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Estatística
Título: SOCIO-ENVIRONMENTAL RISK ANALYSIS IN THE CITY OF TERESÓPOLIS: A METHODOLOGICAL PROPOSAL
Autor: AMANDA SCOFANO DE ANDRADE SILVA
Colaborador(es): LUIZ FELIPE GUANAES REGO - Orientador
Catalogação: 11/JUN/2019 Língua(s): PORTUGUESE - BRAZIL
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=39028&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=39028&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.39028
Resumo:
Due to its natural and social characteristics, Brazil emerges as one of the countries most affected by extreme events. Faced with so many tragedies arising from the so-called natural disasters, it is necessary to re-dimension the importance of the discussion about socio-environmental risks. Preventing natural disasters is an efficient and cost-effective procedure compared to restoring the damages caused by these events. The tools contained in Geographic Information Systems (GIS) can effectively aid in risk prevention. The present research is a methodological proposal for the analysis of socioenvironmental risks, based on map algebra. The chosen scenario was the Rio de Janeiro municipality of Teresópolis, due to its geography and its history of extreme natural events. Three data fronts were used to calculate socioenvironmental risk: CPRM susceptibility charts, use mapping and INEA coverage; and IBGE census data. All the data were integrated and manipulated in a GIS environment, providing reliable results about the social-environmental risk level of the municipality. In this sense, the methodology of the present research allowed the manipulation of some dispersed data, correlating them in a GIS environment, and offering a new proposal in the treatment of socio-environmental risk.
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