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		<isbn>978-85-17-00066-9 (Internet)</isbn>
		<isbn>978-85-17-00065-2 (DVD)</isbn>
		<label>720</label>
		<citationkey>RochaPerz:2013:CoAsTh</citationkey>
		<title>Variation in deforestation estimates: a comparative assessment of three remote sensing protocols for the case of Acre, Brazil</title>
		<format>DVD, Internet.</format>
		<year>2013</year>
		<secondarytype>PRE CN</secondarytype>
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		<size>298 KiB</size>
		<author>Rocha, Karla da Silva,</author>
		<author>Perz, Stephen George,</author>
		<electronicmailaddress>rocha@ufl.edu</electronicmailaddress>
		<editor>Epiphanio, José Carlos Neves,</editor>
		<editor>Galvão, Lênio Soares,</editor>
		<e-mailaddress>wanderf@dsr.inpe.br</e-mailaddress>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 16 (SBSR)</conferencename>
		<conferencelocation>Foz do Iguaçu</conferencelocation>
		<date>13-18 abr. 2013</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>8184-8191</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>Many deforestation estimates have been derived from the Landsat platform in the past 30 years. More recently, estimates have also been produced from other orbital platforms, or using distinct methods of image processing and classification. As a result, there is often a diversity of estimates of LULCC available for high-profile study regions. Deforestation is increasingly seen as a metric for evaluating the effectiveness of environmental policies, and different estimates can be politicized by groups with interest in higher or lower estimates. Further, clean development mechanisms involving forest conservation have advanced toward implementation but require accurate estimates of forest cover with which to determine environmental service payments. Such issues are at play in many regions, notably the Brazilian Legal Amazon (BLA), where deforestation has proceeded rapidly, resulting in biodiversity loss and carbon emissions. This paper therefore compares deforestation estimates in the Amazon using data from multiple remote sensing studies. The main goal is to evaluate specific steps in remote sensing methodology to identify factors that account for differences in the resulting deforestation estimates. The comparison focuses on deforestation estimates from three different sources. The analysis shows differences in deforestation estimates; while there are many possible sources of such differences, in this analysis estimates vary primarily due to definitions of land cover classes.</abstract>
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		<type>Processamento de Imagens</type>
		<language>en</language>
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