@MastersThesis{Zerbini:1992:EsFiAé,
author = "Zerbini, Newton Jord{\~a}o",
title = "Estimativa de fitomassa a{\'e}rea em regi{\~a}o de floresta
tropical com uso de dados TM-LANDSAT 5 e HRV-SPOT 1",
school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
year = "1992",
address = "Sao Jose dos Campos",
month = "1992-12-16",
keywords = "vegeta{\c{c}}{\~a}o, Amaz{\^o}nia (regi{\~a}o), florestas,
biomassa, TM-LANDSAT 5, HRV-SPOT 1(sat{\'e}lite franc{\^e}s),
sat{\'e}lites LANDSAT, uso da terra, biomass, rain forest,
vegetation, land use, HRV-SPOT 1 (french satellite), TM-LANDSAT
5.",
abstract = "A floresta Amaz{\^o}nica tem sido tema de grandes discuss{\~o}es
devido {\`a} amplitude das interven{\c{c}}{\~o}es ali
realizadas. Com uma {\'a}rea de 3,5 milh{\~o}es de Km2 a
Amaz{\^o}nia brasileira requer sistemas eficientes de coleta de
informa{\c{c}}{\~o}es para a gest{\~a}o racional dos seus
recursos florestais. O presente trabalho prop{\~o}e o
desenvolvimento de um m{\'e}todo de quantifica{\c{c}}{\~a}o de
fitomassa a{\'e}rea de floresta tropical, a partir de dados
espectrais obtidos de imagens TM-LANDSAT 5 e HRV-SPOT 1, em
{\'a}rea a ser inundada por hidrel{\'e}trica. Para isso,
determinou-se a correla{\c{c}}{\~a}o entre as vari{\'a}veis de
fitomassa a{\'e}rea, dendrom{\'e}tricas, espectrais e de cota,
em quatro parcelas consideradas: Floresta Densa de Terra Firme -
Relevo Ondulado (parcelas 1 e 4), Floresta Densa de Terra Firme -
Relevo Plano (parcela 2) e Floresta de Baixo (parcela 3). As
parcelas foram divididas em tr{\^e}s estratos: superior,
intermedi{\'a}rio e inferior. Ao contr{\'a}rio dos demais
estratos, as vari{\'a}veis espectrais, combinadas com as
vari{\'a}veis de fitomassa, nao permitiram a
quantifica{\c{c}}{\~a}o da fitomassa a{\'e}rea do estrato
superior da floresta. Com o uso de An{\'a}lise de Regress{\~a}o
identificaram-se as equa{\c{c}}{\~o}es de
quantifica{\c{c}}{\~a}o de fitomassa. O m{\'e}todo proposto
apresentou-se vi{\'a}vel e com resultados significativos seja com
a utiliza{\c{c}}{\~a}o de imagens TM-LANDSAT ou HRV-SPOT, seja
imagens {\'{\i}}ndice ou imagens fra{\c{c}}{\~a}o. Dentre doze
modelos testados, optou-se pela utiliza{\c{c}}{\~a}o do modelo
de ajuste linear, que demonstrou signific{\^a}ncia entre as
vari{\'a}veis de fitomassa dos estratos intermedi{\'a}rios e
inferior e as vari{\'a}veis espectrais e de cota. E
recomend{\'a}vel a realiza{\c{c}}{\~a}o de estudo de modelagem,
com vistas a defini{\c{c}}{\~a}o de modelos mais eficientes para
quantifica{\c{c}}{\~a}o de fitomassa nos tr{\^e}s estratos.
ABSTRACT: The Amazon forest has been the subject of much debate
due to the extent of human intervention occurring there. The
Brazilian Amazon, with 3.5 million km2, requires efficient systems
of data collection for rational management of its forest
resources. The present dissertation develops a quantitative method
for determining the biomass of tropical forest using satellite
imagery from TM-LANDSAT 5 and HRV-SPOT in an. area to be inundated
for hydroelectricity. The study determined the correlation of
biomass above-ground and tree measurements with spectral response
and elevation in four samples: Dense Forest on Dry Land -
Undulated Relief (samples 1 and 4), Dense Forest on Dry Land -
Flat Relief (sample 2), and Floodplain Forest (sample 3). The
forest samples were divided into three vertical levels for
analysis. In comparison with the other forest levels, the spectral
variables combined with the biomass variables did not permit the
quantification of the biomass in the highest levei of the forest.
Regression analysis identified the equations for quantifying
biomass. The proposed method is practical and gave significant
results using either image index or image fraction for both
TM-LANDSAT or HRV-SPOT data. Of the twelve models tested, a linear
model was which gave a significant relationship for the biomass in
the intermediate and low levels with spectral and elevation
variables. It is recommended that future studies determine the
most efficient model to quantify the biomass in the three levels
of the forest.",
committee = "Batista, Get{\'u}lio Teixeira (presidente) and Santos, Jo{\~a}o
Roberto dos (orientador) and Alves, Di{\'o}genes Salas and
Martinelli, Luiz Antonio",
copyholder = "SID/SCD",
englishtitle = "Estimation of above-ground phytomass in a tropical forest using
TM-LANDSAT 5 e HVR-SPOT 1 data",
label = "6559",
language = "pt",
pages = "146",
ibi = "6qtX3pFwXQZ3r59YD6/GP3nT",
url = "http://urlib.net/ibi/6qtX3pFwXQZ3r59YD6/GP3nT",
targetfile = "publicacao.pdf",
urlaccessdate = "2024, May 02"
}