@article{ref1,
title="Estimation of exposed population to landslides and floods risk areas in Brazil, on an intra-urban scale",
journal="International journal of disaster risk reduction",
year="2018",
author="Assis Dias, Mariane Carvalho de and Saito, Silvia Midori and Alvalá, Regina Célia dos Santos and Stenner, Cláudio and Pinho, Gustavo and Nobre, Carlos Afonso and Fonseca, Maria Rita de Souza and Santos, Camilla and Amadeu, Pilar and Silva, Dennis and Lima, Cibele Oliveira and Ribeiro, Julia and Nascimento, Frederico and Corrêa, Clarissa de Oliveira",
volume="31",
number="",
pages="449-459",
abstract="The knowledge on population demographics and the living conditions in risk areas are crucial for risk management and disaster response. In Brazil, this information is not available yet on a national scale. With the goal of characterizing at risk populations, in the present article a methodology is proposed to associate demographic census data with risk areas for landslides and floods in Brazil. The unique source of information about the Brazilian population, available for the entire country, in intra-urban scale, is provided by the Population Census developed by the Brazilian Institute of Geography and Statistics. However, the association of census information with risk areas cannot be done in a direct and automated way, due to the different geometries between the risk areas and census tracts. Considering the need to associate data from distinct geometries, a new basemap was created, named Statistical Territorial Base of Risk. Its graphical delimitations incorporate information from the population census about the mapped risk areas. The proposed methodology was initially implemented in three pilot municipalities located in the state of Rio de Janeiro (Petrópolis, Teresópolis and Nova Friburgo). The results show the estimation of approximately 155.000 people exposed to the risk of landslides and/or floods in 1.357 risk areas. It also allowed for the identification of regions within those municipalities with the highest concentration of at-risk population. The availability of information on the conditions of exposure of populations residing in risk areas can subsides decision makers in the context of disaster risk management.<p /> <p>Language: en</p>",
language="en",
issn="2212-4209",
doi="10.1016/j.ijdrr.2018.06.002",
url="http://dx.doi.org/10.1016/j.ijdrr.2018.06.002"
}