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		<isbn>978-85-17-00088-1</isbn>
		<label>59611</label>
		<citationkey>CastroFidaPrad:2017:AnOrOb</citationkey>
		<title>Análise orientada a objetos aplicada a imagem de alta resolução para identificação de solo exposto em ambiente montanhoso de Mata Atlântica</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>1263 KiB</size>
		<author>Castro, Lívia Furriel de,</author>
		<author>Fidalgo, Elaine Cristina Cardoso,</author>
		<author>Prado, Rachel Bardy,</author>
		<electronicmailaddress>liviafurrielc@gmail.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>1518-1525</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>Since bared soil and lands with low production of biomass may be considered indicators of degraded areas, is important to develop methods to identify and classify bared soil using remote sensing. In this context, this study aimed to identify areas bared soil mountainous landscape of Atlantic Forest using Geographic Object-Based Image Analysis (Geobia) and its Principal Components applied to high resolution multispectral of images of the satellite World View-2. The classification method applied the third Principal Component, the Normalized Difference Vegetation Index (NDVI) and the image of the green spectral band. A visual evaluation of the classification results showed that the classification method was good to classify bared soil, which include dirt roads, land prepared for cultivation, and even degraded areas with low production of biomass, which is the study focus.</abstract>
		<area>SRE</area>
		<type>Processamento de imagens</type>
		<language>pt</language>
		<targetfile>59611.pdf</targetfile>
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