Smart data for smart city morphology : the case of Meridia neighborhood in Nice, France
Caglioni, M. and Fusco, G. and Venerandi, A. (2020) Smart data for smart city morphology : the case of Meridia neighborhood in Nice, France. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 6. pp. 33-39. (https://doi.org/10.5194/isprs-annals-VI-4-W2-2020-...)
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Abstract
Nowadays, cities have to withstand multiple challenges such as climate change, increasing urban population, economic cycles, health crises, traffic congestion, rising levels of energy consumption and citizens' expectations. Recently, the smart city has been proposed as a model to face such challenges. Underneath its digital skin, which provides ubiquitous high-tech solutions, the smart city is often presented in continuity with the traditional city, while getting inspired by the modernist or international paradigm (free standing towers, high density development and functional zoning). Is this actually the case? To understand the features of urban form of new smart developments and how these relate to existing approaches in city planning, we propose a quantitative methodology to compare features of multiple city areas, which is based on the computation of a set of 3D morphometrics of the urban environment, and descriptive statistics for each metric. We applied this methodology to compare Nice Meridia, a French example of smart city development, with a traditional neighbourhood, located in the same city. Outcomes show that the smart city neighbourhood shares some morphological aspects with the traditional city, but differs significantly in other respects, showing the interest of quantitative 3D metrics.
ORCID iDs
Caglioni, M., Fusco, G. and Venerandi, A. ORCID: https://orcid.org/0000-0003-4887-0120;-
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Item type: Article ID code: 76710 Dates: DateEvent15 September 2020Published15 September 2020AcceptedSubjects: Fine Arts > Architecture Department: Faculty of Engineering > Architecture Depositing user: Pure Administrator Date deposited: 08 Jun 2021 13:36 Last modified: 11 Nov 2024 13:06 URI: https://strathprints.strath.ac.uk/id/eprint/76710