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Tipo da ReferênciaJournal Article
Identificador8JMKD3MGP3W34P/3MPQ47L
Repositóriosid.inpe.br/mtc-m21b/2016/11.11.15.57
Metadadossid.inpe.br/mtc-m21b/2016/11.11.15.57.05
Sitemtc-m21b.sid.inpe.br
DOI10.1590/0001-3765201620150176
ISSN0001-3765
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Chave de CitaçãoCuradoMuCuRoPeNoSa:2016:MoRePh
Autor1 Curado, Leone F. A.
2 Musis, Carlos R. de
3 Cunha, Cristiano R. da
4 Rodrigues, Thiago R.
5 Pereira, Vinicius Márcio Rodrigues
6 Nogueira, José S.
7 Sanches, Luciana
Grupo1
2
3
4
5 CRC-CRC-INPE-MCTI-GOV-BR
Afiliação1 Universidade Federal do Mato Grosso (UFMT)
2 Universidade Federal do Mato Grosso (UFMT)
3 Universidade Federal do Mato Grosso (UFMT)
4 Universidade Federal do Mato Grosso (UFMT)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Universidade Federal do Mato Grosso (UFMT)
7 Universidade Federal do Mato Grosso (UFMT)
Endereço de e-Mail do Autor1
2
3
4 thiagorangel@pgfa.ufmt.br
5 vinicius.pereira@inpe.br
TítuloModeling the reflection of Photosynthetically active radiation in a monodominant floodable forest in the Pantanal of Mato Grosso State using multivariate statistics and neural networks
RevistaAnais da Academia Brasileira de Ciência
Ano2016
Volume88
Número3
MêsSept.
Palavras-ChavePantanal, photosynthetically active radiation (PAR), Cambarazal, Albedo.
ResumoThe study of radiation entrance and exit dynamics and energy consumption in a system is important for understanding the environmental processes that rule the biosphere-atmosphere interactions of all ecosystems. This study provides an analysis of the interaction of energy in the form of photosynthetically active radiation (PAR) in the Pantanal, a Brazilian wetland forest, by studying the variation of PAR reflectance and its interaction with local rainfall. The study site is located in Private Reserve of Natural Heritage, Mato Grosso State, Brazil, where the vegetation is a monodominant forest of Vochysia divergens Phol. The results showed a high correlation between the reflection of visible radiation and rainfall; however, the behavior was not the same at the three heights studied. An analysis of the hourly variation of the reflected waves also showed the seasonality of these phenomena in relation to the dry and rainy seasons. A predictive model for PAR was developed with a neural network that has a hidden layer, and it showed a determination coefficient of 0.938. This model showed that the Julian day and time of measurements had an inverse association with the wind profile and a direct association with the relative humidity profile.
Páginas1387-1395
Idiomaen
Tipo de Trabalhojournal article
Tipo SecundárioPRE PN
DivulgaçãoWEBSCI; PORTALCAPES; SCIELO; SCOPUS.
AreaETES
Tamanho1194 KiB
Número de Arquivos1
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