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Geospatial analysis and modeling of flood risk areas in the São Paulo City

Grant number: 14/21948-5
Support type:Scholarships in Brazil - Master
Effective date (Start): January 01, 2015
Effective date (End): November 30, 2016
Field of knowledge:Physical Sciences and Mathematics - Geosciences - Physical Geography
Cooperation agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
Principal Investigator:Marcos César Ferreira
Grantee:Talytha Accioly Simões Coelho
Home Institution: Instituto de Geociências (IG). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

The development and growth of the urban area in recent centuries have resulted in increased competition for space. In response to this disorderly occupation, natural events are occurring, mainly by change in the infiltration and flow balance, as well in the original characteristics of urban drainage channels. One of the main phenomena that affect cities are those related to the water issue, like floods, inundation and waterlogging. These natural events reach great number of peoples, causing material and immaterial damage. Brazil is one of the most affected countries by floods. This phenomena result in thousands of natural disasters victims. There is lack of studies and policies applied to the disaster prevention in Sao Paulo - which is reached by large floods along major urban rivers floodplains. Then, we argued that is very important to improve strategies for mapping and spatial analysis of geographical data applied to reducing damage and deaths caused by these hydrological phenomena in the urban areas. The research will be based on flooding points recorded in São Paulo using Crowdmap program (Poli/USP) and the CGE database. These flooding points will be used to define higher dot density areas (HDDA), estimate by kernel density algorithm. High intensity rainfall will be calculated for HDDA using gauges with more than 30 years time series. After, a land use-land cover map of HDDA surrounding areas obtained upon RapidEye image data, and 2010 IBGE census data, will be integrated to characterizing the socio-economical profile of the population living in the HDDA. (AU)

Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)

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