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		<isbn>978-85-17-00088-1</isbn>
		<label>59932</label>
		<citationkey>LeiteSantSilvRoch:2017:EsCaGe</citationkey>
		<title>Utilização dos índices espectrais NBR e NDVI na caracterização de incêndios no PARNA Chapada Diamantina (Bahia): Estudo de caso dos Gerais do Machobongo</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
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		<author>Leite, Cândida Caroline Souza de Santana,</author>
		<author>Santos, Sarah Moura Batista dos,</author>
		<author>Silva, Ardemírio de Barros,</author>
		<author>Rocha, Washington de Jesus Sant'Anna da Franca,</author>
		<electronicmailaddress>candidaleite.geo@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>2131-2137</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>The use of Remote Sensing techniques to suport the identification of burned areas can be useful to find the degree of severity and extention of the affected areas by fire. In order to identify burned areas the Normalized Burn Ratio (NBR) and the Normalized Difference Vegetation Index (NDVI) are used to classify satellite images from the sensor bands ratios. NBR identifies areas with dry vegetation from the OLI sensor reflectance bands 5 and 7, while NDVI analyzes the reflectance of healthy and non-healthy vegetation through bands 4 and 5 of the same sensor. In this sense, the calculations of the spectral indexes above mentioned were carried out in order to identify fire events in the National Park of Chapada Diamantina (PNCD), which is among the most burned Biodiversity Conservation Units in Brazil. As a case study, an area affected by fire in 2015 was selected in the Gerais do Machobongo hill. The applied methods allowed the identification of burned area, attesting the efficiency of both indexes used. Although NDVI was able to differentiate the clouds from the other targets in the image, for a better analysis, NBR was more effective, as it characterized the burned vegetation more prominently. A spectral profile traced across burn scar shows in detail the values of the indexes by image pixels making clear the best performing of NDBR in the study area.</abstract>
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		<language>pt</language>
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