@PhDThesis{Silva:1985:MaFoVe,
author = "Silva, Dagoberto",
title = "Mapeamento das forma{\c{c}}{\~o}es vegetais e da
varia{\c{c}}{\~a}o da l{\^a}mina d'{\'a}gua em parte do Parque
Nacional do Pantanal Mato-Grossense e adjac{\^e}ncias,
atrav{\'e}s de t{\'e}cnicas de sensoriamento remoto",
school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
year = "1985",
address = "S{\~a}o Jos{\'e} dos Campos",
month = "1985-05-07",
note = "{4 mapas. escala: 1:40.000}",
keywords = "Pantanal Mato-grossense, sensoriamento remoto, processamento
digital, vegeta{\c{c}}{\~a}o, TM-LANDSAT, Pantanal
Matogrossense, remote sensing, digital processing, vegetation,
TM-LANDSAT.",
abstract = "Este estudo teve por objetivo principal mapear as
forma{\c{c}}{\~o}es vegetais e a varia{\c{c}}{\~a}o da
l{\^a}mina d'{\'a}gua em parte do Parque Nacional do Pantanal
Mato-grossense e adjac{\^e}ncias, atrav{\'e}s de t{\'e}cnicas
de sensoriamento remoto.Utilizaram-se fotografias a{\'e}reas
infravermelhas coloridas e dados digitais do MSS-LANDSAT.
Comparou-se o mapa de cobertura vegetal obtido atrav{\'e}s da
interpreta{\c{c}}{\~a}o das fotoqrafias a{\'e}reas com aqueles
obtidos atrav{\'e}s do processamento digital
(classifica{\c{c}}{\~a}o supervisionada e
n{\~a}o-supervisionada) de dados do MSS-LANDSAT. O uso das
fotografias a{\'e}reas possibilitou identificar as seguintes
unidades de vegeta{\c{c}}{\~a}o: Floresta Estacional
Semidecidual das Terras Baixas, Floresta Estacional Semidecidual
Aluvial, Vegeta{\c{c}}{\~a}o de Transi{\c{c}}{\~a}o e Campos
Inund{\'a}veis. No processamento digital de dados do MSS-LANDSAT,
a Floresta Estacional Semidecidual Aluvial e a
Vegeta{\c{c}}{\~a}o de Transi{\c{c}}{\~a}o apresentaram
respostas espectrais semelhantes, por isto formaram uma {\'u}nica
classe. A unidade Campos Inund{\'a}veis foi dividida em duas
subclasses, devido a diferentes conte{\'u}dos de unidade. A
classifica{\c{c}}{\~a}o supervisionada forneceu resultados mais
precisos do que a classifica{\c{c}}{\~a}o
n{\~a}o-supervisionada. A utiliza{\c{c}}{\~a}o do algoritmo
SLICER no canal 7 do MSS-LANDSAT permitiu mapear uma {\'a}rea de
l{\^a}mina d'{\'a}gua 33,9 vezes maior na {\'e}poca de cheias
do que na {\'e}poca de vazante. ABSTRACT: The main objective of
this study was to map the plant associations and the variation of
the water surface in part of the Pantanal Mato-grossense National
Park and its surroundings, using remote sensing techniques. Color
infrared aerial photographs and MSS-LANDSAT digital data were
used. The vegetation cover map obtained by the interpretation of
aerial photographs was compared with maps obtained by digital
processing (supervised and nonsupervised classification) of the
MSS-LANDSAT data. Using aerial photographic interpretation
techniques, the following vegetation units were identified:
Semideciduous Seasonal Forest of the Lowlands, Semideciduous
Seasonal Alluvial Forest, Vegetation of Tiansition and Seasonally
Flooded Grasslands. The digital processing of the MSS-LANDSAT data
indicqted that Semideciduous Seasonal Alluvial Forest and the
Vegetation of Transition had similar spectral responses. Due to
this spectral similarity these vegetation units were included in
one class. The Seasonally Flooded Grasslands unit was considered
as two subclasses, due to different moisture contents. The
supervised classification provided more accurate results than the
nonsupervised classification. The utilization of the SLICER
algorithm at the MSS-LANDSAT 7 band allowed mapping a water
surface 33,9 times bigger in the flooded season than in the dry
season.",
committee = "Batista, Get{\'u}lio Teixeira (presidente), and Kux, Hermann
(orientador), and Carneiro, Carlos Marx Ribeiro and Disperati,
Attilio Antonio and Almeida Filho, Raimundo de",
copyholder = "SID/SCD",
englishtitle = "Mapping of vegetation formations and variation of water extension
in part of the National Park Pantanal Matogrossense and adjacency,
using remote sensing techniques.",
label = "17",
language = "pt",
pages = "80",
ibi = "6qtX3pFwXQZ3r59YD6/GNnGc",
url = "http://urlib.net/ibi/6qtX3pFwXQZ3r59YD6/GNnGc",
targetfile = "publicacao.pdf",
urlaccessdate = "04 maio 2024"
}