Multidimensionality in geospatial urban crime prevention modelling and decision support: the case of Porto, Portugal

• Type: Chapter or Part of a Book
• Date: 2022

Authors

Saraiva, Miguel (Author) FLUP; Marques, Teresa Sá (Author) FLUP; Ribeiro, Diogo (Author) FLUP; Amante, Ana (Author) Other

Book

Title: Urban crime prevention: multi-disciplinary approaches

Pages: 191-216

ISBN: 978-3-031-15107-1

Electronic ISBN: 978-3-031-15108-8

Publisher: Springer Cham

Indexing

Crossref

Scientific classification

CORDIS: Social sciences > Geography

Other information

DOI: 10.1007/978-3-031-15108-8_9

Abstract (EN): Striving for safe and secure cities continues to be a top priority in planning and strategic agendas, as feelings of insecurity and urban vulnerabilities often increase regardless of the fluctuations in crime statistics. More and more, it is recognized that creating safe environments is a task for multiple stakeholders and that the multidimensional characteristics of places are important predictors of the spatial distribution of crime and insecurity. However, only a few models conceptualize “the place” as a cumulative aggregation of micro-geographical patterns and territorial specificities, when correlating with the space–time variation of crime occurrences. Using the city of Porto, in Portugal, as a case study, this research aims to contribute to this growing field within the Geography of Crime/Criminology of Places literature, by developing a local-level multidimensional decision-support model, combining official crime statistics with morphological, functional, socio-economic and perceptual variables. Considering data at block level, with the support of Geographical Information Systems and statistical and data mining tools, including Multiple Correspondence Analysis, profiles are created that display the internal dynamics of the city and help establish which spatial determinants may contribute to explain the registered crime pattern. Such space-based know-how can support holistic and innovative public planning solutions for prevention, relevant for cohesion and integration.

Language: English

Type (Professor's evaluation): Scientific