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		<identifier>8JMKD3MGP6W34M/3TUPK42</identifier>
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		<isbn>978-85-17-00097-3</isbn>
		<citationkey>PletshPeSiKöArAnMo:2019:CoSpIn</citationkey>
		<title>Combination of spectral indices for burned area detection in the brazilian amazonia</title>
		<format>Internet</format>
		<year>2019</year>
		<secondarytype>PRE CN</secondarytype>
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		<size>675 KiB</size>
		<author>Pletsh, Mikhaela Aloísia Jéssie Santos,</author>
		<author>Penha, Thales Vaz,</author>
		<author>Silva Júnior, Celso Henrique Leite,</author>
		<author>Körting, Thales Sehn,</author>
		<author>Aragão, Luiz Eduardo Oliveira e Cruz de,</author>
		<author>Anderson, Liana Oighenstein,</author>
		<author>Morelli, Fabiano,</author>
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		<group>DIDPI-CGOBT-INPE-MCTIC-GOV-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>mikhaela.pletsch@inpe.br</electronicmailaddress>
		<electronicmailaddress>thales.penha@inpe.br</electronicmailaddress>
		<electronicmailaddress>celso.junior@inpe.br</electronicmailaddress>
		<electronicmailaddress>thales.korting@inpe.br</electronicmailaddress>
		<electronicmailaddress>luiz.aragao@inpe.br</electronicmailaddress>
		<electronicmailaddress>liana.anderson@cemaden.gov.br</electronicmailaddress>
		<electronicmailaddress>fabiano.morelli@inpe.br</electronicmailaddress>
		<editor>Gherardi, Douglas Francisco Marcolino,</editor>
		<editor>Sanches, Ieda DelArco,</editor>
		<editor>Aragão, Luiz Eduardo Oliveira e Cruz de,</editor>
		<conferencename>Simpósio Brasileiro de Sensoriamento Remoto, 19 (SBSR)</conferencename>
		<conferencelocation>Santos</conferencelocation>
		<date>14-17 abril 2019</date>
		<publisher>Instituto Nacional de Pesquisas Espaciais (INPE)</publisher>
		<publisheraddress>São José dos Campos</publisheraddress>
		<pages>1248-1251</pages>
		<booktitle>Anais</booktitle>
		<tertiarytype>full paper</tertiarytype>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<keywords>Rainforest, Landsat-8, Spectral Index, Forest Fires, Burnt Area.</keywords>
		<abstract>Spectral Indices (SI) are widely used for remote sensing application because they enhance targeted features in optical images through the algebraic combination of spectral bands. There is a large variety of SI, in which the performance varies depending on the user's application. Considering the different emphases that spectral indices may offer, here we present a test-case based on the combination of 10 SI in a three channels remote sensing image (Red; Green; Blue - RGB) aiming to highlight burned areas from other targets such as vegetation and water. This process generated 120 possible combinations without repetition. With spatial resolution of 30m, the proposed method was able to achieve an accuracy between 0,21 and 0.86, according to Cohen's Kappa coefficient. The two groups of indices MIRBI, NBR2, EVI, MNDWI and CSI; and BAI, NBR and NDVI were the most inaccurate and accurate indices, respectively, identified for the study site.</abstract>
		<area>SRE</area>
		<type>Classificação e mineração de dados</type>
		<language>pt</language>
		<targetfile>97276.pdf</targetfile>
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