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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemarte.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier3ERPFQRTRW/3A68DMP
Repositorydpi.inpe.br/marte/2011/07.26.16.56
Last Update2011:07.26.16.56.03 (UTC) tereza@sid.inpe.br
Metadata Repositorydpi.inpe.br/marte/2011/07.26.16.56.03
Metadata Last Update2018:06.06.02.24.43 (UTC) administrator
ISBN978-85-17-00056-0 (Internet)
978-85-17-00057-7 (DVD)
Citation KeyAndradeVieiLaceDavi:2011:ReNeAr
TitleRedes Neurais Artificiais (RNA) aplicadas à classificação de áreas cafeeiras na região de Três Pontas-MG
FormatDVD, Internet.
Year2011
Access Date2025, May 09
Secondary TypePRE CN
Number of Files1
Size474 KiB
2. Context
Author1 Andrade, Lívia Naiara de
2 Vieira, Tatiana Grossi Chquiloff
3 Lacerda, Wilian Soares
4 Davis Junior, Clodoveu Augusto
Affiliation1 Universidade Federal de Minas Gerais – Departamento de Ciência da Computação
2 Empresa de Pesquisa Agropecuária de Minas Gerais - EPAMIG/CTSM
3 Universidade Federal de Lavras – Departamento de Ciência da Computação
4 Universidade Federal de Minas Gerais – Departamento de Ciência da Computação
Author e-Mail Address1 livia.naiara.andrade@gmail.com
2 tatiana@epamig.ufla.br
3 lacerda@dcc.ufla.br
4 clodoveu@dcc.ufmg.br
EditorEpiphanio, José Carlos Neves
Galvão, Lênio Soares
e-Mail Addressluana@dsr.inpe.br
Conference NameSimpósio Brasileiro de Sensoriamento Remoto, 15 (SBSR).
Conference LocationCuritiba
Date30 abr. - 5 maio 2011
PublisherInstituto Nacional de Pesquisas Espaciais (INPE)
Publisher CitySão José dos Campos
Pages7603-7610
Book TitleAnais
OrganizationInstituto Nacional de Pesquisas Espaciais (INPE)
History (UTC)2011-08-15 15:18:03 :: luana@dsr.inpe.br -> tereza@sid.inpe.br :: 2011
2011-08-19 18:15:27 :: tereza@sid.inpe.br -> administrator :: 2011
2018-06-06 02:24:43 :: administrator -> tereza@sid.inpe.br :: 2011
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordsremote sensing
artificial neural network
automatic classification
land use mapping
sensoriamento remoto
redes neurais artificiais
classificação automática
mapeamento
uso da terra
AbstractCoffee production is an activity of fundamental importance in the southern region of Minas Gerais state in Brazil and techniques for estimating the planted area, in order to establish reliable yield estimates, are being widely investigated. This study presents an application of Artificial Neural Networks (ANN) to automatically classify remote sensing data to identify coffee crops in Tres Pontas, South region of Minas Gerais. A complicating factor is the high similarity of the spectral patterns of coffee and areas of native forest. Masks were created to filter out drainage and urban areas. The result of the ANN classification was superior to the results found in the literature using automatic classifiers based on the multilayer perceptron model of artificial neural network . The kappa index of the map classified by ANN was 67.61%.
AreaSRE
TypeProcessamento de Imagens
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/3ERPFQRTRW/3A68DMP
zipped data URLhttp://urlib.net/zip/3ERPFQRTRW/3A68DMP
Languagept
Target Filep0606.pdf
User Groupluana@dsr.inpe.br
tereza@sid.inpe.br
Visibilityshown
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Host Collectiondpi.inpe.br/banon/2003/12.10.19.30
6. Notes
Empty Fieldsarchivingpolicy archivist callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition group issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype url versiontype volume
7. Description control
e-Mail (login)tereza@sid.inpe.br
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