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1. Identity statement
Reference TypeBook Section
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3LRKB5B
Repositorysid.inpe.br/mtc-m21b/2016/06.09.19.27   (restricted access)
Last Update2016:06.09.19.28.02 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21b/2016/06.09.19.27.16
Metadata Last Update2018:06.04.02.40.54 (UTC) administrator
Secondary KeyINPE--/
DOI10.5772/61869
ISBN978-953-51-2444-3
978-953-51-2443-6
Citation KeyOgashawaraCurtAraúStec:2016:BiMoTr
TitleBio-optical modeling in a tropical hypersaline lagoon environment
Year2016
Access Date2024, Apr. 20
Secondary TypePRE LI
Number of Files1
Size1845 KiB
2. Context
Author1 Ogashawara, Igor
2 Curtarelli, Marcelo Pedroso
3 Araújo, Carlos Alberto Sampaio de
4 Stech, José Luiz
Resume Identifier1
2
3
4 8JMKD3MGP5W/3C9JHHN
Group1
2 DSR-OBT-INPE-MCTI-GOV-BR
3 DSR-OBT-INPE-MCTI-GOV-BR
4 DSR-OBT-INPE-MCTI-GOV-BR
Affiliation1 Indiana University
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
2 mpedroso@dsr.inpe.br
3 carlos@dsr.inpe.br
4 jose.stech@inpe.br
EditorMarghany, Maged
Book TitleEnvironmental applications of remote sensing
PublisherInTech
Pages235-258
History (UTC)2016-06-09 19:28:02 :: simone -> administrator :: 2016
2018-06-04 02:40:54 :: administrator -> simone :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsWater quality
chlorophyll-a
turbidity
bio-optical modeling
AbstractIn this chapter, we attempted to present an overview of the use of remote sensing to mon‐ itor water quality parameters, mainly chlorophyll-a (chl-a) and turbidity. We summarized the main concepts of bio-optical modeling and presented a case study of the application of the Hyperspectral Imager for the Coastal Ocean (HICO) for the monitoring of water quality in a tropical hypersaline aquatic environment. Using HICO, we evaluated a set of different semi-empirical bio-optical algorithms for chl-a and turbidity estimation devel‐ oped for inland and oceanic waters in the Araruama Lagoon, RJ, Brazil, which is an ex‐ treme environment due to its high salinity values. We also developed an empirical algorithm for both water quality parameters and compared the performances. Results showed that for chl-a estimation all models have a low performance with a normalized root mean square error (NRMSE) varying from 24.13 to 30.46. For turbidity, the bio-opti‐ cal algorithms showed a better performance with the NRMSE between 15.49 and 28.04. Overall, these results highlight the importance of including extreme environments, such as the Araruama Lagoon, on the validation of bio-optical algorithms as well as the need for new orbital hyperspectral sensors which will improve the development of the field.
AreaSRE
Arrangementurlib.net > BDMCI > Fonds > Produção pgr ATUAIS > SER > Bio-optical modeling in...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
Languageen
Target Fileogashawara_bio.pdf
User Groupsimone
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3ER446E
DisseminationBNDEPOSITOLEGAL
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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7. Description control
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