%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.12.53.21
%2 sid.inpe.br/marte2/2017/10.27.12.53.22
%@isbn 978-85-17-00088-1
%F 59458
%T Desenvolvimento de metodologia para determinação de áreas topograficamente susceptíveis a inundação na área urbana do munícipio de Cascavel, PR
%D 2017
%A Mengue, Diego Hendler Scheffer,
%A Richetti, Jonathan,
%A Fernandes, Gustavo,
%A Piasecki, Allice,
%A Rufatto, Mariana Eveli,
%@electronicmailaddress diegohsmengue@gmail.com
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 2955-2959
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X The use of remote sensing in urban and rural mapping has shown great contribution to the society at preventing and studying several problems. Affecting a substantial amount of people every year, floods nowadays can be analyzed under the remote sensing optic. By combining the usage of satellite images, hydrological and topographical information into a GIS, it is possible to create a preventive study for an area. In that context, to indicate risk areas is a process that requires different information plans. This papers purpose is to develop a methodology capable of outlining the areas within a certain region (in this case, Cascavel, PR city) that have a bigger risk of flooding due to water proximity and topography. To define the methodology requires identifying the study area using Google Earth Pro, acquiring topographical information for that location - from the Shuttle Radar Topography Mission, for example - and then merging this information with the location of water bodies using the ArcGIS 10.3 software. ArcGIS 10.3 itself offers all the data management tools required to apply the method once acquired the information, which grants the methodology scalability. As for the results, applying said methodology to Cascavel, PR produces satisfying outcomes, as those matches the city historical inexistence of large floods.
%9 Classificação e mineração de dados
%@language pt
%3 59458.pdf