1. Identity statement | |
Reference Type | Journal Article |
Site | plutao.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Identifier | 8JMKD3MGP3W/43NH2FE |
Repository | sid.inpe.br/plutao/2020/12.07.13.58.33 |
Last Update | 2020:12.08.21.13.59 (UTC) lattes |
Metadata Repository | sid.inpe.br/plutao/2020/12.07.13.58.34 |
Metadata Last Update | 2022:01.04.01.31.18 (UTC) administrator |
DOI | 10.14393/rbcv72n4-54044 |
ISSN | 0560-4613 1808-0936 |
Label | lattes: 1175464822052393 2 MoreiraReKöDuCaAr:2020:SuAnMO |
Citation Key | MoreiraReKöDuCaAr:2020:SuAnMO |
Title | Subpixel analysis of MODIS imagery time series using transfer learning and relative calibration |
Year | 2020 |
Access Date | 2024, May 18 |
Type of Work | journal article |
Secondary Type | PRE PN |
Number of Files | 1 |
Size | 1395 KiB |
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2. Context | |
Author | 1 Moreira, Noeli Aline Particcelli 2 Reis, Mariane Souza 3 Körting, Thales Sehn 4 Dutra, Luciano Vieira 5 Castejon, Emiliano Ferreira 6 Arai, Egídio |
Resume Identifier | 1 2 3 4 8JMKD3MGP5W/3C9JHMA 5 6 8JMKD3MGP5W/3C9JGUP |
ORCID | 1 0000-0002-5308-8080 2 0000-0001-9356-7652 3 0000-0002-0876-0501 4 0000-0002-7757-039X 5 0000-0002-4148-2830 6 0000-0003-1994-5277 |
Group | 1 DIDPI-CGOBT-INPE-MCTIC-GOV-BR 2 CST-CST-SESPG-INPE-MCTIC-GOV-BR 3 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 4 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 5 DIDSR-CGOBT-INPE-MCTIC-GOV-BR 6 DIDSR-CGOBT-INPE-MCTIC-GOV-BR |
Affiliation | 1 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 Address | 1 noeli.aline@inpe.br 2 mariane.reis@inpe.br 3 thales.korting@inpe.br 4 luciano.dutra@inpe.br 5 emiliano.castejon@inpe.br 6 egidio.arai@inpe.br |
Journal | Revista Brasileira de Cartografia |
Volume | 72 |
Number | 4 |
Pages | 558-573 |
Secondary Mark | A2_INTERDISCIPLINAR A2_GEOGRAFIA A2_ARQUITETURA_E_URBANISMO B1_PLANEJAMENTO_URBANO_E_REGIONAL_/_DEMOGRAFIA B1_CIÊNCIAS_AMBIENTAIS B2_GEOCIÊNCIAS B3_ENGENHARIAS_I B4_ENGENHARIAS_III B4_CIÊNCIAS_SOCIAIS_APLICADAS_I B5_ENGENHARIAS_IV B5_ENGENHARIAS_II B5_CIÊNCIAS_AGRÁRIAS_I B5_BIODIVERSIDADE C_ZOOTECNIA_/_RECURSOS_PESQUEIROS C_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA C_CIÊNCIAS_BIOLÓGICAS_I C_ASTRONOMIA_/_FÍSICA |
History (UTC) | 2020-12-07 15:16:48 :: lattes -> administrator :: 2020 2020-12-08 21:03:14 :: administrator -> lattes :: 2020 2020-12-08 21:14:00 :: lattes -> administrator :: 2020 2020-12-10 10:52:18 :: administrator -> lattes :: 2020 2020-12-14 14:08:48 :: lattes -> administrator :: 2020 2022-01-04 01:31:18 :: administrator -> simone :: 2020 |
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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 |
Version Type | publisher |
Keywords | Relative Calibration.Image Time-series.Samples Extension.Subpixel Analysis. Land Cover classification |
Abstract | Transfer learning reuses a pre-trained model on a new related problem, which can be useful for monitoring large areas such as the Amazon biome. A given object must havesimilar spectral characteristics in the data usedfor this type of analysis, which can be achieved usingrelative calibration techniques. In this article, we present a relative calibration process in multitemporal images and evaluate its impacts on a subpixel classification process. MODIS images from the Amazon region, collected between 2013and 2017, were relatively calibrated using a 2012 image as reference and classified by transfer learning. Classifications of calibrated and uncalibrated images were compared with data from the PRODES project, focusing on forest areas. A great variation was observed in the spectral responses of the forest class, even in images of proximatedates and fromthe same sensor. These variations significantly impacted the land cover classifications in the subpixel, with cases of agreement between the uncalibrated data maps and PRODES of 0%. For calibrated data, the agreement values were greater than 70%. The results indicate that the method used, although quite simple, is adequate and necessary for the subpixel classification of MODIS images by transfer learning. |
Area | SRE |
Arrangement 1 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Subpixel analysis of... |
Arrangement 2 | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Subpixel analysis of... |
Arrangement 3 | urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CST > Subpixel analysis of... |
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/8JMKD3MGP3W/43NH2FE |
zipped data URL | http://urlib.net/zip/8JMKD3MGP3W/43NH2FE |
Language | en |
Target File | moreira_subpixel.pdf |
Reader Group | administrator lattes |
Visibility | shown |
Archiving Policy | allowpublisher allowfinaldraft |
Update Permission | not transferred |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPCW/3EQCCU5 8JMKD3MGPCW/3ER446E 8JMKD3MGPCW/449U4PL |
Citing Item List | sid.inpe.br/bibdigital/2013/09.09.15.05 1 sid.inpe.br/bibdigital/2013/09.13.21.11 1 |
URL (untrusted data) | http://www.seer.ufu.br/index.php/revistabrasileiracartografia/article/view/54044 |
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 e-mailaddress format isbn lineage mark mirrorrepository month nextedition notes parameterlist parentrepositories previousedition previouslowerunit progress project readpermission rightsholder schedulinginformation secondarydate secondarykey session shorttitle sponsor subject tertiarymark tertiarytype usergroup |
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7. Description control | |
e-Mail (login) | simone |
update | |
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