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		<isbn>978-85-17-00088-1</isbn>
		<label>60069</label>
		<citationkey>SouzaLoSoPaMoSaLo:2017:AvEsUm</citationkey>
		<title>Avaliação espectral da umidade da vegetação por meio do Normalized Difference Water Index - NDWI</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
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		<size>1104 KiB</size>
		<author>Souza, José Carlos,</author>
		<author>Lopes, Elfany Reis do Nascimento,</author>
		<author>Sousa, Jocy Ana Paixão de,</author>
		<author>Padovanni, Naia Godoy,</author>
		<author>Morais, Maria Cintia Matias,</author>
		<author>Sales, Jomil Costa,</author>
		<author>Lourenço, Roberto Wagner,</author>
		<electronicmailaddress>jcsouza1974@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>204-210</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>Among the numerous applications of remote sensing we have the estimate of vegetation index and the evaluation of the spectral behavior of vegetation cover, in relationship atmospheric conditions of time. The goal this study is to estimate quantitatively the moisture content of vegetation through in the NDWI (Normalized Difference Water Index) and evaluate the temporal changes of this index, pixel by pixel, considering periods of rain and drought. The study was applied in the watershed of the river Una, in the municipality of Ibiúna, São Paulo.  The NDWI was generated in the software ArcGis 10, using images of the sensor OLI/Landsat 8 of the months of January and August 2015. The index image generated was processed in the software Matlab 7.12 here was built a matrix, correlating the variations of the index, pixel by pixel, in both periods analyzed. The results showed direct influence of seasonality on the variation of index of moisture of the vegetation, showing loss in the water content of the vegetation in 73.03% of the pixels evaluated. The class of the NDWI that showed more marked change was the range 0.4 - 0.5 which ranged from 30.4%. Another evident factor is the influence of irrigated agriculture in the behavior of vegetation n January to 6.76% in August, where 5.92% of the pixels had higher NDWI values in the dry month.</abstract>
		<area>SRE</area>
		<type>Landsat OLI</type>
		<language>pt</language>
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