Multiscale analysis of coastal social vulnerability to extreme events in Brazil

被引:0
作者
Lima, Cibele Oliveira [1 ]
Bonetti, Jarbas [2 ]
Gandra, Tiago Borges Ribeiro [3 ]
Bonetti, Carla [2 ]
Scherer, Marinez Eymael Garcia [2 ]
机构
[1] Fed Univ Santa Catarina UFSC, Postgrad Program Geog, Florianopolis, SC, Brazil
[2] Fed Univ Santa Catarina UFSC, Dept Oceanog, Florianopolis, SC, Brazil
[3] Fed Inst Educ Sci & Technol Rio Grande Sul IFRS, Rio Grande, RS, Brazil
关键词
Census data; PCA (principal component analysis); Vulnerable populations; Composite indices; Brazilian coastal zone; CLIMATE-CHANGE; IMPACTS; HAZARDS; GENDER; INDEX; INDICATORS; PCA;
D O I
10.1007/s11069-023-06246-w
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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.
引用
收藏
页码:1163 / 1184
页数:22
相关论文
共 61 条
[1]   Using Principal Component Analysis for information-rich socio-ecological vulnerability mapping in Southern Africa [J].
Abson, David J. ;
Dougill, Andrew J. ;
Stringer, Lindsay C. .
APPLIED GEOGRAPHY, 2012, 35 (1-2) :515-524
[2]  
[Anonymous], 2005, NATURAL DISASTER HOT
[3]  
[Anonymous], 2004, Reducing Disaster Risk: A Challenge for Development
[4]   A flood vulnerability index for coastal cities and its use in assessing climate change impacts [J].
Balica, S. F. ;
Wright, N. G. ;
van der Meulen, F. .
NATURAL HAZARDS, 2012, 64 (01) :73-105
[5]   PCA STABILITY AND CHOICE OF DIMENSIONALITY [J].
BESSE, P .
STATISTICS & PROBABILITY LETTERS, 1992, 13 (05) :405-410
[6]  
Bonetti J, 2017, GEOINFORMATICS MARIN, P367, DOI [10.1201/9781315181523-17, DOI 10.1201/9781315181523-17]
[7]  
Bonetti J., 2013, Coast. Res. Libr., V1000, P423, DOI [DOI 10.1007/978-94-007-5234-4_16, 10.1007/978-94-007-5234-4_16/FIGURES/9, DOI 10.1007/978-94-007-5234-4_16/FIGURES/9]
[8]   Erosion hazard vulnerability of US coastal counties [J].
Boruff, BJ ;
Emrich, C ;
Cutter, SL .
JOURNAL OF COASTAL RESEARCH, 2005, 21 (05) :932-942
[9]  
BRASIL, 2004, PRESIDENCIA REPUBLIC
[10]  
Bryant FB, 1995, Principal components analysis and exploratory and confirmatory factor analysis. Reading and understanding multivariate statistics, P99