Chiara BORDON, Università Iuav di Venezia, Italy
The abstract proposed is based on the Master’s Thesis in Local Development (University of Padua) defended by the undersigned on September 21st, 2021.
The aim of the work is to provide local Public Administration with a cost-effective and scalable solution for the improvement of accessibility in the urban environment, by also fostering citizens’ participation and ownership in local decision-making processes.
The thesis is developed starting from a legal framework overview at an international level, landing to the Italian law (L. 104/1992) that prescribes the adoption of Plans for the Elimination of Architectural Barriers (PEBA, in Italian) at the administrative level. The focus is then shifted at the local PEBA, approved by the Municipality of Rovigo in 2019, which highlights a remarkably positive situation for the accessibility inside public buildings. The outdoor urban space is generally neglected and hinders equality for citizens with disabilities.
The work is therefore to link the already existing criteria with the ones suggested at the international level [(UN, 2006), (EC, 2021)] to create a more inclusive urban environment. To do so, thanks to a deep methodological analysis, the mapping tool adopted has been a bot for a famous chat app, that generates CC0 geo-data that can be analyzed with GIS software. The geospatial analysis proved the current criteria to be insufficient to declare full accessibility, as the barriers mapped in the city center in the surroundings the assessed buildings are nearly a hundred and consist mainly of poor keep-up or old planning.
The data so far collected proves the need for more systematic analysis and urban planning in this field, and the database produced can be used as a decision support system by the PA. Moreover, the work can be scaled up by the local government, thanks to regional projects that are currently being funded for this purpose in the study area.
Mots clés : Urban Planning|Accessibility of the built environment|Open Data|Crowdsource|GIS analysis
A102817CB