The purpose of the paper is twofold. First, the many sustainable mobility strategies developed in 37 European neighbourhoods are presented, and how these are related to other spatial patterns and urban form (functional mix, density, green circulation, technologies for energy saving, education and sensitising, stakeholders’ participation, etc.) is discussed. Second, commonalities and differences among the neighbourhoods are investigated through two different clustering techniques: Cluster Analysis and Self Organising Maps (SOM) Neural Network.

Assessing sustainable mobility at neighbourhood level. Cluster analysis and Self Organising Maps (SOM) Neural Network

DIAPPI, LIDIA;MALTESE, ILA STEFANIA;MARIOTTI, ILARIA
2012

Abstract

The purpose of the paper is twofold. First, the many sustainable mobility strategies developed in 37 European neighbourhoods are presented, and how these are related to other spatial patterns and urban form (functional mix, density, green circulation, technologies for energy saving, education and sensitising, stakeholders’ participation, etc.) is discussed. Second, commonalities and differences among the neighbourhoods are investigated through two different clustering techniques: Cluster Analysis and Self Organising Maps (SOM) Neural Network.
Planning Support Tools: Policy Analysis, Implementation and Evaluation
9788856854633
Sustainable mobility; neighbourhood; cluster analysis; SOM
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/658084
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