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		<isbn>978-85-17-00088-1</isbn>
		<label>59993</label>
		<citationkey>MoraesDFQDSSML:2017:DeSeNu</citationkey>
		<title>Detecção semiautomática de nuvens e sombras nas imagens WFI/CBERS-4 utilizando a ferramenta cloud detection do sistema TerraAmazon</title>
		<format>Internet</format>
		<year>2017</year>
		<secondarytype>PRE CN</secondarytype>
		<numberoffiles>1</numberoffiles>
		<size>1057 KiB</size>
		<author>Moraes, Douglas Rafael Vidal de,</author>
		<author>Dias, Emily Regina Siqueira,</author>
		<author>Feitosa, Jeremias Vitório Pinto,</author>
		<author>Quadros, Camila Barata,</author>
		<author>Dias, Mírian Corrêa,</author>
		<author>Souza, Jefferson Jesus de,</author>
		<author>Santos, Laís Freitas Moreira dos,</author>
		<author>Miranda, Magda Valéria Corrêa,</author>
		<author>Luz, Nelton Cavalcante,</author>
		<author>Ronise,</author>
		<group></group>
		<group>CRCRA-COCRE-INPE-MCTIC-GOV-BR</group>
		<group>YYY-CRCRA-INPE-MCTIC-GOV-BR</group>
		<group>CRCRA-COCRE-INPE-MCTIC-GOV-BR</group>
		<affiliation></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>
		<electronicmailaddress>douglas.moraes@funcate.org.br</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>5009-5016</pages>
		<booktitle>Anais</booktitle>
		<organization>Instituto Nacional de Pesquisas Espaciais (INPE)</organization>
		<transferableflag>1</transferableflag>
		<abstract>The  Amazon  region,  by  its  geographical  location,  with  influences  of  the  Intertropical  Convergence Zone, offers to optical sensors, the obtainment of images with high cloud coverage in the greater part of the year, which makes difficult and/or prevents the orbital images interpretation and can become an obstacle for the remote sensing and geoprocessing in the forests monitoring. Keeping this in view, it was implemented a cloud automatic detection tool, the Cloud Detection, which is available in the application TerraAmazon, developed by INPE  and  FUNCATE  to  give  support  to  the  projects,  developed  by  the  National  Institute  for  Space  Research (INPE) for the monitoring of forests. The present work applied different values to the parameters referring to the plugin  Cloud  Detection  in  the  semiautomatic  detection  of  clouds  and  shadows  for  WFI/CBERS-4  images,  to  verify which parameters collaborate for the efficiency of the detection and vectorization of the two targets in question. The results showed that the values of the morphological filters opening was the one who collaborates more for the  differences  in  the  vectorization;  and  there  will  always  have  confusion  related  to  some  water  bodies  that, because of theirs similar reflectance, they are detected as shadows, which can be edited manually and deleted of the mapping.</abstract>
		<area>SRE</area>
		<type>CBERS</type>
		<language>pt</language>
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