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		<isbn>978-85-17-00066-9 (Internet)</isbn>
		<isbn>978-85-17-00065-2 (DVD)</isbn>
		<label>436</label>
		<citationkey>Hartwig:2013:MaLiVa</citationkey>
		<title>Mapeamento litológico do Vale do Curaçá (BA) a partir da fusão de componentes principais de dados dos satélites ALOS-PALSAR e TM-Landsat</title>
		<format>DVD, Internet.</format>
		<year>2013</year>
		<secondarytype>PRE CN</secondarytype>
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		<size>525 KiB</size>
		<author>Hartwig, Marcos Eduardo,</author>
		<group>SER-SRE-SPG-INPE-MCTI-GOV-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>meh@dsr.inpe.br</electronicmailaddress>
		<editor>Epiphanio, José Carlos Neves,</editor>
		<editor>Galvão, Lênio Soares,</editor>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 16 (SBSR)</conferencename>
		<conferencelocation>Foz do Iguaçu</conferencelocation>
		<date>13-18 abr. 2013</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>3635-3642</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
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		<abstract>The purpose of this work was the lithological mapping of the Curaçá Valley, northern State of Bahia, using satellite data from ALOS-PALSAR (L-band and HH-HV polarization) and TM-Landsat. The processing chain was divided in four steps: (i) pre-processing; (ii) processing; (iii) RGB-IHS fusion; and (iv) MaxVer classification of hybrid image. The first step consisted of the coregistration of the reflected and radar images (coherence - &#61543; and amplitude - A). The second step consisted of the principal component transformation of the reflected and radar sets of images independently. The third step involved the composite of principal components of radar and reflected data using the RGB-IHS fusion method, in which the I channel (intensity) was replaced by PC1 obtained from the radar set of images. The fourth and last step corresponds to the MaxVer classification of the hybrid image. The results showed that the hybrid image represents an excellent product for photogeological mapping, allowing the individualization of the main lithological units. This result may be related, among other things, to the peculiar physiographic features of the study area, as scarce vegetation and shallow soil profile. On the other hand, the MaxVer classification from hybrid image showed a moderate result (kappa = 0,45), which allowed an incomplete discrimination of the lithological units, even considering a substantial number of homogeneously distributed training samples.</abstract>
		<area>SRE</area>
		<type>Geologia</type>
		<language>pt</language>
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