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		<identifier>8JMKD3MGP6W34M/3PSLQFC</identifier>
		<repository>sid.inpe.br/marte2/2017/10.27.12.40.13</repository>
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		<isbn>978-85-17-00088-1</isbn>
		<label>59258</label>
		<citationkey>MaldonadoSionTentAceñ:2017:SeAuÁr</citationkey>
		<title>Separación automática de áreas de bosque nativo por aproximación temática a través de la acumulación multitemporal de clases con Índice SAVI bajo</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>3252 KiB</size>
		<author>Maldonado, Francisco Dario,</author>
		<author>Sione, Walter Fabián,</author>
		<author>Tentor, Fernando Raul,</author>
		<author>Aceñolaza, Pablo Gilberto,</author>
		<electronicmailaddress>francisco.dario.maldonado@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>2370-2377</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>The objective of this work was develop an automatic system for discrimination of areas of native forest, agricultural and cattle use without forest. This objective is aimed at the automatic generation of forest mask for input data to an automatic system for change detection and monitoring of native forest, trough successive masking of annual masks of clear cuts. In this work was used a methodological approach based on the separately process of small spatial subsets (administrative districts), that can be processed by simple techniques increasing de accuracy with each methodological iteraction. The first simple technique was Kmean classification, the second is the SAVI vegetation index, and then, the apply of thematic label to the classes based on the average of SAVI values  for the pixels in class and accumulation of occurrences of SAVI low in a frequency map. As a result, the class zero frecuency was labeles as native forest for compose the Map of native forest and no forest. The results show two classes with low fragmentation, and the no forest class with well defined geometric forms. The forest class show little fragmentation, despite the frequency map was the result of  one serie of independent thematic transformations.</abstract>
		<area>SRE</area>
		<type>Mudança de uso e cobertura da terra</type>
		<language>es</language>
		<targetfile>59258.pdf</targetfile>
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		<url>http://marte2.sid.inpe.br/rep-/sid.inpe.br/marte2/2017/10.27.12.40.13</url>
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