<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>marte2.sid.inpe.br 802</site>
		<holdercode>{isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S}</holdercode>
		<identifier>8JMKD3MGP6W34M/3PSMC4J</identifier>
		<repository>sid.inpe.br/marte2/2017/10.27.15.37.37</repository>
		<lastupdate>2017:10.27.15.37.37 dpi.inpe.br/marte2/2013/05.17.15.03.06 banon</lastupdate>
		<metadatarepository>sid.inpe.br/marte2/2017/10.27.15.37.38</metadatarepository>
		<metadatalastupdate>2018:06.06.03.10.47 dpi.inpe.br/marte2/2013/05.17.15.03.06 administrator {D 2017}</metadatalastupdate>
		<isbn>978-85-17-00088-1</isbn>
		<label>59657</label>
		<citationkey>PenachioOliTagBarZim:2017:ÍnVeOb</citationkey>
		<title>Índices de vegetação para obtenção de umidade do solo</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>994 KiB</size>
		<author>Penachio, Sara Maciel,</author>
		<author>Oliveira, Samuel Almeida Santos de,</author>
		<author>Tagliarini, Felipe de Souza Nogueira,</author>
		<author>Barros, Ana Clara de,</author>
		<author>Zimback, Célia Regina Lopes,</author>
		<electronicmailaddress>sarapenachio@hotmail.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>5991-5997</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>The remote sensing is a powerful tool in several environmental studies, and the use of satellites images is commonly used to acquire a plenty of climate data. The local of study is the experimental farm, Fazenda Lageado, located in Botucatu city, SP, Brazil, its area is in the vicinity of 940 ha. For scientific purposes it is important to relate field data to remote sensing data. Vegetation index and water index are a resultant of a raster calculation, in a geographic information system, from different bands of the satellite Sentinel-2A which bands are already corrected. The indices have the capability of measure the photosynthetic activity and the rate of fluid water in the vegetation, the present study has the achievement of finding a significant relation between the soil moisture, obtained as a volumetric proportion of water and water plus soil, at different depths and the index values, if the relation is meaning, then the remote sensing can be used as an indirect way of measurement for soil moisture. The statistical method was the linear regression with the software origin, the p value was the validating parameter used, which indicates the probability that the independent variable explaining the dependent variable has occurred by random effect. This study has showed no significant relation between any simple regression at a 5% of confidence interval, but at 10%  confidence the soil moisture at 60 cm explained the NDWI index.</abstract>
		<area>SRE</area>
		<type>Recursos hídricos</type>
		<language>pt</language>
		<targetfile>59657.pdf</targetfile>
		<usergroup>banon</usergroup>
		<visibility>shown</visibility>
		<mirrorrepository>urlib.net/www/2011/03.29.20.55</mirrorrepository>
		<nexthigherunit>8JMKD3MGP6W34M/3PMFNUS</nexthigherunit>
		<citingitemlist>sid.inpe.br/marte2/2017/09.25.14.55 3</citingitemlist>
		<hostcollection>dpi.inpe.br/marte2/2013/05.17.15.03.06</hostcollection>
		<username>banon</username>
		<lasthostcollection>dpi.inpe.br/marte2/2013/05.17.15.03.06</lasthostcollection>
		<url>http://marte2.sid.inpe.br/rep-/sid.inpe.br/marte2/2017/10.27.15.37.37</url>
	</metadata>
</metadatalist>