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		<isbn>978-85-17-00088-1</isbn>
		<label>59774</label>
		<citationkey>ViannaCarvSilvLemo:2017:VaSaND</citationkey>
		<title>Variação sazonal do NDVI das três fitofisionomias do município de Boa Nova ? Ba</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
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		<size>672 KiB</size>
		<author>Vianna, Luana Menezes,</author>
		<author>Carvalho, Rita de Cássia Freire,</author>
		<author>Silva, Mateus Tinôco,</author>
		<author>Lemos, Odair Lacerda,</author>
		<electronicmailaddress>lm.vianna@hotmail.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>6075-6080</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
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		<abstract>The main objective of this study was to assess the NDVIs seasonal variation that took place among the vegetation groups in the municipality of Boa Nova  BA, located in the southwest part of Bahia. Remote sensing is the practice of attaining land surfaces images with no contact between the detector and the object. NDVI is a remote sensing technique widely used in vegetation assessments, because its an index that emphasizes variations in land covers density. In this study the Normalized Difference Vegetation Index (NDVI) was calculated with Landsat 8 images in the dry season (06/16/2016) and the wet season (02/10/2016). The studied area is a transition zone between two biomes, Atlantic Forest and Caatinga and present three types of vegetation: caatinga, seasonal deciduous forest and ombrophilous dense forest. The images were processed in a GIS software (ArcGis 10.3). The results show that in the wet season, its not possible to distinguish the formations, and higher index were more common. In the dry season, it is possible to distinguish the different formations. In the ombrophilous dense forest, there were not big differences in the seasons, showing low correlation between NDVI and precipitation rates. In caatinga and seasonal deciduous forest seasonal, the low NDVI during the dry season was common in most areas this can be explained by the presence of deciduous vegetation and/or dry pasture.</abstract>
		<area>SRE</area>
		<type>Floresta e outros tipos de vegetação</type>
		<language>pt</language>
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