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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitemtc-m21d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34T/47TLSDH
Repositorysid.inpe.br/mtc-m21d/2022/11.03.12.34   (restricted access)
Last Update2022:11.03.12.34.27 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21d/2022/11.03.12.34.27
Metadata Last Update2023:01.03.16.46.22 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.1109/IGARSS46834.2022.9884210
ISBN978-166542792-0
Citation KeyShimabukuroArSiDuMaDuMa:2022:MaMoFo
TitleMapping and Monitoring Forest Plantation using Fraction Images Derived from Multi-Annual Landsat TM Datasets
FormatOn-line
Year2022
Access Date2024, May 18
Secondary TypePRE CI
Number of Files1
Size359 KiB
2. Context
Author1 Shimabukuro, Yosio Edemir
2 Arai, Egidio
3 Silva, Gabriel Máximo da
4 Dutra, Andeise Cerqueira
5 Mataveli, Guilherme Augusto Verola
6 Duarte, Valdete
7 Martini, Paulo Roberto
Resume Identifier1 8JMKD3MGP5W/3C9JJCQ
2 8JMKD3MGP5W/3C9JGUP
3
4
5
6 8JMKD3MGP5W/3C9JJAU
7 8JMKD3MGP5W/3C9JJ3M
Group1 DIOTG-CGCT-INPE-MCTI-GOV-BR
2 DIOTG-CGCT-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
7 SEREL-COGAB-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)
7 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 yosio.shimabukuro@inpe.br
2 egidio.arai@inpe.br
3 gabrielmaximo04@gmail.com
4 andeise.dutra@inpe.br
5 guilherme.mataveli@inpe.br
6 valdete.duarte@inpe.br
7 paulo.martini@inpe.br
Conference NameIEEE International Geoscience and Remote Sensing Symposium (IGARSS )
Conference LocationKuala Lampur
Date17-22 July 2022
PublisherIEEE
Pages5969-5972
Book TitleProceedings
History (UTC)2022-11-03 12:34:53 :: simone -> administrator :: 2022
2023-01-03 16:46:22 :: administrator -> simone :: 2022
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsEucalypt and Pine plantations
Fraction image
Image Processing
Linear Spectral Mixing Model
AbstractThis article presents a method to map the extent of forest plantation in an area located in the São Paulo State (Brazil). The proposed method applies the Linear Spectral Mixing Model (LSMM) to Landsat Thematic Mapper (TM) datasets to derive annually vegetation, soil and shade fraction images for local analysis. We used 30 m annual mosaics of TM images during the 1985 to 1995 time period. These fraction images have the advantage to reduce the volume of data to be analyzed highlighting the target characteristics. Then, we generated only one mosaic for each fraction images for TM dataset computing de maximum value through this period, facilitating the classification of areas occupied by forest plantation. The proposed method allowed to classify two forest plantation classes: Eucalypt and Pine. In addition, it allowed to monitor the phenological stages of Eucalypt according to its growth cycle. The results are very important for planning and management by the commercial companies and can contribute to develop an automatic method to map forest plantation areas in a regional and global scales.
AreaSRE
Arrangement 1urlib.net > Produção pgr ATUAIS > SER > Mapping and Monitoring...
Arrangement 2urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > Mapping and Monitoring...
Arrangement 3urlib.net > BDMCI > Fonds > Produção a partir de 2021 > COGAB > Mapping and Monitoring...
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4. Conditions of access and use
Languageen
Target FileMapping_and_Monitoring_Forest_Plantation_using_Fraction_Images_Derived_from_Multi-Annual_Landsat_TM_Datasets.pdf
User Groupsimone
Reader Groupadministrator
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Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3F3NU5S
8JMKD3MGPCW/46KUATE
8JMKD3MGPCW/46L2F3E
Citing Item Listsid.inpe.br/bibdigital/2022/04.03.22.23 5
sid.inpe.br/bibdigital/2013/10.18.22.34 1
sid.inpe.br/bibdigital/2022/04.04.04.41 1
Host Collectionurlib.net/www/2021/06.04.03.40
6. Notes
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