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Smart citizens enabling resilient neighbourhoods (SCERN): Participatory mapping platform for resilience planning at a neighbourhood scale

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posted on 2025-06-26, 13:08 authored by Christopher Macdonald Hewitt, Anna Do, Suzanne ElayanSuzanne Elayan, Rob Feick, Oliver Gruebner, Emily Rank, Krystelle Shaughnessy, Haley Sheppard, Marin Solter, Martin SykoraMartin Sykora, Ketan Shankardass

Urban communities face a range of stressors, including crime, pollution, and infrastructure challenges, which disproportionately affect marginalized populations. Resilience planning can help address these issues, but existing tools often lack meaningful community involvement. This paper introduces the Smart Citizens Enabling Resilient Neighbourhoods (SCERN) participatory mapping tool, a geo-questionnaire-based mobile GIS application designed to engage community members in resilience planning. SCERN facilitates data collection on local stressors and support systems through demographic profiling and spatial mapping, allowing for a nuanced understanding of place-based experiences. This tool was pilot tested at Wilfrid Laurier University in Waterloo Canada, with 33 participants in two groups submitting 113 place reports. Analysis of these reports identified key locations associated with spatial patterns of resilience as well as locations for targeted interventions. Using the tool in combination with a broader resilience planning framework ensures that community members are central to both data collection and planning processes. Furthermore, SCERN's adaptability renders it a valuable resource for urban planners, researchers, and community organizations. By fostering community participation, this tool provides a scalable and customizable approach to resilience planning that prioritizes equity and inclusion.

History

School

  • Loughborough Business School

Published in

Cities

Volume

165

Publisher

Elsevier Ltd

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0).

Acceptance date

2025-05-20

Publication date

2025-06-05

Copyright date

2025

ISSN

0264-2751

Language

  • en

Depositor

Dr Martin Sykora. Deposit date: 9 June 2025

Article number

106101

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