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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W/48743N2
Repositorysid.inpe.br/plutao/2022/12.12.17.51
Last Update2022:12.15.18.45.12 (UTC) lattes
Metadata Repositorysid.inpe.br/plutao/2022/12.12.17.51.01
Metadata Last Update2023:07.08.07.14.44 (UTC) administrator
DOI10.14210/cotb.v13.p029-036
Labellattes: 0096913881679975 4 HomemCoelhoOlivMoreSant:2022:MéClÁr
Citation KeyCoelhoBittMoreSant:2022:MéClÁr
TitleMétodo para a Classificação de Áreas Queimadas Baseado em Aprendizado de Máquina Automatizado
Year2022
Access Date2024, May 28
Secondary TypePRE CN
Number of Files1
Size487 KiB
2. Context
Author1 Coelho, Marcelly Homem
2 Bittencourt, Olga Oliveira
3 Morelli, Fabiano
4 Santos, Rafael Duarte Coelho dos
Resume Identifier1
2
3
4 8JMKD3MGP5W/3C9JJ4N
Group1 CAP-COMP-DIPGR-INPE-MCTI-GOV-BR
2 COPDT-CGIP-INPE-MCTI-GOV-BR
3 DIPE4-COGPI-INPE-MCTI-GOV-BR
4 COPDT-CGIP-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 marcellyhc@gmail.com
2 olgarf.oliveira@gmail.com
3 fabiano.morelli@inpe.br
4 rafael.santos@inpe.br
Conference NameComputer on the Beach
Conference LocationItajaí, SC
Date05-07 maio 2022
Pages029
Book TitleAnais
Tertiary TypeArtigo
History (UTC)2022-12-12 18:06:29 :: lattes -> administrator :: 2022
2022-12-13 15:14:44 :: administrator -> lattes :: 2022
2022-12-15 18:45:14 :: lattes -> administrator :: 2022
2023-07-08 07:14:44 :: administrator -> simone :: 2022
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsBurnt areas
Automated machine learning
Classification

Supervised learning
Remote sensing
AbstractForest fires burn large areas of native vegetation and it causes impacts in the social, economic and ecological scope. Burnt areas classification can help understand fires occurrence and support public policies. This work aims to develop a method of automatic burnt areas classification. The method is based on the application of Automated Machine Learning in data sets, from the Landsat8/OLI satellite images of 2018 and 2019. We intend to answer the following research question: Is it possible to automate the choice of machine learning models and maintain quality levels in the classification of burnt areas?. The contribution of this research is to determine whether a predictive model, trained with validated samples from 2018, is capable of classifying fires occurrences in 2019. For the performance evaluation, the following metrics were analyzed: precision, probability of detection and average success rate. The results indicate that the method has a high potential to classify burnt areas.
AreaCOMP
Arrangement 1urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CAP > Método para a...
Arrangement 2urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGIP > Método para a...
Arrangement 3urlib.net > BDMCI > Fonds > Produção a partir de 2021 > COGPI > Método para a...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://plutao.sid.inpe.br/ibi/8JMKD3MGP3W/48743N2
zipped data URLhttp://plutao.sid.inpe.br/zip/8JMKD3MGP3W/48743N2
Languagept
Target File029.pdf
Reader Groupadministrator
lattes
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3F2PHGS
8JMKD3MGPCW/46KUES5
8JMKD3MGPCW/46L2FGP
Citing Item Listsid.inpe.br/bibdigital/2022/04.03.23.11 21
sid.inpe.br/bibdigital/2013/10.12.22.16 4
sid.inpe.br/mtc-m21/2012/07.13.14.58.32 1
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notes
Empty Fieldsarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition editor format isbn issn lineage mark mirrorrepository nextedition notes numberofvolumes orcid organization parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark type url usergroup volume
7. Description control
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