand, the distribution of park demand is very similar in both cities, although their park spatial distributions are different. We include racial/ethnic information from the Census to explore how the park exposure connects tracts of different racial/ethnic groups. We associate parks to racial/ethnic groups based on the number of visitors from each group. Parks within minorities’ tracts are mostly used by majority groups. Finally, through detecting communities in the network, we find that park exposure connects the cities locally, linking parks to their tracts nearby. Furthermore, we find a significant spatial correlation between network communities and different racial/ethnic composition in Los Angeles. This way, patterns of park exposure reproduce the separation among demographic groups of the city.
Fil: Salgado Corrado, Ariel Olaf. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
Fil: Yuan, Ziyun. No especifíca;
Fil: Caridi, Délida Inés. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
Fil: González, Marta C.. Lawrence Berkeley National Laboratory; Estados Unidos. University of California at Berkeley; Estados Unidos
Materia
ACCESSIBILITY
CDR
CENSUS
DEMAND
EXPOSURE
GREEN SPACES
OSM
PARKS
SEGREGATION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/203614

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spelling Exposure to parks through the lens of urban mobilitySalgado Corrado, Ariel OlafYuan, ZiyunCaridi, Délida InésGonzález, Marta C.ACCESSIBILITYCDRCENSUSDEMANDEXPOSUREGREEN SPACESOSMPARKSSEGREGATIONhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1https://purl.org/becyt/ford/2.1https://purl.org/becyt/ford/2https://purl.org/becyt/ford/5.7https://purl.org/becyt/ford/5This work presents a portable framework to estimate potential park demand and park exposure through bipartite weighted networks. We use mobility information and open spatial information. Mobility information comes in the form of daily activities sampled from a model based on Call Detail Records (CDR). Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. The framework summarizes each city’s information into one bipartite weighted network with the link weights representing the number of potential visits to a park from each census tract on an average weekday. We compare park exposure and park demand in Greater Los Angeles and Greater Boston in a pre-pandemic scenario. The park exposure of a census tract is calculated as the number of parks surrounding the daily activities of its inhabitants. The demand of a park is calculated as the number of daily activities surrounding it. We find that both cities’ distribution of park exposure have similar shape with Boston having a higher average. On the other hand, the distribution of park demand is very similar in both cities, although their park spatial distributions are different. We include racial/ethnic information from the Census to explore how the park exposure connects tracts of different racial/ethnic groups. We associate parks to racial/ethnic groups based on the number of visitors from each group. Parks within minorities’ tracts are mostly used by majority groups. Finally, through detecting communities in the network, we find that park exposure connects the cities locally, linking parks to their tracts nearby. Furthermore, we find a significant spatial correlation between network communities and different racial/ethnic composition in Los Angeles. This way, patterns of park exposure reproduce the separation among demographic groups of the city.Fil: Salgado Corrado, Ariel Olaf. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; ArgentinaFil: Yuan, Ziyun. No especifíca;Fil: Caridi, Délida Inés. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; ArgentinaFil: González, Marta C.. Lawrence Berkeley National Laboratory; Estados Unidos. University of California at Berkeley; Estados UnidosSpringer Science and Business Media Deutschland GmbH2022-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/203614Salgado Corrado, Ariel Olaf; Yuan, Ziyun; Caridi, Délida Inés; González, Marta C.; Exposure to parks through the lens of urban mobility; Springer Science and Business Media Deutschland GmbH; EPJ Data Science; 11; 1; 12-2022; 1-212193-1127CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1140/epjds/s13688-022-00351-9info:eu-repo/semantics/altIdentifier/url/https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-022-00351-9info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:09:51Zoai:ri.conicet.gov.ar:11336/203614instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:09:51.411CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Exposure to parks through the lens of urban mobility
title Exposure to parks through the lens of urban mobility
spellingShingle Exposure to parks through the lens of urban mobility
Salgado Corrado, Ariel Olaf
ACCESSIBILITY
CDR
CENSUS
DEMAND
EXPOSURE
GREEN SPACES
OSM
PARKS
SEGREGATION
title_short Exposure to parks through the lens of urban mobility
title_full Exposure to parks through the lens of urban mobility
title_fullStr Exposure to parks through the lens of urban mobility
title_full_unstemmed Exposure to parks through the lens of urban mobility
title_sort Exposure to parks through the lens of urban mobility
dc.creator.none.fl_str_mv Salgado Corrado, Ariel Olaf
Yuan, Ziyun
Caridi, Délida Inés
González, Marta C.
author Salgado Corrado, Ariel Olaf
author_facet Salgado Corrado, Ariel Olaf
Yuan, Ziyun
Caridi, Délida Inés
González, Marta C.
author_role author
author2 Yuan, Ziyun
Caridi, Délida Inés
González, Marta C.
author2_role author
author
author
dc.subject.none.fl_str_mv ACCESSIBILITY
CDR
CENSUS
DEMAND
EXPOSURE
GREEN SPACES
OSM
PARKS
SEGREGATION
topic ACCESSIBILITY
CDR
CENSUS
DEMAND
EXPOSURE
GREEN SPACES
OSM
PARKS
SEGREGATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
https://purl.org/becyt/ford/2.1
https://purl.org/becyt/ford/2
https://purl.org/becyt/ford/5.7
https://purl.org/becyt/ford/5
dc.description.none.fl_txt_mv This work presents a portable framework to estimate potential park demand and park exposure through bipartite weighted networks. We use mobility information and open spatial information. Mobility information comes in the form of daily activities sampled from a model based on Call Detail Records (CDR). Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. The framework summarizes each city’s information into one bipartite weighted network with the link weights representing the number of potential visits to a park from each census tract on an average weekday. We compare park exposure and park demand in Greater Los Angeles and Greater Boston in a pre-pandemic scenario. The park exposure of a census tract is calculated as the number of parks surrounding the daily activities of its inhabitants. The demand of a park is calculated as the number of daily activities surrounding it. We find that both cities’ distribution of park exposure have similar shape with Boston having a higher average. On the other hand, the distribution of park demand is very similar in both cities, although their park spatial distributions are different. We include racial/ethnic information from the Census to explore how the park exposure connects tracts of different racial/ethnic groups. We associate parks to racial/ethnic groups based on the number of visitors from each group. Parks within minorities’ tracts are mostly used by majority groups. Finally, through detecting communities in the network, we find that park exposure connects the cities locally, linking parks to their tracts nearby. Furthermore, we find a significant spatial correlation between network communities and different racial/ethnic composition in Los Angeles. This way, patterns of park exposure reproduce the separation among demographic groups of the city.
Fil: Salgado Corrado, Ariel Olaf. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
Fil: Yuan, Ziyun. No especifíca;
Fil: Caridi, Délida Inés. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Calculo. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Calculo; Argentina
Fil: González, Marta C.. Lawrence Berkeley National Laboratory; Estados Unidos. University of California at Berkeley; Estados Unidos
description This work presents a portable framework to estimate potential park demand and park exposure through bipartite weighted networks. We use mobility information and open spatial information. Mobility information comes in the form of daily activities sampled from a model based on Call Detail Records (CDR). Spatial information comprise parks represented through OpenStreetMaps polygons and census tracts from the 2010 decennial US Census. The framework summarizes each city’s information into one bipartite weighted network with the link weights representing the number of potential visits to a park from each census tract on an average weekday. We compare park exposure and park demand in Greater Los Angeles and Greater Boston in a pre-pandemic scenario. The park exposure of a census tract is calculated as the number of parks surrounding the daily activities of its inhabitants. The demand of a park is calculated as the number of daily activities surrounding it. We find that both cities’ distribution of park exposure have similar shape with Boston having a higher average. On the other hand, the distribution of park demand is very similar in both cities, although their park spatial distributions are different. We include racial/ethnic information from the Census to explore how the park exposure connects tracts of different racial/ethnic groups. We associate parks to racial/ethnic groups based on the number of visitors from each group. Parks within minorities’ tracts are mostly used by majority groups. Finally, through detecting communities in the network, we find that park exposure connects the cities locally, linking parks to their tracts nearby. Furthermore, we find a significant spatial correlation between network communities and different racial/ethnic composition in Los Angeles. This way, patterns of park exposure reproduce the separation among demographic groups of the city.
publishDate 2022
dc.date.none.fl_str_mv 2022-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/203614
Salgado Corrado, Ariel Olaf; Yuan, Ziyun; Caridi, Délida Inés; González, Marta C.; Exposure to parks through the lens of urban mobility; Springer Science and Business Media Deutschland GmbH; EPJ Data Science; 11; 1; 12-2022; 1-21
2193-1127
CONICET Digital
CONICET
url http://hdl.handle.net/11336/203614
identifier_str_mv Salgado Corrado, Ariel Olaf; Yuan, Ziyun; Caridi, Délida Inés; González, Marta C.; Exposure to parks through the lens of urban mobility; Springer Science and Business Media Deutschland GmbH; EPJ Data Science; 11; 1; 12-2022; 1-21
2193-1127
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1140/epjds/s13688-022-00351-9
info:eu-repo/semantics/altIdentifier/url/https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-022-00351-9
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer Science and Business Media Deutschland GmbH
publisher.none.fl_str_mv Springer Science and Business Media Deutschland GmbH
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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