Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources

Compact development is one of the most effective solutions for sustainable urbanization under the rapid growth of the urban population. Great efforts have been made to measure urban physical compactness while limited attention has been paid to functional zoning of urban areas. Here, we introduce a n...

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Autores principales:	Ting Lan, Guofan Shao, Zhibang Xu, Lina Tang, Lang Sun
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Urban functional compactness Geospatial analysis Sustainable city Functional zoning Data integtation Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/bd6cf1d23ce04211af796d07e40eeb8e
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id	oai:doaj.org-article:bd6cf1d23ce04211af796d07e40eeb8e
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spelling	oai:doaj.org-article:bd6cf1d23ce04211af796d07e40eeb8e2021-12-01T04:37:31ZMeasuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources1470-160X10.1016/j.ecolind.2020.107177https://doaj.org/article/bd6cf1d23ce04211af796d07e40eeb8e2021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X2031116Xhttps://doaj.org/toc/1470-160XCompact development is one of the most effective solutions for sustainable urbanization under the rapid growth of the urban population. Great efforts have been made to measure urban physical compactness while limited attention has been paid to functional zoning of urban areas. Here, we introduce a novel index, called the functional compactness index (FCI), to quantify urban functional compactness through the integration of geospatial data sources, including Points of Interest (POIs) data, Road Network of OpenStreetMap (RNO) data, and National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data. The FCI does not require the analysis of the grid scale and thus, is technically simpler than conventional compactness index (CI). We examined the effectiveness of FCI on estimating urban compactness under four land use scenarios and in four Chinese cities. The results suggest that: (1) the FCI can comprehensively reflect the intensity of human activity, the differentiation between residential zones and other functional zones, and the mixing degree of different functional zones; (2) the FCI is not affected by the service radius of residential zones; (3) the FCI can reflect the overall and local-scale functional compactness of a city; and (4) the FCI can be used to effectively compare spatial characteristics of functional compactness among different cities. In conclusion, the FCI considers the rationality of urban functional layout, which not only is helpful for urban planning, but also enriches the quantitative methods of urban compactness evaluation.Ting LanGuofan ShaoZhibang XuLina TangLang SunElsevierarticleUrban functional compactnessGeospatial analysisSustainable cityFunctional zoningData integtationEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 107177- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Urban functional compactness Geospatial analysis Sustainable city Functional zoning Data integtation Ecology QH540-549.5
spellingShingle	Urban functional compactness Geospatial analysis Sustainable city Functional zoning Data integtation Ecology QH540-549.5 Ting Lan Guofan Shao Zhibang Xu Lina Tang Lang Sun Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources
description	Compact development is one of the most effective solutions for sustainable urbanization under the rapid growth of the urban population. Great efforts have been made to measure urban physical compactness while limited attention has been paid to functional zoning of urban areas. Here, we introduce a novel index, called the functional compactness index (FCI), to quantify urban functional compactness through the integration of geospatial data sources, including Points of Interest (POIs) data, Road Network of OpenStreetMap (RNO) data, and National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light data. The FCI does not require the analysis of the grid scale and thus, is technically simpler than conventional compactness index (CI). We examined the effectiveness of FCI on estimating urban compactness under four land use scenarios and in four Chinese cities. The results suggest that: (1) the FCI can comprehensively reflect the intensity of human activity, the differentiation between residential zones and other functional zones, and the mixing degree of different functional zones; (2) the FCI is not affected by the service radius of residential zones; (3) the FCI can reflect the overall and local-scale functional compactness of a city; and (4) the FCI can be used to effectively compare spatial characteristics of functional compactness among different cities. In conclusion, the FCI considers the rationality of urban functional layout, which not only is helpful for urban planning, but also enriches the quantitative methods of urban compactness evaluation.
format	article
author	Ting Lan Guofan Shao Zhibang Xu Lina Tang Lang Sun
author_facet	Ting Lan Guofan Shao Zhibang Xu Lina Tang Lang Sun
author_sort	Ting Lan
title	Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources
title_short	Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources
title_full	Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources
title_fullStr	Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources
title_full_unstemmed	Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources
title_sort	measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/bd6cf1d23ce04211af796d07e40eeb8e
work_keys_str_mv	AT tinglan measuringurbancompactnessbasedonfunctionalcharacterizationandhumanactivityintensitybyintegratingmultiplegeospatialdatasources AT guofanshao measuringurbancompactnessbasedonfunctionalcharacterizationandhumanactivityintensitybyintegratingmultiplegeospatialdatasources AT zhibangxu measuringurbancompactnessbasedonfunctionalcharacterizationandhumanactivityintensitybyintegratingmultiplegeospatialdatasources AT linatang measuringurbancompactnessbasedonfunctionalcharacterizationandhumanactivityintensitybyintegratingmultiplegeospatialdatasources AT langsun measuringurbancompactnessbasedonfunctionalcharacterizationandhumanactivityintensitybyintegratingmultiplegeospatialdatasources
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Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources

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