MAPEAMENTO DA VULNERABILIDADE SOCIAL EM SETORES CENSITÁRIOS:

This study aimed to construct and analyze the Social Vulnerability Index (SVI) of the municipality of Eunápolis, Bahia, Brazil, based on data from the 2010 Demographic Census. The methodology involved using Principal Component Analysis (PCA) for variable selection and weighting, and the QGIS software for spatialization of the results at the census tract level. Three fundamental dimensions of vulnerability were considered: human capital, urban infrastructure, and income and employment. The results indicated that most of the municipal territory was classified as having high or very high levels of vulnerability, with a particular emphasis on the human capital dimension, which was strongly impacted by high illiteracy rates, and on urban infrastructure, marked by deficiencies in access to basic services. The income and employment dimension revealed significant gender inequalities and the persistence of poverty pockets. The integration of these dimensions showed that more than two-thirds of the municipality experiences adverse socioeconomic conditions, highlighting priority areas for government intervention. It is concluded that the SVI is an effective analytical tool to support territorial planning and guide the formulation of more equitable and targeted public policies. It overcomes the limitations of aggregated indicators such as the Municipal Human Development Index (MHDI) and contributes to the promotion of inclusive and sustainable development in Eunápolis.

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Publication Details

Journal
Brazilian Geographical Journal
Published
2025-06-30
DOI
https://doi.org/10.14393/bgj-v16n1-a2025-73530
Primary Topic
Social and Political Issues
Type
article
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article

MAPEAMENTO DA VULNERABILIDADE SOCIAL EM SETORES CENSITÁRIOS:

Sandra Adriana Neves Nunes, Emília Rahnemay Kohlman Rabbani, Roberto Muhájir Rahnemay Rabbani, Jeorge Luís Martins de Oliveira
Brazilian Geographical Journal
Social and Political Issues
article

MAPEAMENTO DA VULNERABILIDADE SOCIAL EM SETORES CENSITÁRIOS:

Sandra Adriana Neves Nunes, Emília Rahnemay Kohlman Rabbani, Roberto Muhájir Rahnemay Rabbani, Jeorge Luís Martins de Oliveira
article en

Abstract

This study aimed to construct and analyze the Social Vulnerability Index (SVI) of the municipality of Eunápolis, Bahia, Brazil, based on data from the 2010 Demographic Census. The methodology involved using Principal Component Analysis (PCA) for variable selection and weighting, and the QGIS software for spatialization of the results at the census tract level. Three fundamental dimensions of vulnerability were considered: human capital, urban infrastructure, and income and employment. The results indicated that most of the municipal territory was classified as having high or very high levels of vulnerability, with a particular emphasis on the human capital dimension, which was strongly impacted by high illiteracy rates, and on urban infrastructure, marked by deficiencies in access to basic services. The income and employment dimension revealed significant gender inequalities and the persistence of poverty pockets. The integration of these dimensions showed that more than two-thirds of the municipality experiences adverse socioeconomic conditions, highlighting priority areas for government intervention. It is concluded that the SVI is an effective analytical tool to support territorial planning and guide the formulation of more equitable and targeted public policies. It overcomes the limitations of aggregated indicators such as the Municipal Human Development Index (MHDI) and contributes to the promotion of inclusive and sustainable development in Eunápolis.

Brazilian Geographical JournalVol. 16(1)
Universidade Federal do Sul da Bahia (BR), Secretaria da Educação do Estado da Bahia (BR), Universidade de Pernambuco (BR)
Openalex Percentile: Top 63%
Social and Political Issues
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MAPEAMENTO DA VULNERABILIDADE SOCIAL EM SETORES CENSITÁRIOS: — Sandra Adriana Neves Nunes, Emília Rahnemay Kohlman Rabbani, et al. · Brazilian Geographical Journal (2025) | TGRS Research Map | TGRS