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1. Identity statement
Reference TypeJournal Article
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
IdentifierJ8LNKAN8RW/3D53ESE
Repositorydpi.inpe.br/plutao/2012/11.28.15.38
Last Update2013:01.17.14.02.29 (UTC) marciana
Metadata Repositorydpi.inpe.br/plutao/2012/11.28.15.38.01
Metadata Last Update2022:04.11.18.00.43 (UTC) marciana
Secondary KeyINPE--PRE/
DOI10.3390/rs4092492
ISSN2072-4292
Labellattes: 8408207746528834 1 BernardesAdMoAdGiRu:2012:MoBiBe
Citation KeyBernardesMorAdaGiaRud:2012:MoBiBe
TitleMonitoring Biennial Bearing Effect on Coffee Yield Using MODIS Remote Sensing Imagery
Year2012
Access Date2023, Jan. 30
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size881 KiB
2. Context
Author1 Bernardes, Tiago
2 Moreira, Maurício Alves
3 Adami, Marcos
4 Giarolla, Angélica
5 Rudorff, Bernardo Friedrich Theodor
Resume Identifier1
2 8JMKD3MGP5W/3C9JHT4
3
4 8JMKD3MGP5W/3C9JGHP
5 8JMKD3MGP5W/3C9JGKP
Group1 DSR-OBT-INPE-MCTI-GOV-BR
2 DSR-OBT-INPE-MCTI-GOV-BR
3 DSR-OBT-INPE-MCTI-GOV-BR
4 DSR-OBT-INPE-MCTI-GOV-BR
5 DSR-OBT-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)
Author e-Mail Address1 tiago.bernardes@cemaden.gov.br 
2 mauricio@dsr.inpe.br
e-Mail Addresstiago.bernardes@cemaden.gov.br
JournalRemote Sensing
Volume4
Number9
Pages2492-2509
History (UTC)2012-11-28 23:06:26 :: lattes -> marciana :: 2012
2013-01-17 14:02:29 :: marciana -> administrator :: 2012
2016-06-04 01:08:12 :: administrator -> marciana :: 2012
2016-10-11 00:24:12 :: marciana -> administrator :: 2012
2018-06-05 00:02:03 :: administrator -> marciana :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsFoliar biomass
Growing season
High yield
Landsat images
Leaf biomass
Minas Gerais
Minimum value
Previous year
Pure pixel
Reference map
Remote sensing imagery
Vegetation index
Wavelet filtering
Pixels
Radiometers
Remote sensing
Vegetation
Satellite imagery
AbstractCoffee is the second most valuable traded commodity worldwide. Brazil is the worlds largest coffee producer, responsible for one third of the world production. A coffee plot exhibits high and low production in alternated years, a characteristic so called biennial yield. High yield is generally a result of suitable conditions of foliar biomass. Moreover, in high production years one plot tends to lose more leaves than it does in low production years. In both cases some correlation between coffee yield and leaf biomass can be deduced which can be monitored through time series of vegetation indices derived from satellite imagery. In Brazil, a comprehensive, spatially distributed study assessing this relationship has not yet been done. The objective of this study was to assess possible correlations between coffee yield and MODIS derived vegetation indices in the Brazilian largest coffee-exporting province. We assessed EVI and NDVI MODIS products over the period between 2002 and 2009 in the south of Minas Gerais State whose production accounts for about one third of the Brazilian coffee production. Landsat images were used to obtain a reference map of coffee areas and to identify MODIS 250 m pure pixels overlapping homogeneous coffee crops. Only MODIS pixels with 100% coffee were included in the analysis. A wavelet-based filter was used to smooth EVI and NDVI time profiles. Correlations were observed between variations on yield of coffee plots and variations on vegetation indices for pixels overlapping the same coffee plots. The vegetation index metrics best correlated to yield were the amplitude and the minimum values over the growing season. The best correlations were obtained between variation on yield and variation on vegetation indices the previous year (R = 0.74 for minEVI metric and R = 0.68 for minNDVI metric). Although correlations were not enough to estimate coffee yield exclusively from vegetation indices, trends properly reflect the biennial bearing effect on coffee yield. Keywords: remote sensing; coffee yield; vegetation indices; wavelet filtering.
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/J8LNKAN8RW/3D53ESE
zipped data URLhttp://urlib.net/zip/J8LNKAN8RW/3D53ESE
Languageen
Target Fileremotesensing-04-02492.pdf
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5. Allied materials
Next Higher Units8JMKD3MGPCW/3ER446E
DisseminationWEBSCI; PORTALCAPES; COMPENDEX.
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notes
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark mirrorrepository month nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype url
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1. Identity statement
Reference TypeJournal Article
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
IdentifierJ8LNKAN8RW/3C64765
Repositorydpi.inpe.br/plutao/2012/06.21.21.20.45   (restricted access)
Last Update2012:08.14.16.55.22 (UTC) marciana
Metadata Repositorydpi.inpe.br/plutao/2012/06.21.21.20.46
Metadata Last Update2021:07.28.21.56.19 (UTC) administrator
DOI10.1073/pnas.1111374109
ISSN0027-8424
Labellattes: 1913003589198061 6 MacedoDeMoStGaSh:2012:DeDeSo
Citation KeyMacedoDeMoStGaSh:2012:DeDeSo
TitleDecoupling of deforestation and soy production in the southern Amazon during the late 2000s
ProjectNational Aeronautics and Space Administration[NNX08AX08H]; Gordon and Betty Moore Foundation; Packard Foundation; National Science Foundation[DEB-0949996, DEB-0743703]
Year2012
MonthJan.
Access Date2023, Jan. 30
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size555 KiB
2. Context
Author1 Macedo, Marcia N.
2 DeFries, Ruth S.
3 Morton, Douglas C.
4 Stickler, Claudia M.
5 Galford, Gillian L.
6 Shimabukuro, Yosio Edemir
Resume Identifier1
2
3
4
5
6 8JMKD3MGP5W/3C9JJCQ
Group1
2
3
4
5
6 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1 Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY 10027;
2 Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY 10027;
3 Goddard Space Flight Center, National Aeronautics and Space Administration, Greenbelt, MD 20771;
4 Instituto de Pesquisa Ambiental da Amazônia, DF 71.503-505 Brasília, Bra
5 Woods Hole Research Center, Falmouth, MA 02540-1644
6 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1
2
3
4
5
6 yosio@ltid.inpe.br
e-Mail Addressyosio@ltid.inpe.br
JournalProceedings of the National Academy of Sciences of the United Sates of America
Volume109
Number4
Pages1341-1346
Secondary MarkA1_ASTRONOMIA_/_FÍSICA A1_BIOTECNOLOGIA B1_CIÊNCIA_DA_COMPUTAÇÃO A1_CIÊNCIAS_BIOLÓGICAS_I A1_CIÊNCIAS_BIOLÓGICAS_II A1_CIÊNCIAS_BIOLÓGICAS_III A1_ECOLOGIA_E_MEIO_AMBIENTE A1_FARMÁCIA A1_GEOCIÊNCIAS A1_GEOGRAFIA A1_INTERDISCIPLINAR A1_MEDICINA_I A1_MEDICINA_II A1_MEDICINA_III A1_MEDICINA_VETERINÁRIA A1_ODONTOLOGIA A1_PSICOLOGIA A1_QUÍMICA A1_SAÚDE_COLETIVA
History (UTC)2012-06-22 00:11:01 :: lattes -> secretaria.cpa@dir.inpe.br :: 2012
2012-08-14 16:55:22 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012
2013-03-22 14:11:54 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012
2013-03-22 14:19:21 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012
2013-03-22 14:38:49 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012
2013-03-26 18:12:57 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012
2016-06-04 01:08:05 :: administrator -> marciana :: 2012
2016-08-19 13:46:55 :: marciana -> administrator :: 2012
2021-07-28 21:56:19 :: administrator -> marciana :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordsagriculture
land sparing
extensification
Brazilian Amazon
AbstractFrom 2006 to 2010, deforestation in the Amazon frontier state of Mato Grosso decreased to 30% of its historical average (1996-2005) whereas agricultural production reached an all-time high. This study combines satellite data with government deforestation and production statistics to assess land-use transitions and potential market and policy drivers associated with these trends. In the forested region of the state, increased soy production from 2001 to 2005 was entirely due to cropland expansion into previously cleared pasture areas (74%) or forests (26%). From 2006 to 2010, 78% of production increases were due to expansion (22% to yield increases), with 91% on previously cleared land. Cropland expansion fell from 10 to 2% of deforestation between the two periods, with pasture expansion accounting for most remaining deforestation. Declining deforestation coincided with a collapse of commodity markets and implementation of policy measures to reduce deforestation. Soybean profitability has since increased to pre-2006 levels whereas deforestation continued to decline, suggesting that antideforestation measures may have influenced the agricultural sector. We found little evidence of direct leakage of soy expansion into cerrado in Mato Grosso during the late 2000s, although indirect land-use changes and leakage to more distant regions are possible. This study provides evidence that reduced deforestation and increased agricultural production can occur simultaneously in tropical forest frontiers, provided that land is available and policies promote the efficient use of already-cleared lands (intensification) while restricting deforestation. It remains uncertain whether government- and industry-led policies can contain deforestation if future market conditions favor another boom in agricultural expansion.
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Languageen
User Groupadministrator
lattes
secretaria.cpa@dir.inpe.br
Reader Groupadministrator
marciana
secretaria.cpa@dir.inpe.br
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Archiving Policydenypublisher allowfinaldraft
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ER446E
URL (untrusted data)www.pnas.org/cgi/doi/10.1073/pnas.1111374109
DisseminationWEBSCI; PORTALCAPES.
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notes
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn lineage mark mirrorrepository nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress rightsholder secondarydate secondarykey session shorttitle sponsor subject targetfile tertiarymark tertiarytype
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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP7W/3ATRC65
Repositorysid.inpe.br/mtc-m19/2011/12.06.17.38   (restricted access)
Last Update2012:08.14.14.45.34 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m19/2011/12.06.17.38.17
Metadata Last Update2021:02.12.13.48.14 (UTC) administrator
Secondary KeyINPE--PRE/
DOI10.1016/j.eswa.2011.07.044
ISSN0957-4174
Citation KeyCamargoAlCoFeOlHeFe:2012:OpSoOb
TitleAn open source object-based framework to extract landform classes
ProjectBrazilian National Council for Scientific Research (CNPQ); German Aerospace Agency (DLR)[491084/2005-6]
Year2012
MonthJan.
Access Date2023, Jan. 30
Secondary TypePRE PI
Number of Files1
Size3005 KiB
2. Context
Author1 Camargo, Flávio Fortes
2 Almeida, Cláudia Maria de
3 Costa, Gilson Alexandre Ostwald Pedro da
4 Feitosa, Raul Queiroz
5 Oliveira, D. A. B.
6 Heipke, Christian
7 Ferreira, R. S.
Resume Identifier1
2 8JMKD3MGP5W/3C9JGS3
Group1 DSR-OBT-INPE-MCTI-GOV-BR
2 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Dept. of Electric Engineering, Catholic University of Rio, R. Marquês de São Vicente, 225, 22451-900, Rio de Janeiro - RJ, Brazil
4 Dept. of Electric Engineering, Catholic University of Rio, R. Marquês de São Vicente, 225, 22451-900, Rio de Janeiro - RJ, Brazil
5 ept. of Electric Engineering, Catholic University of Rio, R. Marquês de São Vicente, 225, 22451-900, Rio de Janeiro - RJ, Brazil
6 IPI, Leibniz University of Hannover, Nienburger Str. 1, D-30167, Hannover, Germany
7 Leibniz Univ Hannover, Inst Photogrammetry & GeoInformat, D-30167 Hannover, Germany
Author e-Mail Address1 almeida@dsr.inpe.br
e-Mail Addresssecretaria.cpa@dir.inpe.br
JournalExpert Systems with Applications
Volume39
Number1
Pages541-554
Secondary MarkA1_ADMINISTRAÇÃO,_CIÊNCIAS_CONTÁBEIS_E_TURISMO B1_CIÊNCIA_DA_COMPUTAÇÃO A1_ENGENHARIAS_I A1_ENGENHARIAS_III A2_GEOCIÊNCIAS A1_INTERDISCIPLINAR
History (UTC)2011-12-06 17:47:04 :: secretaria.cpa@dir.inpe.br -> administrator :: 2011 -> 2012
2011-12-20 17:07:37 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012
2012-02-07 16:20:03 :: secretaria.cpa@dir.inpe.br -> banon :: 2012
2012-02-07 16:21:03 :: banon -> secretaria.cpa@dir.inpe.br :: 2012
2012-08-14 14:46:04 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012
2012-10-19 00:31:01 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012
2012-12-21 17:27:51 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012
2013-01-20 15:39:58 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012
2013-03-08 17:13:40 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012
2021-02-12 13:48:14 :: administrator -> marciana :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsCognitive approaches
Object-based image analysis
Semantic network
InterIMAGE
Geomorphology
AbstractThis paper introduces a new open source, knowledge-based framework for automatic interpretation of remote sensing images, called InterIMAGE. This framework exhibits a flexible modular architecture, in which image processing operators can be associated to both root and leaf nodes of a semantic network, which accounts for a differential strategy in comparison to other object-based image analysis platforms currently available. The architecture, main features as well as an overview on the interpretation strategy implemented in InterIMAGE are presented. The paper also reports an experiment on the classification of landforms. Different geomorphometric and textural attributes obtained from ASTER/Terra images were combined with fuzzy logic to drive the interpretation semantic network. Object-based statistical agreement indices, estimated from a comparison between the classified scene and a reference map, were used to assess the classification accuracy. The InterIMAGE interpretation strategy yielded a classification result with strong agreement and proved to be effective for the extraction of landforms.
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Languageen
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Reader Groupadministrator
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Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/mtc-m19@80/2009/08.21.17.02.53
Next Higher Units8JMKD3MGPCW/3ER446E
DisseminationWEBSCI; PORTALCAPES; COMPENDEX.
Host Collectionsid.inpe.br/mtc-m19@80/2009/08.21.17.02
6. Notes
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel format isbn label lineage mark nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress rightsholder secondarydate session shorttitle sponsor subject targetfile tertiarymark tertiarytype typeofwork url
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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP7W/3CGDHCB
Repositorysid.inpe.br/mtc-m19/2012/08.24.12.51   (restricted access)
Last Update2012:08.24.12.57.29 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m19/2012/08.24.12.51.29
Metadata Last Update2020:10.01.15.58.03 (UTC) administrator
Secondary KeyINPE--PRE/
ISSN0143-1161
Citation KeyLuciaLoboMoraBarbGalv:2012:ReSpCl
TitleReference spectra to classify Amazon water types
Year2012
MonthJune
Access Date2023, Jan. 30
Secondary TypePRE PI
Number of Files1
Size2041 KiB
2. Context
Author1 Lucia Lobo, Felipe
2 Moraes Novo, Evlyn Márcia Leão
3 Barbosa, Claudio Clemente
4 Galvão, Lênio Soares
Resume Identifier1
2
3
4 8JMKD3MGP5W/3C9JHLF
Group1
2 DSR-OBT-INPE-MCTI-GOV-BR
3 DPI-OBT-INPE-MCTI-GOV-BR
4 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
JournalInternational Journal of Remote Sensing
Volume33
Number11
Pages3422-3442
Secondary MarkB3_BIOTECNOLOGIA A1_CIÊNCIA_DA_COMPUTAÇÃO A2_CIÊNCIAS_AGRÁRIAS_I B2_CIÊNCIAS_BIOLÓGICAS_I B1_ECOLOGIA_E_MEIO_AMBIENTE B1_ENGENHARIAS_I B2_ENGENHARIAS_II B1_ENGENHARIAS_III A2_ENGENHARIAS_IV B1_GEOCIÊNCIAS A1_GEOGRAFIA A2_INTERDISCIPLINAR B1_ODONTOLOGIA A1_PLANEJAMENTO_URBANO_E_REGIONAL_/_DEMOGRAFIA A2_SAÚDE_COLETIVA
History (UTC)2012-08-24 12:51:29 :: marciana -> administrator ::
2012-08-24 12:51:29 :: administrator -> marciana :: 2012
2013-01-18 14:52:07 :: marciana -> administrator :: 2012
2020-10-01 15:58:03 :: administrator -> marciana :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsChlorophyll
Geodetic satellites
Reflection
AbstractReference spectra extracted from spectral libraries can distinguish different water types in images when associated with limnological information. In this study, we compiled available databases into a single spectral library, using field water reflectance spectra and limnological data collected by different researchers and campaigns in the Amazonian region. By using an iterative clustering procedure based on the combination of reflectance and optically active components (OACs), reference spectra representative of the major Amazonian water types were defined from this library. Differences between the resultant limnological classes were also evaluated by paired t-tests at significance level 0.05. Finally, reference spectra were tested for Spectral Angle Mapper (SAM) classification of waters in Hyperion/Earth Observing-One (EO-1) and Medium Resolution Imaging Spectrometer (MERIS)/Environment Satellite (Envisat) images acquired simultaneously as the field campaigns. Results showed highly variable concentrations of OACs due to the complexity of the Amazonian aquatic environments. Ten classes were defined to represent this complexity, broadly grouped into four limnological characteristics: clear waters with low concentrations of OACs (class 1); black waters rich in dissolved organic carbon (DOC) (class 2); waters with large concentrations of inorganic suspended solids (ISSs) (classes 3-7); and waters dominated by chlorophyll-a (chl-a) (classes 8-10). Using the ten reference spectra, SAM classification of the field water curves produced an overall accuracy of 86% with the highest values observed for classes 3, 4, 6 and 7 and the lowest accuracy for classes 1 and 2. The results of paired t-tests confirmed the class differences based on the concentrations of OACs. SAM classification of the Hyperion and MERIS images using ground truth information resulted in overall classification accuracies of 48% and 67%, respectively, with the highest errors associated with specific portions of the scenes that were not adequately represented in the spectral library.
AreaSRE
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > Reference spectra to...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Reference spectra to...
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4. Conditions of access and use
Languageen
User Groupadministrator
marciana
Reader Groupadministrator
marciana
Visibilityshown
Archiving Policydenypublisher denyfinaldraft12
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/mtc-m19@80/2009/08.21.17.02.53
Next Higher Units8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3ER446E
DisseminationWEBSCI; PORTALCAPES; MGA; COMPENDEX.
Host Collectionsid.inpe.br/mtc-m19@80/2009/08.21.17.02
6. Notes
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel doi e-mailaddress electronicmailaddress format isbn label lineage mark nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder secondarydate session shorttitle sponsor subject targetfile tertiarymark tertiarytype typeofwork url
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1. Identity statement
Reference TypeJournal Article
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
IdentifierJ8LNKAN8RW/3C646A9
Repositorydpi.inpe.br/plutao/2012/06.21.21.10.28   (restricted access)
Last Update2012:08.21.11.53.07 (UTC) administrator
Metadata Repositorydpi.inpe.br/plutao/2012/06.21.21.10.29
Metadata Last Update2020:10.01.15.57.39 (UTC) administrator
DOI10.1109/LGRS.2012.2185213
ISSN1545-598X
Labellattes: 3852581196429739 2 FariasLorBenChaRom:2012:FuLoAp
Citation KeyFariasLorBenChaRom:2012:FuLoAp
TitleFuzzy Logic Applied to Track Generation Areas of Swell Systems Observed by SAR
Year2012
Access Date2023, Jan. 30
Secondary TypePRE PI
Number of Files1
Size691 KiB
2. Context
Author1 Farias, Eduardo Gentil de
2 Lorenzzetti, Joao Antonio
3 Bentamy, Abderrahim
4 Chapron, Bertrand
5 Romain, Husson
Resume Identifier1
2 8JMKD3MGP5W/3C9JHEF
Group1 DSR-OBT-INPE-MCTI-GOV-BR
2 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Laboratoire d’Oceanographie Spatiale, Institut Français de Recherche pour l’Exploitation de la Mer, 29280 Plouzané, France
4 Laboratoire d’Oceanographie Spatiale, Institut Français de Recherche pour l’Exploitation de la Mer, 29280 Plouzané, France
5 Collecte Localisation Satellites, 29280 Plouzané, France
Author e-Mail Address1 gentil@dsr.inpe.br
2 loren@dsr.inpe.br
e-Mail Addressloren@dsr.inpe.br
JournalIEEE Geoscience and Remote Sensing Letters
Volume9
Number5
Pages841-845
Secondary MarkB2_ASTRONOMIA_/_FÍSICA B2_BIOTECNOLOGIA B1_CIÊNCIA_DA_COMPUTAÇÃO A1_ENGENHARIAS_IV A2_GEOCIÊNCIAS B1_GEOGRAFIA
History (UTC)2012-06-22 00:11:01 :: lattes -> administrator :: 2012
2012-07-18 14:03:30 :: administrator -> secretaria.cpa@dir.inpe.br :: 2012
2012-08-21 11:53:07 :: secretaria.cpa@dir.inpe.br -> administrator :: 2012
2020-10-01 15:57:39 :: administrator -> marciana :: 2012
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsSynthetic Aperture Radar
Swell
Wave Propagation
AbstractRecently, with the availability of a great number of synthetic aperture radar (SAR) wave mode spectra, it has been possible to derive a set of great circle lines of swell propagation whose intersection points indicate the position of the storm generating the observed swell field. However, due to the inherent limitations of SAR spectra, the locus of convergence of great circle of swell propagation can be sometimes diffuse or contain multiple convergence regions. In this letter, we adapted the fuzzy cluster logic method to identify the regions of convergence of SAR wave field rays. The analysis of the results of the fuzzy algorithm clearly indicates the ability of this statistical method to identify the cluster center region of swell fields observed in SAR wave mode images. The measure of success of the method was how well the generation center of the swell could be traced back to an existing strong storm system.
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Reference TypeJournal Article
Sitemtc-m16d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP7W/3DETLH2
Repositorysid.inpe.br/mtc-m19/2013/01.28.12.36   (restricted access)
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DOI10.1007/s10933-011-9545-6
ISSN0921-2728
Citation KeyMcGlueSCZTEPSCA:2012:LiBrFo
TitleErratum to: Limnogeology in Brazil's "forgotten wilderness": A synthesis from the large floodplain lakes of the Pantanal
Year2012
Access Date2023, Jan. 30
Secondary TypePRE PI
Number of Files1
Size124 KiB
2. Context
Author 1 McGlue, M. M.
 2 Silva, A.
 3 Corradini, F. A.
 4 Zani, H.
 5 Trees, M. A.
 6 Ellis, G. S.
 7 Parolin, M.
 8 Swarzenski, P. W.
 9 Cohen, A. S.
10 Assine, M. L. h.
Group 1
 2
 3
 4 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation 1 Department of Geosciences, The University of Arizona, 1040 East 4th Street, Tucson, AZ 85721, United States
 2 Departamento de Ciências do Ambiente, Universidade Federal de Mato Grosso do Sul-UFMS-CPAN, Av. Rio Branco, 1270, Corumbá, MS 79304-902, Brazil
 3 Faculdade de Geografia, Universidade Federal do Pará- UFPA, Folha 31, Quadra 7, Lote Especial S/N, Marabá, PA 68501-970, Brazil
 4 Instituto Nacional de Pesquisas Espaciais (INPE)
 5 Energy Resources Program, U.S. Geological Survey, Denver, CO, United States
 6
 7 Faculdade Estadual de Ciências e Letras de Campo Mourão, Av. Comendador Norberto Marcondes, 733, Campo Mourão, PR 87303-100, Brazil
 8 U.S. Geological Survey, Santa Cruz, CA, United States
 9 U.S. Geological Survey, Santa Cruz, CA, United States
10 Departamento de Geologia Aplicada-IGCE, Universidade Estadual Paulista-UNESP/Campus Rio Claro, Av. 24-A, 1515, Rio Claro, SP 13506-900, Brazil
JournalJournal of Paleolimnology
Volume47
Number1
Pages165-166
History (UTC)2013-01-28 15:18:13 :: marciana -> administrator :: 2012
2013-07-19 01:42:10 :: administrator -> banon :: 2012
2013-08-05 16:52:40 :: banon -> administrator :: 2012
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Reference TypeJournal Article
Sitemtc-m16d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP7W/3CHDR6L
Repositorysid.inpe.br/mtc-m19/2012/08.30.18.03   (restricted access)
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Secondary KeyINPE--PRE/
DOI10.1007/s11852-011-0164-1
ISSN1400-0350
Citation KeyContiArArBaRoMaFu:2012:BaCaIn
TitleAn integrated GIS for sedimentological and geomorphological analysis of a lagoon environment. Barra de Cananéia inlet region, (Southeastern Brazil)
Year2012
MonthMar.
Access Date2023, Jan. 30
Secondary TypePRE PI
Number of Files1
Size1146 KiB
2. Context
Author1 Conti, Luis Américo
2 Araujo, Carlos Alberto S.
3 Araujo, Carlos Alberto Sampaio de
4 Barcellos, Roberto L.
5 Rodrigues, Marcelo
6 Mahiques, Michel M.
7 Furtado, Valdenir V.
Group1
2 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1 Universidade de São Paulo
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Universidade de São Paulo
4 Universidade Federal de Pernambuco
Author e-Mail Address1 lconti@usp.br
JournalJournal of Coastal Conservation
Volume16
Number1
Pages13-24
History (UTC)2012-10-02 12:43:34 :: marciana -> administrator :: 2012
2012-10-02 12:43:59 :: administrator -> marciana :: 2012
2012-10-09 18:23:24 :: marciana -> administrator :: 2012
2012-11-27 16:12:35 :: administrator -> marciana :: 2012
2012-11-27 16:28:36 :: marciana -> administrator :: 2012
2018-06-05 04:12:55 :: administrator -> marciana :: 2012
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KeywordsBottom sediments
Coastal manegement
Gis
Lagoon
Organic matter
Sediment transport
AbstractThe aim of this work is to use GIS integration data to characterize sedimentary processes in a SubTropical lagoon environment. The study area was the Cananéia Inlet estuary in the southeastern section of the Cananéia Lagoon Estuarine System (CLES), state of São Paulo, Brazil (25°03′S/47°53′W). The area is formed by the confluence of two estuarine channels forming a bay-shaped water body locally called "Trapandé Bay". The region is surrounded by one of the most preserved tracts of Atlantic Rain Forest in Southwestern Brazil and presents well-developed mangroves and marshes. In this study a methodology was developed using integrated a GIS database based on bottom sediment parameters, geomorphological data, remote sensing images, Hidrodynamical Modeling data and geophysical parameters. The sediment grain size parameters and the bottom morphology of the lagoon were also used to develop models of net sediment transport pathways. It was possible to observe that the sediment transport vectors based on the grain size model had a good correlation with the transport model based on the bottom topography features and Hydrodynamic model, especially in areas with stronger energetic conditions, with a minor contribution of finer sediments. This relation is somewhat less evident near shallower banks and depositional features. In these regions the organic matter contents in the sediments was a good complementary tool for inferring the hydrodynamic and depositional conditions (i.e. primary productivity, sedimentation rates, sources, oxi-reduction rates).
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Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress format isbn label lineage mark nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url
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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP7W/3CGEDBB
Repositorysid.inpe.br/mtc-m19/2012/08.24.17.30
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Secondary KeyINPE--PRE/
DOI10.3390/rs4051245
ISSN2072-4292
Citation KeyAnderson:2012:BiFoPr
TitleBiome-scale forest properties in Amazonia based on field and satellite observations
Year2012
MonthMay
Access Date2023, Jan. 30
Secondary TypePRE PI
Number of Files1
Size1790 KiB
2. Context
AuthorAnderson, Liana O
GroupDSR-OBT-INPE-MCTI-GOV-BR
AffiliationInstituto Nacional de Pesquisas Espaciais (INPE), Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, United Kingdom
JournalRemote Sensing
Volume4
Number5
Pages1245-1271
History (UTC)2012-08-30 12:14:24 :: marciana -> administrator :: 2012
2012-11-22 00:33:56 :: administrator -> marciana :: 2012
2012-12-11 12:44:14 :: marciana -> administrator :: 2012
2018-06-05 04:12:55 :: administrator -> marciana :: 2012
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KeywordsDIFFERENCE VEGETATION INDEX
NOAA-AVHRR DATA
NET PRIMARY PRODUCTION
TROPICAL RAIN-FOREST
LEAF-AREA INDEX
LANDSAT TM DATA
BRAZILIAN AMAZON
ABOVEGROUND BIOMASS
SOUTH-AMERICA
WOOD DENSITY
AbstractAmazonian forests are extremely heterogeneous at different spatial scales. This review intends to present the large-scale patterns of the ecosystem properties of Amazonia, and focuses on two parts of the main components of the net primary production: the long-lived carbon pools (wood) and short-lived pools (leaves). First, the focus is on forest biophysical properties, and secondly, on the macro-scale leaf phenological patterns of these forests, looking at field measurements and bringing into discussion the recent findings derived from remote sensing dataset. Finally, I discuss the results of the three major droughts that hit Amazonia in the last 15 years. The panorama that emerges from this review suggests that slow growing forests in central and eastern Amazonia, where soils are poorer, have significantly higher above ground biomass and higher wood density, trees are higher and present lower proportions of large-leaved species than stands in northwest and southwest Amazonia. However, the opposite pattern is observed in relation to forest productivity and dynamism, which is higher in western Amazonia than in central and eastern forests. The spatial patterns on leaf phenology across Amazonia are less marked. Field data from different forest formations showed that new leaf production can be unrelated to climate seasonality, timed with radiation, timed with rainfall and/or river levels. Oppositely, satellite images exhibited a large-scale synchronized peak in new leaf production during the dry season. Satellite data and field measurements bring contrasting results for the 2005 drought. Discussions on data processing and filtering, aerosols effects and a combined analysis with field and satellite images are presented. It is suggested that to improve the understanding of the large-scale patterns on Amazonian forests, integrative analyses that combine new technologies in remote sensing and long-term field ecological data are imperative.
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6. Notes
Empty Fieldsalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel e-mailaddress electronicmailaddress format isbn label lineage mark nextedition notes orcid parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder secondarydate secondarymark session shorttitle sponsor subject tertiarymark tertiarytype typeofwork url
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Reference TypeJournal Article
Sitemtc-m16d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP7W/3CGDM8P
Repositorysid.inpe.br/mtc-m19/2012/08.24.13.38   (restricted access)
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Secondary KeyINPE--PRE/
DOI10.1007/s12665-011-1434-9
ISSN1866-6280
Citation KeyMoraisMartPara:2012:MuApUs
TitleMulti-scale approach using remote sensing images to characterize the iron deposit N1 influence areas in Carajás Mineral Province (Brazilian Amazon)
Year2012
MonthAug.
Access Date2023, Jan. 30
Secondary TypePRE PI
Number of Files1
Size1193 KiB
2. Context
Author1 Morais, Maria Carolina
2 Martins Junior, Paulo Pereira
3 Paradella, Waldir Renato
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JJBT
Group1
2
3 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1 Mining School, Geology Department (DEGEO), Federal University of Ouro Preto (UFOP), Av. José Cândido da Silveira, 2000, Horto, Belo Horizonte, MG 31170-000, Brazil
2 Water Resources Sector (SAA), Tecnology Centre of Minas Gerais (CETEC), Av. José Cândido Da Silveira, 2000, Horto, Belo Horizonte, MG 31170-000, Brazil
3 Instituto Nacional de Pesquisas Espaciais (INPE)
JournalEnvironmental Earth Sciences
Volume66
Number7
Pages2085-2096
History (UTC)2012-08-24 13:43:09 :: marciana -> administrator :: 2012
2018-06-05 04:12:54 :: administrator -> marciana :: 2012
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KeywordsDeforestation - Image reconstruction - Iron deposits - Iron ores - Mineral resources - Physical chemistry - Radar - Remote sensing
AbstractMining activities cause a wide range of changes to the environment, substantially affecting both the physical and biological environmental sectors. In the Caraja´s Mineral Province, located in the Amazon rainforest, environmental regulations tend to be more rigorous, due to the fragility of the environment in which large iron deposits are found. The characterization of the impact of mining on environment considers: the type and extent of the impact, the physical chemistry differences and similarities of the mineral deposits, the deposit size, the adopted mining process, and the environment (both natural and economic) in which the mining process was developed. Remote sensing technology is utilized in this study, in particular, the use of ortho-aerial photograph, and optical and radar images with distinct spatial resolution. These permit the elaboration in synoptic maps, multi-scale and dynamic, of the changes wrought upon the environment: deforestation, removal of vegetation cover, topographic surface and landscape alteration, and slope instabilities among others. In this aspect, determining the extent of influence of the mining activity is directly tied to the characterization of its impact on various natural systems at the observed scale, and not by simply defining a predetermined Euclidean distance. The results showed that remote sensing technology, optical and radar images, proved to be efficient in the study of environmental information and the areas of influence on the semi-regional and local scales in the Amazon forest.
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Reference TypeJournal Article
Sitemtc-m16d.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP7W/3CEU62H
Repositorysid.inpe.br/mtc-m19/2012/08.15.13.19   (restricted access)
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Secondary KeyINPE--PRE/
DOI10.1016/j.ecoinf.2011.12.003
ISSN1574-9541
Citation KeyValérioKampAssiStec:2012:AsFrOp
TitleThe asymmetric fragmentation operator applied to meteo-limnological time series in a tropical reservoir
Year2012
MonthMar.
Access Date2023, Jan. 30
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size1516 KiB
2. Context
Author1 Valério, A. M.
2 Kampel, Milton
3 Assireu, Arcilan Trevenzoli
4 Stech, José Luis
Resume Identifier1
2 8JMKD3MGP5W/3C9JHTG
Group1 DSR-OBT-INPE-MCTI-GOV-BR
2 DSR-OBT-INPE-MCTI-GOV-BR
3 DSR-OBT-INPE-MCTI-GOV-BR
4 DSR-OBT-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 alineval@dsr.inpe.br
2 milton@dsr.inpe.br
3
4 stech@dsr.inpe.br
e-Mail Addressmarcelo.pazos@inpe.br
JournalEcological Informatics
Volume8
Pages29-36
Secondary MarkB2_CIÊNCIA_DA_COMPUTAÇÃO B1_ECOLOGIA_E_MEIO_AMBIENTE B2_ENGENHARIAS_IV C_ENSINO_DE_CIÊNCIAS_E_MATEMATICA A2_INTERDISCIPLINAR
History (UTC)2012-08-15 13:38:04 :: marcelo.pazos@sid.inpe.br -> administrator :: 2012
2016-07-03 21:01:52 :: administrator -> marcelo.pazos@inpe.br :: 2012
2016-10-13 01:48:48 :: marcelo.pazos@inpe.br -> administrator :: 2012
2018-06-05 04:12:42 :: administrator -> marcelo.pazos@inpe.br :: 2012
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KeywordsAsymmetric fragmentation
Complex systems
Ecological processes
Reservoir
Wavelet transform INDEX KEYWORDS: asymmetry
complexity
data set
ecological modeling
fragmentation
limnology
prediction
pristine environment
reservoir
time series
tropical environment
wavelet analysis
Brazil
Manso Reservoir
Mato Grosso
AbstractEcological data are sometimes difficult to analyze due to the intrinsic complexity of natural systems containing nonlinear equations. Efficient methods are required to better understand the information extracted from complex processes and to support the development of ecological prediction models. In this context, two techniques were used in this work to analyze meteo-limnological time series from a tropical reservoir: theWavelet Transform (WT) and the Asymmetric Fragmentation Operator (AFO). The in situ data is based on a dataset acquired from an Eulerian systemdeployed in Manso Reservoir, Brazil, in 2007. The results indicated that the AFO method outperformed theWT method in the analysis of ecological parameters. The pioneering use of AFO in this sort of study proved to be a useful tool to study the variability of water quality parameters.
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