@Article{XaudEpip:2014:DiUsCo,
author = "Xaud, Maristela Ramalho and Epiphanio, Jos{\'e} Carlos Neves",
affiliation = "{Empresa Brasileira de Pesquisa Agropecu{\'a}ria – Embrapa
Roraima} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Din{\^a}mica do uso e cobertura da terra no sudeste de Roraima
utilizando t{\'e}cnicas de detec{\c{c}}{\~a}o de
mudan{\c{c}}as / Land use and land cover dynamics in the
southeastern Roraima using change detection techniques",
journal = "Acta Amazonica",
year = "2014",
volume = "44",
number = "1",
pages = "107--120",
month = "Mar.",
keywords = "uso da terra, detec{\c{c}}{\~a}o de mudan{\c{c}}a,
imagens-fra{\c{c}}{\~a}o, sensoriamento remoto, Amaz{\^o}nia,
land use, change detection, fraction images, remote sensing,
Amazon.",
abstract = "A ocupa{\c{c}}{\~a}o e consolida{\c{c}}{\~a}o do
territ{\'o}rio na Amaz{\^o}nia apresentam diferentes
caracter{\'{\i}}sticas relacionadas {\`a} din{\^a}mica das
convers{\~o}es de uso e cobertura da terra, que podem ser
analisadas utilizando imagens orbitais de sensoriamento remoto. O
objetivo do presente trabalho foi avaliar os produtos de
detec{\c{c}}{\~a}o de mudan{\c{c}}as gerados por an{\'a}lise
de vetor de mudan{\c{c}}a (AVM) e subtra{\c{c}}{\~a}o de
imagens, a partir de imagens-fra{\c{c}}{\~a}o derivadas das
imagens {\'o}pticas TM/Landsat, para o estudo das convers{\~o}es
de uso e cobertura da terra presentes em {\'a}rea de
coloniza{\c{c}}{\~a}o agr{\'{\i}}cola na regi{\~a}o sudeste
de Roraima. Analisaram-se as imagens de mudan{\c{c}}a
provenientes da aplica{\c{c}}{\~a}o do AVM (magnitude, alfa e
beta) e da subtra{\c{c}}{\~a}o das imagens-fra{\c{c}}{\~a}o
(solo, sombra e vegeta{\c{c}}{\~a}o) quanto {\`a} sua
capacidade de identificar e discriminar as convers{\~o}es
existentes, de acordo com levantamento de campo. Foram testados
dois algoritmos de classifica{\c{c}}{\~a}o de imagens do tipo
supervisionado, Bhattacharyya e Support Vector Machine. Foram
feitos agrupamentos para otimizar a identifica{\c{c}}{\~a}o das
convers{\~o}es nas classifica{\c{c}}{\~o}es testadas. Houve
melhor desempenho do classificador por regi{\~o}es Bhattacharyya
na discrimina{\c{c}}{\~a}o das convers{\~o}es. A
utiliza{\c{c}}{\~a}o das imagens-diferen{\c{c}}a das
fra{\c{c}}{\~o}es como informa{\c{c}}{\~a}o de entrada para o
classificador apresentou qualidade de classifica{\c{c}}{\~a}o
muito boa ou excelente, sendo superior {\`a}s
classifica{\c{c}}{\~o}es utilizando os produtos AVM,
isoladamente ou em conjunto com as imagens-diferen{\c{c}}a.
ABSTRACT: Territory occupation and consolidation in the Amazon
region have some specific characteristics related to the dynamics
of land use and land cover conversions, which can be analyzed
using orbital remote sensing images. The aim of this study was to
evaluate change detection products generated by change vector
analysis (AVM) and image subtraction techniques derived from
linear spectral mixing modeling (MLME), applied to Thematic
Mapper/Landsat optical images, to study land use and land cover
conversions occurring in agricultural settlement areas in the
southeastern region of Roraima, Brazil. We analyzed change images
derived from application of AVM (magnitude, alpha and beta) and
subtraction of fraction images (soil, vegetation and shade), for
their ability to identify and discriminate the existing
conversions. An extensive field work was used as a guide to define
the classes. Exploratory analyses of class behaviors were made and
two supervised algorithms for image classification - Bhattacharyya
and Support Vector Machine - were tested. By grouping (clumping
classes), we sought to optimize conversion identification in the
classification products. The results indicated better
Bhattacharyya region classifier performance of conversion
discrimination. The use of MLME fractions difference images as
input into the classifier resulted a very good or excellent
classification quality, which was better in comparison with
products using AVM images, either in isolation or in conjunction
with MLME difference images.",
doi = "10.1590/S0044-59672014000100011",
url = "http://dx.doi.org/10.1590/S0044-59672014000100011",
issn = "0044-5967",
label = "isi 2014-05 XaudNeve:2014:LaUsLa",
language = "pt",
targetfile = "11.pdf",
urlaccessdate = "03 maio 2024"
}