1. Identity statement | |
Reference Type | Journal Article |
Site | plutao.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identifier | J8LNKAN8RW/38JED83 |
Repository | dpi.inpe.br/plutao/2010/11.11.17.29.25 |
Last Update | 2011:02.04.13.21.19 (UTC) administrator |
Metadata Repository | dpi.inpe.br/plutao/2010/11.11.17.29.26 |
Metadata Last Update | 2018:06.05.00.12.21 (UTC) administrator |
Secondary Key | INPE--PRE/ |
ISSN | 0560-4613 1808-0936 |
Label | lattes: 4872965504009836 1 MelloRudoVieiAgui:2010:ClAuCo |
Citation Key | MelloRudoVieiAgui:2010:ClAuCo |
Title | Classificação automática da colheita da cana-de-açúcar utilizando Modelo Linear de Mistura Espectral/Automatic Classification of Sugarcane Harvest Using Spectral Linear Mixing Model |
Year | 2010 |
Access Date | 2024, May 19 |
Secondary Type | PRE PN |
Number of Files | 1 |
Size | 389 KiB |
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2. Context | |
Author | 1 Mello, Márcio Pupin de 2 Rudorff, Bernardo Friedrich Theodor 3 Vieira, Carlos Antonio Oliveira 4 Aguiar, Daniel Alves de |
Resume Identifier | 1 2 8JMKD3MGP5W/3C9JGKP |
Group | 1 2 DSR-OBT-INPE-MCT-BR |
Affiliation | 1 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 2Universidade Federal de Viçosa – UFV Departamento de Engenharia Civil - DEC |
Author e-Mail Address | 1 mello@dsr.inpe.br 2 bernardo@ltid.inpe.br |
e-Mail Address | mello@dsr.inpe.br |
Journal | Revista Brasileira de Cartografia |
Volume | 62 |
Number | 2 |
Pages | 181-188 |
Secondary Mark | B5_CIÊNCIAS_AGRÁRIAS_I B5_CIÊNCIAS_BIOLÓGICAS_I B5_ECOLOGIA_E_MEIO_AMBIENTE B3_ENGENHARIAS_I B3_ENGENHARIAS_II B4_ENGENHARIAS_III B5_ENGENHARIAS_IV B2_GEOCIÊNCIAS B1_GEOGRAFIA B1_INTERDISCIPLINAR |
History (UTC) | 2010-12-06 14:15:20 :: lattes -> ricardo :: 2010 2010-12-07 11:40:33 :: ricardo -> administrator :: 2010 2010-12-08 15:13:05 :: administrator -> marciana :: 2010 2011-02-04 13:21:19 :: marciana -> administrator :: 2010 2018-06-05 00:12:21 :: administrator -> marciana :: 2010 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Keywords | sensoriamento remoto imagens multitemporais queima monitoramento Remote Sensing Multitemporal Images Burning Monitoring |
Abstract | Sugarcane is currently the best option to produce ethanol which can significantly contribute in the mitigation of the greenhouse effect intensification. However, the sugarcane straw burning prior to harvest is still a critical environmental problem that has to be eliminated. The S o Paulo State government together with the private sugarcane production sector established a protocol to gradually stop the sugarcane straw burning by 2014. Remote sensing images have a great potential to monitor the harvest management procedure with and without straw burning prior to harvest. Currently, this monitoring is carried out using visual interpretation which provides high quality results but is a quite tedious work. The present article has the objective to propose an automated classification procedure based on Spectral Linear Mixing Model technique to identify sugarcane fields that were harvested with and without burning. A visual interpreted reference map was used to assess the automated classification map accuracy which showed an overall index of 89.7%. The proposed methodology showed to be a promising alternative to automate the monitoring of sugarcane harvested with and without straw burning. ABSTRACT Sugarcane is currently the best option to produce ethanol which can significantly contribute in the mitigation of the greenhouse effect intensification. However, the sugarcane straw burning prior to harvest is still a critical environmental problem that has to be eliminated. The São Paulo State government together with the private sugarcane production sector established a protocol to gradually stop the sugarcane straw burning by 2014. Remote sensing images have a great potential to monitor the harvest management procedure with and without straw burning prior to harvest. Currently, this monitoring is carried out using visual interpretation which provides high quality results but is a quite tedious work. The present article has the objective to propose an automated classification procedure based on Spectral Linear Mixing Model technique to identify sugarcane fields that were harvested with and without burning. A visual interpreted reference map was used to assess the automated classification map accuracy which showed an overall index of 89.7%. The proposed methodology showed to be a promising alternative to automate the monitoring of sugarcane harvested with and without straw burning. |
Area | SRE |
Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Classificação automática da... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/J8LNKAN8RW/38JED83 |
zipped data URL | http://urlib.net/zip/J8LNKAN8RW/38JED83 |
Language | pt |
Target File | 62_02_7.pdf |
User Group | administrator lattes marciana |
Visibility | shown |
Archiving Policy | allowpublisher allowfinaldraft |
Read Permission | allow from all |
Update Permission | not transferred |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPCW/3ER446E |
Citing Item List | sid.inpe.br/mtc-m21/2012/07.13.14.41 1 |
URL (untrusted data) | http://www.rbc.ufrj.br/_2010/_RBC62_2.htm |
Dissemination | PORTALCAPES |
Host Collection | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
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6. Notes | |
Empty Fields | alternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel doi format isbn lineage mark mirrorrepository month nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate session shorttitle sponsor subject tertiarymark tertiarytype typeofwork versiontype |
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7. Description control | |
e-Mail (login) | marciana |
update | |
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