Database of areas of interest for characterizing the population vulnerable to hydrogeomorphological processes in Brazil: A proposal for the Demographic Census
DOI:
https://doi.org/10.33448/rsd-v13i6.46213Keywords:
Demographic census; Operational areas of interest; Natural disasters; Vulnerability.Abstract
Every year, more people are affected by disasters caused by hydrological and geomorphological process in Brazil. Climate change scenarios point to a worsening of this situation, mainly affecting the most vulnerable population. In order to obtain representative statistical data and vulnerability indicators to support different risk management strategies, we present a preliminary census cartographic database for the whole of Brazil: the Areas of Operational Interest (AOIs) for hydrogeomorphological risk. The AOIs are a territorial grid used exclusively to activate specific questions in the Census questionnaire, based on a spatially controlled opening. A total of 12,726 AIOs were produced throughout Brazil, with an area to be covered by the census collection of 620.9 km², which corresponds to approximately 1.2% of Brazil's urban areas. The vast majority of AIOs occur on land that is highly vulnerable to dangerous hydrological processes (263.51km²) and landslides (113.75km²). 1,546,176 geocoded address records were identified in the National Register of Addresses for Statistical Purposes (CNEFE), the vast majority (84%) of which are private households. These households correspond to 1.4% of all census private households in Brazil in 2022. It is hoped that specific census information on the vulnerability of the population in AIOs will support priority actions in the social and economic spheres for the implementation of regional public policies that promote harm reduction throughout the country.
References
Adger, W. N. (2006). Vulnerability. Global Environmental Change, 16(3), 268-281. https://doi.org/10.1016/j.gloenvcha.2006.02.006.
Alves, H. P. d. F. (2006). Vulnerabilidade socioambiental na metrópole paulistana: uma análise sociodemográfica das situações de sobreposição espacial de problemas e riscos sociais e ambientais. R. bras. Est. Pop., 23(1), 43-59.
Antunes, M., & Damasco, F. (2022). Entrevista Censo 2022. Revista Brasileira de Geografia, 67(1), 230-249.
Assis Dias, M. C. D., Saito, S. M., Alvalá, R. C. D. S., Seluchi, M. E., Bernardes, T., Camarinha, P. I. M., Stenner, C., & Nobre, C. A. (2020). Vulnerability index related to populations at risk for landslides in the Brazilian Early Warning System (BEWS) [Article]. International Journal of Disaster Risk Reduction, 49, Article 101742. https://doi.org/10.1016/j.ijdrr.2020.101742.
Assis Dias, M. C. d., Saito, S. M., Alvalá, Regina C. d. S., Stenner, C., Pinho, G., Nobre, C. A., Fonseca, M. R. d. S., Santos, C., Amadeu, P., Silva, D., Lima, C. O., Ribeiro, J., Nascimento, F., & Corrêa, Clarissa d. O. (2018). Estimation of exposed population to landslides and floods risk areas in Brazil, on an intra-urban scale. International Journal of Disaster Risk Reduction, 31, 449-459. https://doi.org/https://doi.org/10.1016/j.ijdrr.2018.06.002.
Assis, J., Assis, F., Costa, C., & Martins, L. (2021). Mapeamento de áreas de risco: obtenção de mapas setoriais e de diagnóstico e intervenções Seminário de boas práticas em proteção e defesa civil.
Birkmann, J. (2007). Risk and vulnerability indicators at different scales: applicability, usefulness and policy implications. Environmental Hazards, 7(1), 20-31. https://doi.org/10.1016/j.envhaz.2007.04.002.
Birkmann, J. (Ed.). (2013). Measuring vulnerability to natural hazards: towards disaster-resilient societies (2a ed.). UNU Press.
Birkmann, J. (2013). Measuring vulnerability to promote disaster-resilient societies: conceptual frameworks and definitions. In J. Birkmann (Ed.), Measuring vulnerability to natural hazards: Towards disaster resilient societies (2ed., pp. 9–80). United Nations University Press. https://collections.unu.edu/eserv/UNU:2880/n9789280812022.
Borgatti, L., & Soldati, M. (2010). Landslides and climatic change. In I. Alcántara-Ayala & A. S. Goudie (Eds.), Geomorphological hazards and disaster prevention (pp. 87-96). Cambridge University Press. https://doi.org/10.1017/CBO9780511807527.008.
Brasil. (2015). Construindo cidades resilientes: minha cidade está se preparando. Ministério da Integração Nacional; Secretaria Nacional de Defesa Civil. 2015 (Tradução UNISDR). https://www.gov.br/mdr/pt-br/assuntos/protecao-e-defesa-civil/defesa-civil-no-brasil-e-no-mundo-1/cidades_resilientes_campanha_anterior_material.pdf.
Cardona, O. D. (2005). Indicators of disaster risk and risk management: main technical report. DB/IDEA Program of Indicators for Disaster Risk Management, National University of Colombia, Manizales.
Cardona, O. D., Aalst, M. K. v., Birkmann, J., Fordham, M., McGregor, G., Perez, R., Pulwarty, R. S., Schipper, E. L. F., & Sinh, B. T. (2012). Determinants of risk: exposure and vulnerability. In C. B. Field, V. Barros, T. F. Stocker, & Q. Dahe (Eds.), Managing the risks of extreme events and disasters to advance climate change adaptation. a special report of working groups I and II of the intergovernmental panel on climate change (IPCC) (pp. 65-108). Cambridge University Press. https://doi.org/10.1017/CBO9781139177245.005.
Carmo, R. d., & Valencio, N. (Eds.). (2014). Segurança humana no contexto dos desastres. RiMa Editora.
CEMADEN. (2016). Histórico de criação do CEMADEN. Centro Nacional de Monitoramento e Alerta de Desastres Naturais (CEMADEN). Retrieved 22/02 http://www2.cemaden.gov.br/historico-da-criacao-do-cemaden/.
CEPED-UFSC. (2022). A P&DC e os 30 anos de desastres no Brasil (1991 – 2020). Florianópolis, SC: Ministério do Desenvolvimento Regional, Secretaria Nacional de Proteção e Defesa Civil, Universidade Federal de Santa Catarina, Centro de Estudos de Pesquisa em Engenharia e Defesa Civil.
Chakraborty, S., & Mukhopadhyay, S. (2019). Assessing flood risk using analytical hierarchy process (AHP) and geographical information system (GIS): application in Coochbehar district of West Bengal, India. Natural Hazards, 99(1), 247-274. https://doi.org/10.1007/s11069-019-03737-7.
Chambers, R. (1989). Editorial Introduction: Vulnerability, Coping and Policy [https://doi.org/10.1111/j.1759-5436.1989.mp20002001.x].
CPRM. (2018). Manual de mapeamento de perigo e risco a movimentos gravitacionais de massa. Serviço Geológico do Brasil (SGB/CPRM).
CPRM. (2021). Guia de procedimentos técnicos do departamento de gestão territorial: setorização de áreas de risco geológico [Relatório Técnico] (Guia de procedimentos técnicos do departamento de gestão territorial, Issue. S. G. d. B.-. CPRM. https://rigeo.sgb.gov.br/jspui/handle/doc/22262.
CPRM. (2023a). Lista dos 821 municípios prioritários para a gestão de riscos. Secretaria Nacional de Proteção e Defesa Civil - SNPD. https://www.gov.br/mdr/pt-br/assuntos/emendasparlamentares/PUBL_relatorios_004_821_municipios_prioritarios.pdf.
CPRM. (2023b). Setorização de Riscos Geológicos. SGB - Serviço Geológico do Brasil - CPRM. https://www.sgb.gov.br/publique/Gestao-Territorial/Prevencao-de-Desastres/Saiba-Mais---Setorizacao-de-Riscos-Geologicos-5399.html.
Cutter, S. L. (1996). Vulnerability to environmental hazards. Progress in Human Geography, 20(4), 529-539. https://doi.org/10.1177/030913259602000407.
Cutter, S. L., Boruff, B. J., & Shirley, W. L. (2003). Social Vulnerability to Environmental Hazards*. Social Science Quarterly, 84(2), 242-261. https://doi.org/10.1111/1540-6237.8402002.
Cutter, S. L., Mitchell, J. T., & Scott, M. S. (2000). Revealing the vulnerability of people and Places: a case study of Georgetown County, South Carolina. Annals of the Association of American Geographers 9(4), 713–737. https://doi.org/http://dx.doi.org/10.1111/0004-5608.00219.
Damasco, F., & Antunes, M. (2020). Encontro de geografias no mapeamento censitário de localidades indígenas e quilombolas. Revista Brasileira de Geografia, 65(2), 2-24.
de Almeida, L. Q., Welle, T., & Birkmann, J. (2016). Disaster risk indicators in Brazil: A proposal based on the world risk index [Article]. International Journal of Disaster Risk Reduction, 17, 251-272. https://doi.org/10.1016/j.ijdrr.2016.04.007.
de Loyola Hummell, B. M., Cutter, S. L., & Emrich, C. T. (2016). Social Vulnerability to Natural Hazards in Brazil. International Journal of Disaster Risk Science, 7(2), 111-122. https://doi.org/10.1007/s13753-016-0090-9.
Debortoli, N. S., Camarinha, P. I. M., Marengo, J. A., & Rodrigues, R. R. (2017). An index of Brazil’s vulnerability to expected increases in natural flash flooding and landslide disasters in the context of climate change [journal article]. Natural Hazards, 86(2), 557-582. https://doi.org/10.1007/s11069-016-2705-2.
Deschamps, M. (2008). Estudo sobre a vulnerabilidade socioambiental na Região Metropolitana de Curitiba. Cadernos Metrópole, 19, 191-219.
Dias, M. C. d. A., Saito, S. M., & Fonseca, M. R. S. (2017). Aplicação de dados censitários para caracterização da população exposta em áreas de risco de deslizamentos em Blumenau, Santa Catarina. Revista Brasileira de Cartografia, 68(1).
Dilley, M. (2005). Setting priorities: global patterns of disaster risk. Paper of the Scientific Discussion on Extreme Natural Hazards, Royal Society.
Dilley, M., Chen, R. S., Deichmann, U., Lerner-Lam, A. L., Arnold, M., Agwe, J., Buys, P., Kjekstad, O., Lyon, B., & Yetman, G. (2005). Natural disaster hotspots. a global risk analysis. The World Bank Hazard Management Unit.
dos Santos Alvalá, R. C., de Assis Dias, M. C., Saito, S. M., Stenner, C., Franco, C., Amadeu, P., Ribeiro, J., Souza de Moraes Santana, R. A., & Nobre, C. A. (2019). Mapping characteristics of at-risk population to disasters in the context of Brazilian early warning system. International Journal of Disaster Risk Reduction, 41, 101326. https://doi.org/https://doi.org/10.1016/j.ijdrr.2019.101326.
Dourado, F., Arraes, T., & Silva, M. (2012). O megadesastre da região serrana do Rio de Janeiro – as causas do evento, os mecanismos dos movimentos de massa e a distribuição espacial dos investimentos de reconstrução no pós-desastre. Anuário do Instituto de Geociências - UFRJ, 35(2), 43-54. https://doi.org/10.11137/2012_2_43_54.
Fiocruz-BA. (2021). Indígenas e quilombolas no Censo Demográfico 2021: integração de informações geoespaciais para a ampliação da captação estatística. Fiocruz-BA. Retrieved 10 de outubro from https://ds.saudeindigena.icict.fiocruz.br/handle/bvs/3526.
Gallopín, G. C. (2006). Linkages between vulnerability, resilience, and adaptive capacity. Global Environmental Change, 16(3), 293-303. https://doi.org/https://doi.org/10.1016/j.gloenvcha.2006.02.004.
Gariano, S. L., & Guzzetti, F. (2016). Landslides in a changing climate. Earth-Science Reviews, 162, 227-252. https://doi.org/https://doi.org/10.1016/j.earscirev.2016.08.011.
Goerl, R. F., Kobiyama, M., & Pellerin, J. R. G. M. (2012). Proposta metodológica para mapeamento de áreas de risco a inundação: estudo de caso do município de Rio Negrinho – SC. Boletim de Geografia, 30(1). https://doi.org/10.4025/bolgeogr.v30i1.13519
Golnaraghi, M. (Ed.). (2012). Institutional partnerships in multi-hazard early warning systems: a compilation of seven national good practices and guiding principles. Springer.
Haque, U., da Silva, P. F., Devoli, G., Pilz, J., Zhao, B., Khaloua, A., Wilopo, W., Andersen, P., Lu, P., Lee, J., Yamamoto, T., Keellings, D., Jian-Hong, W., & Glass, G. E. (2019). The human cost of global warming: Deadly landslides and their triggers (1995–2014) [Article]. Science of The Total Environment, 682, 673-684. https://doi.org/10.1016/j.scitotenv.2019.03.415.
Hasegawa, N., Harada, S., Tanaka, S., Ogawa, S., Goto, A., Sasagawa, Y., & Washitake, N. (2012). Multi-Hazard Early Warning System in Japan. In M. Golnaraghi (Ed.), Institutional partnerships in multi-hazard early warning systems: a compilation of seven national good practices and guiding principles (pp. 181-215). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-25373-7.
IBGE. (2012). Os indígenas no Censo Demográfico 2010: primeiras considerações com base no quesito cor ou raça.
IBGE. (2013). Metodologia do Censo Demográfico 2010 (Vol. 41). Ministério do Planejamento, Orçamento e Gestão; Instituto Brasileiro de Geografia e Estatística - IBGE.
IBGE. (2018). População em áreas de risco no Brasil. Instituto Brasileiro de Geografia e Estatística / IBGE - Coordenação de Geografia.
IBGE. (2019). Padrão de registro de endereços - definições e orientações de uso. I. B. d. G. e. E. (IBGE).
IBGE. (2022a). Áreas urbanizadas do Brasil: 2019. Instituto Brasileiro de Geografia e Estatística - IBGE. https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=2101973.
IBGE. (2022b). Áreas Urbanizadas do Brasil: 2019 - notas técnicas. Instituto Brasileiro de Geografia e Estatística – IBGE. https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=2101973.
IBGE. (2023a). Censo demográfico 2022: quilombolas primeiros resultados do universo. Instituto Brasileiro de Geografia e Estatística - IBGE.
IBGE. (2023b). População em áreas de risco no Brasil | 2010. Instituto Brasileiro de Geografia e Estatística (BGE). https://www.ibge.gov.br/geociencias/informacoes-ambientais/estudos-ambientais/21538-populacao-em-areas-de-risco-no-brasil.html?=&t=o-que-e.
IBGE. (2024). Censo demográfico 2022: coordenadas geográficas dos endereços. Instituto Brasileiro de Geografia e Estatística - IBGE. https://www.ibge.gov.br/estatisticas/sociais/populacao/38734-cadastro-nacional-de-enderecos-para-fins-estatisticos.html?=&t=publicacoes.
IPCC (Ed.). (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press.
Jr., H. J. K., & Diamond, S. B. a. L. (2012). Multi-Hazard Early Warning System of the United States National Weather Service. In M. Golnaraghi (Ed.), Institutional partnerships in multi-hazard early warning systems: a compilation of seven national good practices and guiding principles (pp. 115-). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-25373-7_4.
King, D. (2001). Uses and Limitations of Socioeconomic Indicators of Community Vulnerability to Natural Hazards: Data and Disasters in Northern Australia. Natural Hazards, 24, 147-156.
King, D., & MacGregor, C. (2000). Using social indicators to measure community vulnerability to natural hazards [Article]. Australian Journal of Emergency Management, 15(3), 52-57.
Klose, M. (2015). Landslide Databases as Tools for Integrated Assessment of Landslide Risk.
Lacerda, W. A., Netto, A. L. C., & Sato, A. M. (2017). Technical report on landslide related disasters in Brazil In K. Ho, S. Lacasse, & L. Picarelli (Eds.), Slope safety preparedness for impact of climate change (pp. 45-70). CRC Press.
Leichenko, R., McDermott, M., & Bezborodko, E. (2015). Barriers, Limits and Limitations to Resilience. Journal of Extreme Events, 02(01). https://doi.org/10.1142/s2345737615500025.
Mason, K., Lindberg, K., Haenfling, C., Schori, A., Marsters, H., Read, D., & Borman, B. (2021). Social Vulnerability Indicators for Flooding in Aotearoa New Zealand. Int J Environ Res Public Health, 18(8). https://doi.org/10.3390/ijerph18083952.
MCid, & IPT. (2004). Treinamento de técnicos municipais para o mapeamento e gerenciamento de áreas urbanas com risco de escorregamentos, enchentes e inundações [Apostila de treinamento]. Ministério das Cidades - MCid; Instituto de Pesquisas Tecnológicas do Estado de São Paulo -IPT.
MCid, & IPT. (2007). Mapeamento de riscos em encostas e margens de rios. Brasília: Ministério das Cidades - MCid; Instituto de Pesquisas Tecnológicas -IPT.
Mendonca, M. B. d., & Silva, D. R. d. (2020). Integration of census data based vulnerability in landslide risk mapping - The case of Angra dos Reis, Rio de Janeiro, Brazil. International Journal of Disaster Risk Reduction, 50. https://doi.org/10.1016/j.ijdrr.2020.101884
MUNDIAL, B. (2012). Avaliacao de perdas e danos: inundacoes e deslizamentos na Regiao Serrana do Rio de Janeiro - janeiro de 2011. Brasília-DF: Relatório elaborado pelo Banco Mundial com apoio do Governo do Estado do Rio de Janeiro.
Navarro, D., Cantergiani, C., Abajo, B., Gomez de Salazar, I., & Feliu, E. (2023). Territorial vulnerability to natural hazards in Europe: a composite indicator analysis and relation to economic impacts. Natural Hazards. https://doi.org/10.1007/s11069-023-06165-w.
Neto, A. T., & Medeiros, L. C. (2022). Índice da vulnerabilidade social urbana em goiás: a geografia dos riscos e da desigualdade social. Revista Brasileira de Geografia, 67(2), 3-32.
O'Brien, K., Eriksen, S., Nygaard, L. P., & Schjolden, A. N. E. (2007). Why different interpretations of vulnerability matter in climate change discourses. Climate Policy, 7(1), 73-88. https://doi.org/10.1080/14693062.2007.9685639.
O'Keefe, P., Westgate, K., & Wisner, B. (1976). Taking the naturalness out of natural disasters [Article]. Nature, 260, 566-567. https://doi.org/10.1038/260566a0.
Papathoma-Kohle, M., Schlogl, M., & Fuchs, S. (2019). Vulnerability indicators for natural hazards: an innovative selection and weighting approach. Sci Rep, 9(1), 15026. https://doi.org/10.1038/s41598-019-50257-2
Ramli, M. W. A., Alias, N. E., Yusop, Z., & Taib, S. M. (2020). Disaster Risk Index: A Review of Local Scale Concept and Methodologies. IOP Conference Series: Earth and Environmental Science.
Roncancio, D. J., & Nardocci, A. C. (2016). Social vulnerability to natural hazards in São Paulo, Brazil [Article]. Natural Hazards, 84(2), 1367-1383. https://doi.org/10.1007/s11069-016-2491-x.
Roque, M. P. B., Ferreira Neto, J. A., da Cruz Vieira, W., Rocha, B. D., & Calegario, A. T. (2023). Social vulnerability to environmental disasters in the Paraopeba River Basin, Minas Gerais, Brazil. Natural Hazards. https://doi.org/10.1007/s11069-023-06042-6.
Saito, S. M., Assis Dias, M. C. d., Ribeiro, D. F., Alvalá, R. C. d. S., Souza, D. B. d., Santana, R. A. S. d. M., Souza, P. A. d., Ribeiro, J. V. M., & Stenner, C. (2021). Disaster risk areas in Brazil: outcomes from an intra-urban scale analysis. International Journal of Disaster Resilience in the Built Environment, 12(2), 238-250. https://doi.org/10.1108/IJDRBE-01-2020-0008.
Saito, S. M., Dias, M. C. d. A., Alvalá, R. C. d. S., Stenner, C., Franco, C., Ribeiro, J. V. M., Souza, P. A. d., & Santana, R. A. S. d. M. (2019). População urbana exposta aos riscos de deslizamentos, inundações e enxurradas no Brasil. Sociedade & Natureza, 31. https://doi.org/10.14393/SN-v31-2019-46320.
Salvati, P., Ardizzone, F., Cardinali, M., Fiorucci, F., Fugnoli, F., Guzzetti, F., Marchesini, I., Rinaldi, G., Rossi, M., Santangelo, M., & Vujica, I. (2021). Acquiring vulnerability indicators to geo-hydrological hazards: An example of mobile phone-based data collection. International Journal of Disaster Risk Reduction, 55. https://doi.org/10.1016/j.ijdrr.2021.102087.
Sarkar, R., Shaw, R., & Pradhan, B. (Eds.). (2022). Impact of climate change, land use and land cover, and socio-economic dynamics on landslides. Springer. https://doi.org/https://doi.org/10.1007/978-981-16-7314-6.
Schneiderbauer, S., Calliari, E., & Hagenlocher, U. E. M. (2017). The most recent view of vulnerability. In K. Poljansek, M. Marin Ferrer, T. De Groeve, & I. R. Clark (Eds.), Science for disaster risk management 2017: knowing better and losing lessScience for disaster risk management (pp. 70-130). (UNU-EHS Book) European Union.
Souza, D. B. d., Souza, P. A. d., Ribeiro, J. V. M., Santana, R. A. S. d. M., Dias, M. C. d. A., Saito, S. M., & Alvalá, R. C. d. S. (2019). Utilização de dados censitário para a análise de população em áreas de risco. R. Bras. Geogr., 64(1), 122-135.
UNISDR. (2004). Living with risk. a global review of disaster reduction initiatives. Genova: UN Publications.
UNISDR. (2009). 2009 UNIDR on Terminology on Disaster Risk Reduction. United Nations International Strategy for Disaster Reduction.
UNISDR. (2015). Sendai Framework for Disaster Risk Reduction 2015-2030. U.N.O.f.D.R. Reduction. https://www.unisdr.org/files/43291_sendaiframeworkfordrren.pdf.
UNISDR. (2017). National disaster risk assessment: governance system, methodologies, and use of sesults. United Nation Office for Disaster Risk Reduction (UNISDR).
Wilches-Chaux, G. (1993). La vulnerabilidad global. In A. Maskrey (Ed.), Los desastres no son naturales (pp. 11-44). Red de Estudios Sociales en Prevención de Desastres en América Latina - LARED.
Wisner, B., Blaikie, P., Cannon, T., & Davis, I. (2003). At risk: natural hazards, people's vulnerability and disasters (2ª ed.). Routledge.
Wisner, B., & College, O. (2016). Vulnerability as concept, model, metric, and tool. In Oxford Research Encyclopedia of Natural Hazard Science. https://doi.org/10.1093/acrefore/9780199389407.013.25.
WMO. (2015, Published: 23 March 2015). Global Climate in 2014 marked by extreme heat and flooding. https://public.wmo.int/en/media/press-release/global-climate-2014-marked-extreme-heat-and-flooding.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 João Paulo de Carvalho Araújo; Felipe Leitão
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
