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Tipo da ReferênciaConference Proceedings
Sitemtc-m21b.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP5W34M/3HE6FE8
Repositóriosid.inpe.br/mtc-m21b/2014/11.18.23.58.45
Última Atualização2014:12.09.12.25.16 administrator
Metadadossid.inpe.br/mtc-m21b/2014/11.18.23.58.46
Última Atualização dos Metadados2018:06.04.03.04.31 administrator
DOI10.1117/12.2066031
ISBN9781628412765
ISSN0277786X
Rótuloscopus 2014-11 SantosJGTMMGK:2014:DeAbBi
Chave de CitaçãoSantosSGTMMGK:2014:DeAbBi
TítuloDetermining aboveground biomass of the forest successional chronosequence in a test-site of Brazilian Amazon through X- and L-band data analysis
Ano2014
Dataapr. 7, 2014
Data de Acesso03 dez. 2020
Número de Arquivos1
Tamanho458 KiB
Área de contextualização
Autor1 Santos, João Roberto dos
2 Silva, Camila Valéria de Jesus
3 Galvão, Lenio Soares
4 Treuhaft, Robert
5 Mura, José Cláudio
6 Madsen, Soren
7 Gonçalves, Fábio Guimarães
8 Keller, Michael Maier
Identificador de Curriculo1 8JMKD3MGP5W/3C9JHF4
2
3 8JMKD3MGP5W/3C9JHLF
4
5 8JMKD3MGP5W/3C9JHGR
Grupo1 DSR-OBT-INPE-MCTI-GOV-BR
2 SER-SRE-SPG-INPE-MCTI-GOV-BR
3 DSR-OBT-INPE-MCTI-GOV-BR
4
5 DPI-OBT-INPE-MCTI-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA, 91109, United States
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA, 91109, United States
7 Woods Hole Research Center, 149, Woods Hole Road, MA, 02540, United States
8 USDA Forest Service, Rio-Piedras, 100745, Puerto Rico; University of New Hampshire, Durham, NH 03824, United States
Endereço de e-Mailmarcelo.pazos@inpe.br
Nome do EventoInternational Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 2
Localização do EventoPaphos, Cyprus
Volume9229
Título do LivroProceedings
Editora (Publisher)SPIE
Cidade da EditoraPaphos
Histórico2018-06-04 03:04:31 :: administrator -> marcelo.pazos@inpe.br :: 2014
Área de conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Documentoconcluido
Estágio do Documentonot transferred
Transferível1
Tipo do ConteudoExternal Contribution
Tipo SecundárioPRE CI
Tipo de Versãopublisher
Palavras-ChaveBiomass, Forestry, Interferometry, Monitoring, Regression analysis, Remote sensing, Amazon forests, Biophysical parameters, Interferometric coherence, Multivariate regression, PALSAR/ALOS, Secondary succession, TanDEM/TerraSAR-X, Volumetric scattering, Synthetic aperture radar, Biomass, Forestry, Monitoring, Radar, Regression Analysis, Remote Sensing.
ResumoSecondary succession is an important process in the Amazonian region with implications for the global carbon cycle and for the sustainable regional agricultural and pasture activities. In order to better discriminate the secondary succession and to characterize and estimate the aboveground biomass (AGB), backscatter and interferometric SAR data generally have been analyzed through empirical-based statistical modeling. The objective of this study is to verify the capability of the full polarimetric PALSAR/ALOS (L-band) attributes, when combined with the interferometric (InSAR) coherence from the TanDEM-X (X-band), to improve the AGB estimates of the succession chronosequence located in the Brazilian Tapajós region. In order to perform this study, we carried out multivariate regression using radar attributes and biophysical parameters acquired during a field inventory. A previous floristic-structural analysis was performed to establish the chronosequence in three stages: initial vegetation regrowth, intermediate, and advanced regrowth. The relationship between PALSAR data and AGB was significant (p<0.001) and results suggested that the " volumetric scattering" ? (Pv) and " anisotropy" ? (A) attributes were important to explain the biomass content of the successional chronosequence (R2 adjusted= 0.67; RMSE = 32.29 Mg.ha -1). By adding the TanDEM-derived interferometric coherence (i) into the regression modeling, better results were obtained (R2 adjusted = 0.75; RMSE = 28.78Mg.ha-1). When we used both the L- and X-band attributes, the stock density prediction improved to 10.8 % for the secondary succession stands. © 2014 SPIE.
AreaSRE
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