Describing the residential valorisation of urban space at the street level. The French Riviera as example

Alessandro Venerandi, Giovanni Fusco

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

There is a growing concern regarding the use of relatively coarse units for the aggregation of various spatial information. Researchers thus suggest that the street segment might be better suited than areal units for carrying out such a task. Furthermore, the street segment has recently become one of the most prominent spatial units, for example, to study street network centrality, retail density, and urban form. In this paper, we thus propose to use the street segment as unit of analysis for calculating the residential valorisation of urban space. To be more specific, we define a protocol that characterises street segments through a measure of central tendency and one of dispersion of prices. Moreover, through Bayesian clustering, it classifies street segments according to the most probable combination house type-valuation to provide a picture of local submarkets. We apply this methodology to the housing transactions exchanged in the French Riviera, in the period 2008–2017, and observe that outputs seem to align with local specificities of the housing market of that region. We suggest that the proposed protocol can be useful as an explorative tool to question and interpret the housing market, in any metropolitan region, at a fine level of spatial granularity.

Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2020
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Chiara Garau, Ivan Blecic, David Taniar, Bernady O. Apduhan, Ana Maria A.C. Rocha, Eufemia Tarantino, Carmelo Maria Torre, Yeliz Karaca
Place of PublicationCham, Switzerland
Pages505-520
Number of pages16
DOIs
Publication statusPublished - 29 Sep 2020
Event20th International Conference on Computational Science and Its Applications - Cagliari, Italy
Duration: 1 Jul 20204 Jul 2020
https://2020.iccsa.org/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12252 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Computational Science and Its Applications
Abbreviated titleICCSA 2020
Country/TerritoryItaly
CityCagliari
Period1/07/204/07/20
Internet address

Keywords

  • Bayesian clustering
  • French Riviera
  • house prices
  • street network
  • summary statistics

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