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		<secondarykey>INPE-12583-PRE/7876</secondarykey>
		<isbn>85-17-00018-8</isbn>
		<citationkey>RizziRudo:2005:EsCaRi</citationkey>
		<title>Estimativa da produtividade de soja por meio de um modelo agrometeorológico-espectral: estudo de caso no Rio Grande do Sul</title>
		<format>CD-ROM, On-line.</format>
		<year>2005</year>
		<secondarytype>PRE CN</secondarytype>
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		<author>Rizzi, Rodrigo,</author>
		<author>Rudorff, Bernardo Friedrich Theodor,</author>
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		<group>DSR-INPE-MCT-BR</group>
		<group>DSR-INPE-MCT-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>rizzi@dsr.inpe.br</electronicmailaddress>
		<electronicmailaddress>bernardo@dsr.inpe.br</electronicmailaddress>
		<editor>Epiphanio, José Carlos Neves,</editor>
		<editor>Fonseca, Leila Maria Garcia,</editor>
		<e-mailaddress>rizzi@dsr.inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 12 (SBSR)</conferencename>
		<conferencelocation>Goiânia</conferencelocation>
		<date>16-21 abr. 2005</date>
		<publisher>INPE</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>237-244</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Artigos</tertiarytype>
		<organization>Instituto Nacional de Pesquisas Espaciais</organization>
		<transferableflag>1</transferableflag>
		<keywords>Grain yield estimate, soybean, remote sensing, MODIS, NDVI, estimativa de produtividade, soja, sensoriamento remoto.</keywords>
		<abstract>An agrometeorological crop yield model, integrated in a Geographic Information System, was used to estimate soybean grain yield in Rio Grande do Sul State, Brazil, for the crop year of 2000/01.  Two approaches were used for the model: a) agrometeorological (A) model with leaf area index (LAI) estimated from fixed literature values for each growth stage and; b) agrometeorological-spectral (A-E) model with LAI estimated from biweekly MODIS/NDVI images. Both models provided similar results in terms of the State mean crop yield and also compared well with the official statistic from the Brazilian Institute of Geography and Statistics (IBGE). However, the A-E model provided much better local estimates due to the high spatial resolution of LAI data estimated from MODIS/NDVI images.</abstract>
		<area>SRE</area>
		<type>Agricultura</type>
		<language>Português</language>
		<targetfile>237.pdf</targetfile>
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