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Urban delineations and data bases in Europe, ESPON Data Base M4D

Urban delineations and data bases in Europe, ESPON Data Base M4D. A.Bretagnolle 1 , M.Guérois 1 , H. Mathian 1 , A.Pavard 1 1 UMR Géographie-cités, Universités Paris 1 et Paris 7 Aalborg, ESPON Open Seminar 13 June 2012, Development of urban regions in Europe: Key drivers and perspectives.

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Urban delineations and data bases in Europe, ESPON Data Base M4D

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  1. Urban delineations and data bases in Europe, ESPON Data Base M4D A.Bretagnolle1, M.Guérois1, H. Mathian1, A.Pavard1 1UMR Géographie-cités, Universités Paris 1 et Paris 7 Aalborg, ESPON Open Seminar 13 June 2012, Development of urban regions in Europe: Key drivers and perspectives

  2. Introduction Severalurban DB currentlyavailableatEuropeanscale: • How to manage thisdiversity? • Twoworks in progress: • Integratingspecifications • -Evaluatinginteroperability • How to enrich the databases? • By agregationsfrom local data • (using a referencelevel?)

  3. 1. Integratingspecifications (morphological DB) The aimis to formalize the metadata in order to help the userschoosingthe mostappropriate DB regardingtheirscientifictargets Methods: usingsame « grammar » to describe the DB and makethem more comparable Results: specificities (sources, parameters) but alsostrongsimilarites (construction steps)

  4. Integratingspecifications (FUA, work in progress) Methods: samethan for morphological areas Results: specificities (sources for urbancore, parameters, the waypolycentricity cases are considered) but alsostrongsimilarities(construction steps)

  5. 2. Evaluatinginteroperabilitybetweenurban DB (degree of compatibility between data) The aimis to evaluate if wecan compare someindicatorsmeasured for a city or urbanregion in the 2 DB, or enrich a DB using the data of another DB A genericmethod (here, applied to MUA and UMZ): a. Defining(a priori) 4 types of overlapping

  6. 2. Evaluatinginteroperabilitybetweenurban DB b. Definingstatisticalindicatorsthatcandescribethesedifferent configurations

  7. 2. Evaluatinginteroperabilitybetweenurban DB Interoperability c. Testing the sensitivity of the indicators to real configurations of overlapping (476 MUA > 100 000 inh. And UMZ) Results: 1) An evaluationof interoperability

  8. 2. Evaluatinginteroperabilitybetweenurban DB Results: 1) An evaluationof interoperability 2) A typologyof MUA according to the built-up area patterns

  9. 3. How to enrichurbandatabases? Agregation of data from local level to the meso-level of the cities:1) fromLAU2 (richness of socio-demographic data): diffentialaccessibility of bluecollars or executives2) fromgrid data (fine resolution for environ. , demog. data or other): number of people locatedatlessthanhalf an hourfrom the city center…

  10. 3. How to enrichurbandatabases? « Whichreferencelevel » dependsalso on the scale of the study Local scale: gridisfiner and much more accurate Cost-transportation zones: no real differences

  11. The ESPON Urban OLAP Cube: a tool for combiningandanalysingheterogeneousurban data Roger Milego (roger.milego@uab.cat) Aalborg, ESPON Open Seminar 13-14 June 2012

  12. OLAP technology • OLAP (OnLine Analytical Processing): category of software tools designed to help in the extraction of information from data to support better decision-making. • Multidimensionaldata model, complex analytical and ad-hoc queries, rapid execution time. • OLAP Cube = some countable variables (measures) such as ha. aggregated by a set of dimensions: spatial (e.g. NUTS regions), thematic (e.g. land cover) and temporal. • An OLAP Cube can be queried online and offline (.CUB file, from MS Excel).

  13. OLAP Cube: A “cocktail” of data

  14. Urban OLAP Cube NUTS 100 x 100 m Grid OLAP Cube OLAP Database Soil sealing Urban Atlas Corine Land Cover LUZ SupraUMZ End Users Also Protected Sites (N2000+CDDA) Population figures and Area as measures

  15. Thank you for your attention! Roger Milego (roger.milego@uab.cat) Aalborg, ESPON Open Seminar 13-14 June 2012

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