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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45E5QCE
Repositorysid.inpe.br/sibgrapi/2021/09.13.23.26
Last Update2021:09.13.23.26.52 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.13.23.26.52
Metadata Last Update2022:09.10.00.16.17 (UTC) administrator
Citation KeyDallaquaFariFaze:2021:CiScMa
TitleForestEyes Project - Citizen Science and Machine Learning to detect deforested areas in tropical forests
FormatOn-line
Year2021
Access Date2024, May 07
Number of Files1
Size700 KiB
2. Context
Author1 Dallaqua, Fernanda B. J. R.
2 Faria, Fabio A.
3 Fazenda, Álvaro L.
Affiliation1 Instituto de Ciência e Tecnologia - Universidade Federal de São Paulo
2 Instituto de Ciência e Tecnologia - Universidade Federal de São Paulo
3 Instituto de Ciência e Tecnologia - Universidade Federal de São Paulo
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressfernandab.dallaqua@gmail.com
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2021-09-13 23:26:52 :: fernandab.dallaqua@gmail.com -> administrator ::
2022-09-10 00:16:17 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordscitizen science
machine learning
tropical forests
deforestation
classification
AbstractThe conservation of tropical forests is urgent and necessary due to the important role they play in the global ecosystem. Several governmental and private initiatives were created to detect deforestation in tropical forests through analyses of remote sensing images, which demands skilled labor and different ways to deal with a great amount of data. Citizen Science could be used to mitigate these challenges, as it consists of non-specialized volunteers collecting, analyzing, and classifying data to solve technical and scientific problems. In this sense, this work proposes the ForestEyes Project, which aims to combine citizen science and machine learning for deforestation detection. The volunteers classify remote sensing images, and these data are used as the training set for classification algorithms. The volunteers classified more than $5,000$ tasks from remote sensing images of the Brazilian Legal Amazon, and the results were compared to a groundtruth from the Amazon Deforestation Monitoring Project PRODES. The volunteers achieved good labeling of the remote sensing data, even for recent deforestation tasks, building high-confidence labeled collections as they selected the most relevant samples and discarded noisy segments that might disrupt machine learning techniques. Finally, the proposed methodology is promising, and with improvements, it could be able to generate complementary information to official monitoring programs or even generate information for areas not yet monitored.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2021 > ForestEyes Project -...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45E5QCE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45E5QCE
Languageen
Target FileWTD_SIBGRAPI_19.pdf
User Groupfernandab.dallaqua@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 5
sid.inpe.br/banon/2001/03.30.15.38.24 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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