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Scattered or polycentric? Untangling urban growth in three southern European metropolitan regions through exploratory spatial data analysis

Author

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  • Luca Salvati

    (Council for Agricultural Research and Economics (CREA))

  • Giuseppe Venanzoni

    (’Sapienza’ University of Rome)

  • Pere Serra

    (Universitat Autònoma de Barcelona)

  • Margherita Carlucci

    (’Sapienza’ University of Rome)

Abstract

The present study illustrates an exploratory spatial data analysis (ESDA) aimed at investigating changes in the distribution of built-up areas in three southern European metropolitan regions (Barcelona, Rome and Athens). An approach based on global Moran’s indexes of spatial autocorrelations was proposed to assess similarities in the spatial organization of the three regions, based on land-use data for 1960 and 2010. Compact monocentric, scattered low-density and mixed polycentric structures were compared in the three regions using local Moran’s indexes computed at two different scales, “urban” (5 km radius) and “regional” (20 km radius). The proposed approach identifies emerging trends in scattered monocentric or polycentric development. Our results outline the trend toward scattered urban expansion for the three cities, with signs of a modest shift toward polycentrism in Barcelona. ESDA provides basic information needed for policies promoting spatially balanced, sustainable development in originally compact and economically segmented regions.

Suggested Citation

  • Luca Salvati & Giuseppe Venanzoni & Pere Serra & Margherita Carlucci, 2016. "Scattered or polycentric? Untangling urban growth in three southern European metropolitan regions through exploratory spatial data analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(1), pages 1-29, July.
    • Handle: RePEc:spr:anresc:v:57:y:2016:i:1:d:10.1007_s00168-016-0758-5
    DOI: 10.1007/s00168-016-0758-5
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    4. Yongqiang Lv & Xinqi Zheng & Lin Zhou & Lulu Zhang, 2017. "Decentralization and Polycentricity: Spatial Changes of Employment in Beijing Metropolitan Area, China," Sustainability, MDPI, vol. 9(10), pages 1-17, October.
    5. Hening Widi Oetomo & Marsudi Lestariningsih & Susanti, 2017. "Spatial Analysis of Newspaper Sales in East Surabaya Traffict Lights Using Moran Index," International Journal of Business and Administrative Studies, Professor Dr. Bahaudin G. Mujtaba, vol. 3(5), pages 166-174.
    6. Fei Xie & Shuaibing Zhang & Kaixu Zhao & Fengmei Quan, 2022. "Evolution Mode, Influencing Factors, and Socioeconomic Value of Urban Industrial Land Management in China," Land, MDPI, vol. 11(9), pages 1-33, September.
    7. Roberta Fontan Pereira Galvão & Andrea Yuri Flores Urushima & Shoichiro Hara & Wil De Jong, 2020. "Analysis of Land Transition Features and Mechanisms in Peripheral Areas of Kyoto (1950–1960)," Sustainability, MDPI, vol. 12(11), pages 1-22, June.
    8. John R. Hipp & Jae Hong Kim & Benjamin Forthun, 2021. "Proposing new measures of employment deconcentration and spatial dispersion across metropolitan areas in the US," Papers in Regional Science, Wiley Blackwell, vol. 100(3), pages 815-841, June.

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    JEL classification:

    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population

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