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		<isbn>978-85-17-00088-1</isbn>
		<label>59896</label>
		<citationkey>OroAraJúnVelSil:2017:FeAvPo</citationkey>
		<title>Espectrorradiometria: Uma ferramenta para avaliação do potencial produtivo das pastagens tropicais</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>877 KiB</size>
		<author>Oro, Oscar Ivan De,</author>
		<author>Araújo, Fernando Moreira,</author>
		<author>Júnior, Laerte Guimarães Ferreira,</author>
		<author>Veloso, Gabriel Alves,</author>
		<author>Silva, Janete Rêgo,</author>
		<electronicmailaddress>geoscar1988@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>3994-4001</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>In Brazil, there are more than 100 million hectare, between central and Legal Amazonia, with pasture degradation, these causing significant economic and environmental damage for the country. Technological advances such as remote sensing can monitor the dynamic of grassland, but do not determine the quality of pastures, because there are intrinsic variables, such as pasture management that influence the quality of the data. The objective of this paper was to evaluate the use of spectroradiometry as a tool to evaluate the productive potential of tropical pastures in the micro region of São Miguel do Araguaia - Goiás. The methodology was divide an assessment of grazing management and pasture quality by vegetation index obtained with a spectroradiometer. The results demonstrated that the farms visited determined three categories of grazing management, reasonable, great and bad; the analysis of the quality of pastures were characterized three types of high vegetative vigor qualities, agronomic degradation and biological degradation, where the NDVI (p <0.05) could discriminate roofing Brizantha H (2, N = 182) = 31.993 p <0.001 compared to SAVI and EVI. Pastures with great and reasonable management is most likely to have the same spectral behavior than bad. The use of spectroradiometer allows differentiate these coverages in both types of grass.</abstract>
		<area>SRE</area>
		<type>Radiometria e sensores</type>
		<language>pt</language>
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