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		<secondarykey>INPE-12584-PRE/7877</secondarykey>
		<isbn>85-17-00018-8</isbn>
		<citationkey>RizziRudoAdam:2005:EsÁrPl</citationkey>
		<title>Estimativa de área plantada com soja no Rio Grande do Sul através de amostragem por segmentos quadrados</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>
		<author>Adami, Marcos,</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>
		<affiliation>Secretaria de Estado da Agricultura e do Abastecimento do Paraná - SEAB</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>245-252</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>Artigos</tertiarytype>
		<organization>Instituto Nacional de Pesquisas Espaciais</organization>
		<transferableflag>1</transferableflag>
		<keywords>sampling square method, crop area estimate, soybean, amostragem, estimativa de area plantada, soja.</keywords>
		<abstract>This paper evaluates a sampling square method to estimate soybean crop area in Rio Grande do Sul State, Brazil. A soybean thematic map obtained from multitemporal Landsat images classification was used as reference data. The State area was divided into cells of 1 x 1 km of size and stratified into three soybean area densities (0-20, 20-40 and >40%) at municipality level. A probabilistic technique was used to determine four sample rates representing 0.06, 0.12, 0.24 and 0.48% of the study area which were randomly sampled one hundred times. The soybean area for each sample was evaluated based on the reference data map. The one hundred estimates for each sample rate were then compared with the reference data for the entire study area.  Best results were obtained for the highest sample rate with low Coefficient of Variation (5.2), indicating that this method is not only suitable to accurate estimate soybean crop area at State level but it is also an appropriate alternative for early forecast or when cloud free images are not available.</abstract>
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		<type>Agricultura</type>
		<language>Português</language>
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