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		<isbn>978-85-17-00088-1</isbn>
		<label>59514</label>
		<citationkey>SoaresSantBarrFran:2017:SPUtDa</citationkey>
		<title>Mapeamento da Suscetibilidade a movimentos de massa no Município de Santo André - SP utilizando dados geológicos e de Sensoriamento Remoto</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
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		<size>3030 KiB</size>
		<author>Soares, Adilson,</author>
		<author>Santana, Willian Reis de,</author>
		<author>Barradas, Thais Fernandes,</author>
		<author>Franchi, José Guilherme,</author>
		<electronicmailaddress>adilson.soares@me.com</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<e-mailaddress>daniela.seki@inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)</conferencename>
		<conferencelocation>Santos</conferencelocation>
		<date>28-31 maio 2017</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>6521-6528</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>This paper presents a methodology for susceptibility mapping of shallow landslides just from data and software from the public domain. The study was conducted in a mountainous region located on Santo André City, in the state of São Paulo. The susceptibility mapping was generated based on the following maps: geological, slope, vertical curvatures, lineament density and land use. The thematic classes of these maps were weighted according to technical and scientific criteria related to the triggering of landslides. A numerical rating scheme for the factors was developed for spatial data analysis in a GIS. The resulting landslide susceptibility map delineates the area into different zones of four relative susceptibility classes: very high, high, moderate and very low. The results show that some urban areas were built on high and very high risk areas. Slope and lithology are the factors that most influence susceptibility classes.</abstract>
		<area>SRE</area>
		<type>Geomorfologia</type>
		<language>pt</language>
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