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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3M3AHQS
Repositorysid.inpe.br/mtc-m21b/2016/07.08.13.43
Last Update2016:07.08.13.44.17 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21b/2016/07.08.13.43.20
Metadata Last Update2018:06.04.02.41.00 (UTC) administrator
DOI10.3390/s16070956
ISSN1424-8220
Citation KeyOliveiraBrMoBeSaShAr:2016:UsMOSe
TitleUse of MODIS sensor images combined with reanalysis products to retrieve net radiation in Amazonia
Year2016
MonthJuly
Access Date2024, May 18
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size10668 KiB
2. Context
Author1 Oliveira, Gabriel de
2 Brunsell, Nathaniel A.
3 Moraes, Elisabete Caria
4 Bertani, Gabriel
5 Santos, Thiago V. dos
6 Shimabukuro, Yosio Edemir
7 Aragão, Luiz Eduardo Oliveira e Cruz de
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JH24
4
5
6 8JMKD3MGP5W/3C9JJCQ
Group1 SER-SRE-SPG-INPE-MCTI-GOV-BR
2
3 DSR-OBT-INPE-MCTI-GOV-BR
4 SER-SRE-SPG-INPE-MCTI-GOV-BR
5
6 DSR-OBT-INPE-MCTI-GOV-BR
7 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Department of Geography and Atmospheric Science, University of Kansas, 1475 Jayhawk Boulevard, Lawrence, KS, United States
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Department of Soil, Water and Climate, University of Minnesota, 1991 Upper Bufford Circle, Saint Paul, MN, United States
6 Instituto Nacional de Pesquisas Espaciais (INPE)
7 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 gdo@dsr.inpe.br
2 brunsell@ku.edu
3 bete@dsr.inpe.br
4 gabrielb@dsr.inpe.br
5 dossa013@umn.edu
6 yosio@dsr.inpe.br
7 laragao@dsr.inpe.br
JournalSensors
Volume16
Number7
Pages956
Secondary MarkA1_GEOGRAFIA A1_ENGENHARIAS_IV A2_MATERIAIS A2_INTERDISCIPLINAR A2_ENGENHARIAS_I A2_CIÊNCIA_DA_COMPUTAÇÃO B1_MEDICINA_III B1_MEDICINA_II B1_MEDICINA_I B1_GEOCIÊNCIAS B1_ENGENHARIAS_III B1_ENGENHARIAS_II B1_EDUCAÇÃO_FÍSICA B1_BIODIVERSIDADE B2_QUÍMICA B2_CIÊNCIAS_BIOLÓGICAS_II B2_CIÊNCIAS_BIOLÓGICAS_I B2_BIOTECNOLOGIA B2_ASTRONOMIA_/_FÍSICA B3_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA B3_CIÊNCIAS_BIOLÓGICAS_III B4_LETRAS_/_LINGUÍSTICA C_CIÊNCIAS_AGRÁRIAS_I
History (UTC)2016-07-08 13:43:20 :: simone -> administrator ::
2016-07-08 13:43:21 :: administrator -> simone :: 2016
2016-07-08 13:44:18 :: simone -> administrator :: 2016
2016-07-11 06:35:47 :: administrator -> simone :: 2016
2016-08-19 16:47:10 :: simone -> administrator :: 2016
2018-06-04 02:41:00 :: administrator -> simone :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsAmazon region
GLDAS data
LBA project
MODIS sensor
Net radiation
AbstractIn the Amazon region, the estimation of radiation fluxes through remote sensing techniques is hindered by the lack of ground measurements required as input in the models, as well as the difficulty to obtain cloud-free images. Here, we assess an approach to estimate net radiation (Rn) and its components under all-sky conditions for the Amazon region through the Surface Energy Balance Algorithm for Land (SEBAL) model utilizing only remote sensing and reanalysis data. The study period comprised six years, between January 2001December 2006, and images from MODIS sensor aboard the Terra satellite and GLDAS reanalysis products were utilized. The estimates were evaluated with flux tower measurements within the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) project. Comparison between estimates obtained by the proposed method and observations from LBA towers showed errors between 12.5% and 16.4% and 11.3% and 15.9% for instantaneous and daily Rn, respectively. Our approach was adequate to minimize the problem related to strong cloudiness over the region and allowed to map consistently the spatial distribution of net radiation components in Amazonia. We conclude that the integration of reanalysis products and satellite data, eliminating the need for surface measurements as input model, was a useful proposition for the spatialization of the radiation fluxes in the Amazon region, which may serve as input information needed by algorithms that aim to determine evapotranspiration, the most important component of the Amazon hydrological balance.
AreaSRE
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Use of MODIS...
Arrangement 2urlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Use of MODIS...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://mtc-m21b.sid.inpe.br/ibi/8JMKD3MGP3W34P/3M3AHQS
zipped data URLhttp://mtc-m21b.sid.inpe.br/zip/8JMKD3MGP3W34P/3M3AHQS
Languageen
Target Fileoliverira_use.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policyallowpublisher allowfinaldraft
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3ER446E
8JMKD3MGPCW/3F3NU5S
Citing Item Listsid.inpe.br/bibdigital/2013/10.18.22.34 1
sid.inpe.br/mtc-m21/2012/07.13.14.45.11 1
DisseminationWEBSCI; PORTALCAPES.
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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