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Socio Environmental Vulnerability and Geotechnologies as Contributions for Risks Cartography Maria Isabel Castreghini de Freitas UNESP IGCE, Centre of Analysis and Environmental Planning (CEAPLA) Rio Claro SP Brazil CEP 13506 900


  1. Socio ‐ Environmental Vulnerability and Geotechnologies as Contributions for Risks Cartography Maria Isabel Castreghini de Freitas UNESP ‐ IGCE, Centre of Analysis and Environmental Planning (CEAPLA) – Rio Claro – SP Brazil CEP 13506 ‐ 900 ifreitas@rc.unesp.br

  2. TOPICS 1. Aims 2.Concepts 3. Methodology 4. Results 5. Conclusions

  3. AIMS • to perform a review of the methodological procedures for the modeling of socio ‐ environmental vulnerability using geotechnologies • vulnerability is based on GIS and Statistics, using factor analysis and principal component analysis for aggregation of statistical socioeconomic and environmental variables derived from census. This study is the result of research developed in the Laboratory of Spatial Analysis Applied to Public Policies in the CEAPLA/UNESP and is part of the postdoctoral research in CEGOT, under the supervision of Professor Lúcio Cunha, from the University of Coimbra - Portugal.

  4. TOPICS 1. Aims 2.Concepts 3. Methodology 4. Results 5. Conclusions

  5. Vulnerability to Natural Risks • Dependence on Socio ‐ environmental Conditions and their differentiated impacts (Cutter, 2012) Earthquake in Haiti (2010) Earthquake in Chile (2010) Magnitude 7,0 (Richter scale) Magnitude 8,8 200.000 ‐ 250.000 deaths 500 deaths

  6. Vulnerabity • Emerges as “an idea subjacent to the notion of capacity of answer” of an environment or population to the risks (Marandola & Hogan 2004). • the characteristics of a person or group and their situation that influence their capacity to anticipate, cope with, resist and recover from the impact of a natural hazard (an extreme natural event or process) (Wisner et al. 2003). • social vulnerability to the natural and technologic risks incorporates to the standard exposition and biophysical vulnerability evaluations, the resilience and the infrastructural support capacities . (Mendes et al. (2009) and Cunha et al. (2011))

  7. VULNERABILITY MODELS AND RISKS CARTOGRAPHY • Support of Remote Sensing, GIS, GNSS, etc. • Combine natural hazards, exposition and vulnerability maps • Define risks zonning for specific areas • Contribute with the public authorities to designate investments in priority areas

  8. Criticality and Support Capacity Criticality Support Capacity • set of individual and • set of territorial behavioral characteristics infrastructures which which can contribute for the allow the community rupture of the System to react to a disaster

  9. TOPICS 1. Aims 2.Concepts 3. Methodology 4. Results 5. Conclusions

  10. Methodological Procedures • Based on methodologies developed and improved by CUTTER (1996, 2003); MENDES et al. (2009) e CUNHA et al. (2011) • Socio ‐ environmental Vulnerability (SEV) SEV = Criticality x Support Capacity • Factorial Analysis which aggregated social and environmental variables • Statistic program SPSS R.18 and GIS ArcGIS v.9.3 • Municipalities as analysis units

  11. STUDY AREA IN PORTUGAL STUDY AREA IN BRAZIL Legend Study Area Other Counties Legend Other Municipalities Escala 1:6.000.000 Study Area

  12. 2. DATA COLLECTION CENSUS DATA CARTOGRAPHY DATA – Brazil: 2000 a 2010 • Portugal and Brazil – Portugal: 2001 a 2011 Cartographic Intituitions: • Digital Database from Environmental Institute (PT), IBGE and SEADE Statistics Institutes: INE – Foundation (BR) Portugal and IBGE ‐ Brazil • Field Observations • Municipalities Webpages

  13. Factorial Analysis ‐ SPSS • Extraction Method: Principal Components Analysis • Rotation Method : Varimax with Kaiser Normalization • Statistics Validation tests: Kolmogorov ‐ Smirnov and Shapiro ‐ Wilk tests (5% significance) Maps Classification – GIS ArcGIS 9.3 • Natural Breaks and Manual Classifying

  14. Portugal Statistic Results Criticality Support Capacity Explanatory Variables 43 41 Factors 5 5 Cumulative Variance 76 73 (%) Brazil Statistic Results Criticality Support Capacity Explanatory Variables 18 17 Factors 5 5 Cumulative Variance 67 68 (%)

  15. TOPICS 1. Aims 2.Concepts 3. Methodology 4. Results 5. Conclusions

  16. Portugal

  17. Main Factors ‐ Portugal

  18. Criticality Suport Capacity Legend very low low moderate high very high

  19. SOCIO-ENVIRONMENTAL VULNERABILITY - Portugal SV = Criticality x Support Capacity 1.High or Very High Vulnerability North Sector: Montemor,  Soure, Mira e Penacova South Sector: Alcanena e  Porto de Mós.  Low economic development Limited Enviromental and  structural conditions in risk situations. 2. Low and Very Low Vulnerability  Coimbra e Leiria (major urban centres)  Centre and South of study area: Pombal, Marinha Grande, Loulé, Nazaré e Batalha.  Adequated infrastructure and good development

  20. Pombal Leiria Coimbra Batalha

  21. Nazaré Alcanena Montemor-o-Velho Figueira da Foz 12/06/2012

  22. Brazil

  23. Main Factors ‐ Brazil

  24. Criticality Suport Capacity Legend very low low moderate high very high

  25. SOCIO-ENVIRONMENTAL VULNERABILITY - Brazil 1. High or Very High Vulnerability: Municipalities in the interior of  the State of São Paulo: Ibiúna, Embu-Guaçu, Juquitiba, São Roque, Piedade e Salto de Pirapora; Low Socioeconomical  Development Limited Enviromental and  structural conditions in risk situations. 2. Low and Very Low Vulnerability : São Lourenço da Serra and  Municipalities in the coastal zone - Mongaguá, Itanhaém and Peruíbe; Sorocaba e Alumínio  Good socioeconomic status,  housing infrastructure and health.

  26. ITANHAEM Peruíbe SOROCABA - SP MONGAGUÁ

  27. VOTORANTIM - SP ALUMÍNIO - SP

  28. PIEDADE - SP Embu-Guaçu

  29. TOPICS 1. Aims 2.Concepts 3. Methodology 4. Results 5. Conclusions

  30. Conclusions: Vulnerabilities in Study Areas Portugal Brasil Economic Contraction Criminality Low Birth Rate High Birth Rate Rural Exodus Rural Exodus Forest Fire Poverty Aging buildings Precarious condition of housing

  31. CONCLUSIONS: APPLIED METHODOLOGY Accessibility and replicability of the methodology Results close to the geographic knowledge for most municipalities Summary vision of vulnerability Next step: risk mapping at regional and local scale Basis for preventive actions related to socio ‐ environmental vulnerabilities and risks

  32. REFERENCES Alves, H. P. F. A. (2006) Vulnerabilidade socioambiental na metrópole paulistana: uma análise sociodemográfica das situações de sobreposição espacial de problemas e riscos sociais e ambientais. Revista Brasileira de Estudos da População. 23(1):43 ‐ 59 Blaikie, P.; Cannon, T., Davis, I. Y Wisner, B. (1994) At risk: Natural hazards, peo ‐ ple’s vulnerability and disasters. Routledge, London Cunha, L.; Mendes, J.M.; Tavares, A.; Freiria, S. (2011) Construção de modelos de avaliação de vulnerabilidade social a riscos naturais e tecnológicos. O desafio das escalas. In: Santos, N.; Cunha, L. (org.) Trunfos de uma Geografia Activa. Imprensa da Universidade de Coimbra, Coimbra Cutter, S.L. (1996) Vulnerability to environmental hazards. Progress in Human Geography 20(4): 529 ‐ 539 Cutter, S.L. (2012) A Ciência da Vulnerabilidade: modelos, métodos e indicadores. Revista Crítica de Ciências Sociais. 93(1): 59 ‐ 70

  33. ifreitas@rc.unesp.br The author wishes to thank the São Paulo Research Foundation (FAPESP) aid granted to attend the event. Danke sehr! Thank you!

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