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Metadados

1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m16d.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP7W/395RSS8
Repositóriosid.inpe.br/mtc-m19/2011/02.08.11.07
Última Atualização2011:02.08.11.10.44 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m19/2011/02.08.11.07.44
Última Atualização dos Metadados2018:06.05.04.35.29 (UTC) administrator
Chave SecundáriaINPE--PRE/
ISSN1682-1777
Chave de CitaçãoFormaggioVieRenAguMel:2010:ObImAn
TítuloObject-based image analysis and data mining for mapping sugarcane with landsat imagery in brazil
FormatoOn-line
Ano2010
Data de Acesso30 abr. 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho443 KiB
2. Contextualização
Autor1 Formaggio, A. R.
2 Vieira, M. A.
3 Rennó, C. D.
4 Aguiar, D. A.
5 Mello, M. P.
Grupo1 DSR-OBT-INPE-MCT-BR
2
3 DPI-OBT-INPE-MCT-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2
3 Instituto Nacional de Pesquisas Espaciais (INPE)
EditorCoillie, E. A. Addink and F. M. B. Van
Nome do EventoGEOBIA 2010 Geographic Object-Based Image Analysis.
Localização do EventoGhent, Belgium
Data29 June - 2 July
Editora (Publisher)ISPRS Working Groups
Volume38-4/C7
Título do LivroProceedings
Histórico (UTC)2011-02-08 11:21:17 :: marciana -> administrator :: 2010
2018-06-05 04:35:29 :: administrator -> marciana :: 2010
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Palavras-ChaveSugarcane mapping
Artificial Intelligence
Object-based Image Analysis
Data Mining
Landsat images
ResumoMapping of sugarcane planted area is an important information for decision making, mainly when the search for alternatives to mitigate greenhouse gas emissions has indicated the use of biofuels as a viable option. Thus, the aim of this research was to develop a methodology in order to automate the sugarcane mapping task when remote sensing data are used. Thus the integration of two major approaches of Artificial Intelligence, Object-Based Image Analysis (OBIA) and Data Mining (DM), were tested in a study area located in São Paulo state, which is well representative of the agriculture of large regions of Brazil and other countries. OBIA was used to emulate the interpreter knowledge in the process of sugarcane mapping, and DM techniques were employed for automatic generation of knowledge model. A time series of four Landsat images was acquired in order to represent the wide variability of the patterns during sugarcane crop season. Definiens Developer® multiresolution segmentation algorithm produced the objects and properly trained decision tree applied to the Landsat data for the generation of the thematic map with sugarcane as the main class of interest. An overall accuracy of 94% (Kappa = 0,87) was obtained, showing that OBIA and DM are very efficient and promising in the direction of automating the sugarcane classification process with Landsat multitemporal time series.
ÁreaSRE
Arranjo 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Object-based image analysis...
Arranjo 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Object-based image analysis...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreement
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4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGP7W/395RSS8
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP7W/395RSS8
Idiomaen
Arquivo AlvoFormaggio_Full paper.pdf
Grupo de Usuáriosadministrator
marciana
Visibilidadeshown
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhosid.inpe.br/mtc-m19@80/2009/08.21.17.02.53
Unidades Imediatamente Superiores8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3ER446E
Lista de Itens Citandosid.inpe.br/bibdigital/2013/09.13.21.11 1
Acervo Hospedeirosid.inpe.br/mtc-m19@80/2009/08.21.17.02
6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition electronicmailaddress isbn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url versiontype
7. Controle da descrição
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