Multiscale analysis of coastal social vulnerability to extreme events in Brazil

Cibele Oliveira Lima (), Jarbas Bonetti (), Tiago Borges Ribeiro Gandra (), Carla Bonetti () and Marinez Eymael Garcia Scherer ()
Additional contact information
Cibele Oliveira Lima: Federal University of Santa Catarina (UFSC)
Jarbas Bonetti: Federal University of Santa Catarina (UFSC)
Tiago Borges Ribeiro Gandra: Federal Institute of Education, Science and Technology of Rio Grande do Sul (IFRS)
Carla Bonetti: Federal University of Santa Catarina (UFSC)
Marinez Eymael Garcia Scherer: Federal University of Santa Catarina (UFSC)

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2024, vol. 120, issue 2, No 9, 1163-1184

Abstract: Abstract Issues related to prevention and mitigation of extreme events’ impacts, intensified by climate changes, have been receiving progressive attention from the academic community. Impacts are increasingly expensive for the society, particularly in coastal zones, where population growth and concentration of economic activities modify the landscape and alter the natural balance of coastal processes, contributing to increase population’s vulnerability to these events. Considering the growing need to measure the social vulnerability of coastal populations and the lack of studies that focus on the effects of changing spatial scales over vulnerability analysis, this article proposes a methodology for obtaining a multiscale Coastal Social Vulnerability Index to extreme events (SVI-Coast) for 281 municipalities facing the sea in Brazil. The proposed methodology employed data from the most recent available national demographic census (2010), over which descriptive and multivariate statistical techniques were applied, considering three units of spatial aggregation: states, municipalities, and census sectors. Results show that in Brazil there is a tendency for concentration of greater social vulnerabilities in North and Northeast regions and that the key variables responsible for this are income and access to infrastructure, which are underprovided in these regions. This methodology can be replicated on multiple spatial scales, contributing to provide scientific knowledge capable of assisting decision-making by local and regional managers, especially by identifying priority areas, which need urgent actions for mitigation and reduction of coastal social vulnerability.

Keywords: Census data; PCA (principal component analysis); Vulnerable populations; Composite indices; Brazilian coastal zone (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-023-06246-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:120:y:2024:i:2:d:10.1007_s11069-023-06246-w

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-023-06246-w

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().