Close

1. Identity statement
Reference TypeSlides (Audiovisual Material)
Sitemtc-m21d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34T/454U5HB
Repositorysid.inpe.br/mtc-m21d/2021/07.19.13.09
Last Update2021:07.19.13.09.05 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21d/2021/07.19.13.09.05
Metadata Last Update2022:04.03.22.29.42 (UTC) administrator
Secondary KeyINPE--PRE/
ISBN978-1-61208-871-6
ISSN2308-393X
Citation KeyPachecoMaSiSoShEs:2021:ImClMe
TitleImage Classification Methods Assessment for Identification of Small-Scale Agriculture in Brazilian Amazon
Short TitleSlides
FormatOn-line
Year2021
Access Date2024, May 05
Secondary TypePRE CI
Number of Files1
Size2706 KiB
2. Context
Author1 Pacheco, Flávia Domingos
2 Matias, Maíra Ramalho
3 Silva, Gabriel Máximo da
4 Souza, Anielli Rosane de
5 Shimabukuro, Yosio Edemir
6 Escada, Maria Isabel Sobral
Resume Identifier1
2
3
4
5 8JMKD3MGP5W/3C9JJCQ
6 8JMKD3MGP5W/3C9JHRG
Group1 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
2 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
3 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
4 SER-SRE-DIPGR-INPE-MCTI-GOV-BR
5 DIOTG-CGCT-INPE-MCTI-GOV-BR
6 DIOTG-CGCT-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)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 flavia.pacheco@inpe.br
2 mairamatias.geo@gmail.com
3 gabrielmaximo04@gmail.com
4 aniellirosane@yahoo.com.br
5 edemirshima@gmail.com
6 isabel.escada@inpe.br
Conference NameInternational Conference on Advanced Geographic Information Systems, Applications, and Services, 13 (GEOProcessing)
Conference LocationNice, France
Date19-22 july
PublisherIARIA
Publisher CitySão José dos Campos
History (UTC)2021-07-19 13:09:05 :: simone -> administrator ::
2022-04-03 22:29:42 :: administrator -> simone :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordsdigital image processing
segmentation
land use
land cover
smallholders
planetscope
AbstractThis paper aims to test different methods for image classification focusing on small-scale agriculture in the region of Mocajuba and Cametá, municipalities in the Northeast of Pará state, Brazil. It is an important land use class, always ignored by Land-Use and Land-Cover monitoring systems because of its small size and variable spectral signature. We used an image from the PlanetScope Surface Reflectance Mosaics (Analysis Ready) with spatial resolution of 4.77 meters and 4 spectral bands (red, green, blue and infra-red). After proceeding with a multiresolution segmentation to identify image objects, two object-oriented classification algorithms were tested: Adapted Nearest-neighbor and C5.0 Decision trees algorithms. We selected 122 random points using the images available on Google Earth Pro as reference to assess the accuracy of classifications. Afterwards, confusion matrices were generated. Both methods showed similar overall accuracy and kappa value. However, C5.0 Decision trees reached a higher producers accuracy to small-scale agriculture (75%) in comparison to Adapted Nearest-neighbor (65%). The average size of the small-scale agriculture segments estimated was less than 1 ha in both maps, showing the need to carry out studies on scales of greater detail, preferably with images of high spatial resolution to represent these systems properly. In this study, C5.0 Decision trees had the best result, representing the most suitable method for mapping small-scale agriculture in Brazilian Amazon.
AreaSRE
Arrangement 1urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Image Classification Methods... > Slides
Arrangement 2urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Slides
Arrangement 3urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Slides
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 19/07/2021 10:09 1.8 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP3W34T/454U5HB
zipped data URLhttp://urlib.net/zip/8JMKD3MGP3W34T/454U5HB
Languageen
Target File30034_GEOProcessing2021.pdf
User Groupsimone
Visibilityshown
Read Permissionallow from all
5. Allied materials
Mirror Repositoryurlib.net/www/2021/06.04.03.40.25
Next Higher Units8JMKD3MGP3W34T/454U5F5
8JMKD3MGPCW/3F3NU5S
8JMKD3MGPCW/46KUATE
Citing Item Listsid.inpe.br/bibdigital/2022/04.03.22.23 1
Host Collectionurlib.net/www/2021/06.04.03.40
6. Notes
Empty Fieldsarchivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress label lineage mark nextedition notes numberofslides orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarymark session sponsor subject tertiarymark tertiarytype type url volume
7. Description control
e-Mail (login)simone
update 


Close