2015
DOI: 10.3390/rs70912160
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Comparative Analysis of MODIS Time-Series Classification Using Support Vector Machines and Methods Based upon Distance and Similarity Measures in the Brazilian Cerrado-Caatinga Boundary

Abstract: Abstract:We have mapped the primary native and exotic vegetation that occurs in the Cerrado-Caatinga transition zone in Central Brazil using MODIS-NDVI time series (product MOD09Q1) data over a two-year period (2011)(2012)(2013). Our methodology consists of the following steps: (a) the development of a three-dimensional cube composed of the NDVI-MODIS time series; (b) the removal of noise; (c) the selection of reference temporal curves and classification using similarity and distance measures; and (d) classifi… Show more

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Cited by 40 publications
(27 citation statements)
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“…The Savitzky-Golay filter [53], available in Timesat software [54], was used to reduce noise interference. Besides being widely used in studies to denoise time series of vegetation indices [36,[55][56][57], this filter is the one that best adapts in different types of surface, among those evaluated by Geng et al [58]. This filter performs per pixel local polynomial regression to noise removal while retaining the waveform-peak [53], preserving natural seasonality or persistent changes in NDVI.…”
Section: Modis Time Seriesmentioning
confidence: 99%
“…The Savitzky-Golay filter [53], available in Timesat software [54], was used to reduce noise interference. Besides being widely used in studies to denoise time series of vegetation indices [36,[55][56][57], this filter is the one that best adapts in different types of surface, among those evaluated by Geng et al [58]. This filter performs per pixel local polynomial regression to noise removal while retaining the waveform-peak [53], preserving natural seasonality or persistent changes in NDVI.…”
Section: Modis Time Seriesmentioning
confidence: 99%
“…An additional step is the fitting of models to the time series and using either the model parameters for classification directly [28], or deriving statistical metrics and phenological parameters such as start-and end of season from the models [11,22,29]. Other methods compare and cluster time series patterns using similarity measures, e.g., Euclidian distances, Fourier based similarities [20,30], or dynamic time warping [30,31]. Similar to [28], we used seasonal model parameters as metrics and descriptive statistics.…”
Section: Time Series Metricsmentioning
confidence: 99%
“…OOB uses n-bootstrap datasets, leaving out one observation at a time for prediction. This approach has been shown to be comparable to error estimation from independent test data [20,21]. We compared the outcome of this use case with four recent global LC maps: (a) Land Cover-CCI; (b) Globeland30; (c) MODIS 2010; and (d) Globcover-2009, along with (e) a regression kriging based integrated LC map of (a)-(d) presented in [5].…”
mentioning
confidence: 99%
“…A filtragem tem o objetivo de reduzir os ruídos e construir uma série de alta qualidade que preserve as informações originais, já as composições temporais tem o objetivo de selecionar a partir de uma série restrita de dias, o pixel da série com melhor observação definida pelo usuário, o agrupamento dos melhores pixels dentro da série de dias selecionada originará uma nova imagem (GU et al, 2009). A filtragem da série temporal tem sido realizada a partir de diferentes metodologias, dentre elas os filtros de Savitzky e Golay (1964) e Mediana (ATAMAN et al, 1981) já foram testados com sucesso em biomas brasileiros (ABADE et al, 2015;CARVALHO JÚNIOR et al, 2012). com maior incidência de queimadas.…”
Section: Monitoramento De Queimadas Por Imagens Orbitaisunclassified
“…Assim, o método S-G utiliza uma janela móvel com valores ponderados, cujos pesos são provenientes de um polinômio de grau definido pelo usuário Chen et al (2004). adequou o método para o método S-G para o tratamento de séries temporais MODIS, sendo amplamente utilizado(ABADE et al, 2015)…”
unclassified