Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient

Recent regional research has taken an ‘infrastructure turn’ where scholars have called for examining the transformative ability of different infrastructures in causing systemic inequities beyond the spatial conception of ‘urban and the other’. This research examines the interconnected impact of infr...

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Autores principales:	Shrobona Karkun Sen, Hamil Pearsall, Victor Hugo Gutierrez-Velez, Melissa R. Gilbert
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	regional infrastructure transportation green spaces Geographically Weighted Regression Pennsylvania New Jersey Agriculture S
Acceso en línea:	https://doaj.org/article/23f2e3aceacf421487424ea1001f7a39
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id	oai:doaj.org-article:23f2e3aceacf421487424ea1001f7a39
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spelling	oai:doaj.org-article:23f2e3aceacf421487424ea1001f7a392021-11-25T18:09:38ZMeasuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient10.3390/land101112022073-445Xhttps://doaj.org/article/23f2e3aceacf421487424ea1001f7a392021-11-01T00:00:00Zhttps://www.mdpi.com/2073-445X/10/11/1202https://doaj.org/toc/2073-445XRecent regional research has taken an ‘infrastructure turn’ where scholars have called for examining the transformative ability of different infrastructures in causing systemic inequities beyond the spatial conception of ‘urban and the other’. This research examines the interconnected impact of infrastructure systems on existing spatial inequities through a study in metropolitan Philadelphia, Pennsylvania. This study investigates whether the urban-rural (U-R) gradient concept can enhance understanding of the spatial relationship between socioeconomic indicators and infrastructure systems. Indicators of spatial inequalities were regressed against infrastructure variables and imperviousness, as a proxy for the U-R gradient, using multivariate and spatial regression methods. The models show that imperviousness has a positive correlation with the concentration of racialized minorities and a negative correlation with access to health insurance. The study also shows that the predictive power of multiple infrastructures varies across space and does not adhere to urban boundaries or the U-R gradient. The complex interactions among different infrastructures shape inequities and require further inquiry in urban regions around the world.Shrobona Karkun SenHamil PearsallVictor Hugo Gutierrez-VelezMelissa R. GilbertMDPI AGarticleregional infrastructuretransportationgreen spacesGeographically Weighted RegressionPennsylvaniaNew JerseyAgricultureSENLand, Vol 10, Iss 1202, p 1202 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	regional infrastructure transportation green spaces Geographically Weighted Regression Pennsylvania New Jersey Agriculture S
spellingShingle	regional infrastructure transportation green spaces Geographically Weighted Regression Pennsylvania New Jersey Agriculture S Shrobona Karkun Sen Hamil Pearsall Victor Hugo Gutierrez-Velez Melissa R. Gilbert Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient
description	Recent regional research has taken an ‘infrastructure turn’ where scholars have called for examining the transformative ability of different infrastructures in causing systemic inequities beyond the spatial conception of ‘urban and the other’. This research examines the interconnected impact of infrastructure systems on existing spatial inequities through a study in metropolitan Philadelphia, Pennsylvania. This study investigates whether the urban-rural (U-R) gradient concept can enhance understanding of the spatial relationship between socioeconomic indicators and infrastructure systems. Indicators of spatial inequalities were regressed against infrastructure variables and imperviousness, as a proxy for the U-R gradient, using multivariate and spatial regression methods. The models show that imperviousness has a positive correlation with the concentration of racialized minorities and a negative correlation with access to health insurance. The study also shows that the predictive power of multiple infrastructures varies across space and does not adhere to urban boundaries or the U-R gradient. The complex interactions among different infrastructures shape inequities and require further inquiry in urban regions around the world.
format	article
author	Shrobona Karkun Sen Hamil Pearsall Victor Hugo Gutierrez-Velez Melissa R. Gilbert
author_facet	Shrobona Karkun Sen Hamil Pearsall Victor Hugo Gutierrez-Velez Melissa R. Gilbert
author_sort	Shrobona Karkun Sen
title	Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient
title_short	Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient
title_full	Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient
title_fullStr	Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient
title_full_unstemmed	Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient
title_sort	measuring equity through spatial variability of infrastructure systems across the urban-rural gradient
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/23f2e3aceacf421487424ea1001f7a39
work_keys_str_mv	AT shrobonakarkunsen measuringequitythroughspatialvariabilityofinfrastructuresystemsacrosstheurbanruralgradient AT hamilpearsall measuringequitythroughspatialvariabilityofinfrastructuresystemsacrosstheurbanruralgradient AT victorhugogutierrezvelez measuringequitythroughspatialvariabilityofinfrastructuresystemsacrosstheurbanruralgradient AT melissargilbert measuringequitythroughspatialvariabilityofinfrastructuresystemsacrosstheurbanruralgradient
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Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient

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