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Where does the city start? Urban sprawl and compacity

This research examines how to characterize urban sprawl and its implications using various data sources such as Urban Audit, CLC, and soil sealing. It analyzes urban form, percentage of built-up area, compacity index, dynamics, and more, in order to gain insights into the scale dependency of the process and the differential patterns of urban development in cities like Madrid. The study also emphasizes the need for improved delineation methods and visualization tools for dynamic processes.

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Where does the city start? Urban sprawl and compacity

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  1. Where does the city start? Urban sprawl and compacity Jaume Fons-Esteve (Universitat Autònoma de Barcelona) Evidence on European Land Use, 24 May, 2010

  2. What is the unit of analysis?

  3. How to characterise urban sprawl?

  4. Delineation of cities Administrative Agglomerations (END - DG ENV) Urban Audit (Eurostat) Functional UMZ (EEA) Morphological

  5. Paris City center (UA) CLC 2006

  6. Paris City center (UA) City (UA) Kernel (UA)

  7. Paris City center (UA) City (UA) Kernel (UA) UMZ

  8. Paris City center (UA) City (UA) Kernel (UA) UMZ LUZ (UA)

  9. How to characterise urban sprawl?

  10. Data Soil sealing (1) Resolution Urban Audit (1) CLC (3) Extension & Coverage

  11. Implications of different resolution (=) - Urban Audit + CLC

  12. Urban sprawl • Urban form/pattern • Percentage of built-up area • Soil sealing per capita • Compacity index • Mixed uses • Proximity: distance of patches to city centre (normalised accumulated distance) • Dynamics (absolute and comparison centre-peryphery) • Relative increase of built-up area • Land take per capita • Degree of redevelopment • Use of new built-up areas

  13. Dynamics

  14. Urban form

  15. Differential urban patterns: Madrid Residential areas Commercial and industrial areas

  16. 1990-2000

  17. 2000-2006

  18. Conclusions • Need to improve our understanding of scale dependency of process (not simple aggregation) • Use the right delineation fit to purpose of analysis • Data: socio-economic data available at grid level • New visualization tools for dynamic process

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