2012
DOI: 10.1590/s0100-204x2012000900012
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Cropland area estimates using Modis NDVI time series in the state of Mato Grosso, Brazil

Abstract: -The objective of this work was to evaluate a simple, semi-automated methodology for mapping cropland areas in the state of Mato Grosso, Brazil. A Fourier transform was applied over a time series of vegetation index products from the moderate resolution imaging spectroradiometer (Modis) sensor. This procedure allows for the evaluation of the amplitude of the periodic changes in vegetation response through time and the identification of areas with strong seasonal variation related to crop production. Annual cro… Show more

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Cited by 40 publications
(28 citation statements)
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“…Continuous time series NDVI or EVI data can provide detailed vegetation phenology information, thus they are often used for mapping cropland distribution [14,20,21,28]. However, in tropical and subtropical regions, it is impossible to collect continuous time series optical sensor data (e.g., MODIS) due to the cloud cover problem.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Continuous time series NDVI or EVI data can provide detailed vegetation phenology information, thus they are often used for mapping cropland distribution [14,20,21,28]. However, in tropical and subtropical regions, it is impossible to collect continuous time series optical sensor data (e.g., MODIS) due to the cloud cover problem.…”
Section: Discussionmentioning
confidence: 99%
“…Many previous "hard" classification methods such as thresholding approaches or classification algorithms are used to map cropland distribution [6,20,21,27], but the mixed pixel problem inherent in the coarse spatial resolution imagery (e.g., MODIS) often results in large uncertainty in cropland area statistics, resulting in poor area estimation and inaccurate spatial patterns. Although spectral mixture analysis presents an effective way to decompose the spectral reflectance of a pixel into different proportions, and has proven valuable in medium spatial resolution images such as Landsat or hyperspectral data [12,46,47], this approach is not so promising in coarse spatial resolution images such as MODIS due to the complex land cover composition and the difficulty in identifying suitable endmembers in large areas.…”
Section: Discussionmentioning
confidence: 99%
“…Um grupo de trabalhos -com foco em sensoriamento remoto e processamento de imagens -testa diferentes resoluções espaciais, temporais, espectrais e radiométricas. As imagens multiespectrais utilizadas são oriundas dos satélites ópticos Landsat ("land remote sensing satellite") (Antunes et al, 2012;Bolfe et al, 2012;Fernandes et al, 2012;Lu et al, 2012;Oliveira et al, 2012;Silva et al, 2012); Terra/Modis ("moderate resolution imaging spectroradiometer") (Andrade et al, 2012;Johann et al, 2012;Risso et al, 2012;Victoria et al, 2012); Spot ("système pour l'observation de la Terre") (Lu et al, 2012;Vicente et al, 2012); Ikonos e QuickBird (Lu et al, 2012) e imagens de radar como o Alos ("advanced land observing satellite") (Lu et al, 2012;Picoli et al, 2012). A Figura 2 ilustra como diferentes resoluções espaciais podem afetar a representação de feições conhecidas no meio rural.…”
Section: Pesquisa Desenvolvimento E Inovações Geoespaciais Para a Agunclassified
“…A Figura 2 ilustra como diferentes resoluções espaciais podem afetar a representação de feições conhecidas no meio rural. O uso e a cobertura da terra e os sistemas produtivos analisados nos trabalhos incluem culturas como: soja e milho (Antunes et al, 2012;Johann et al, 2012;Luiz et al, 2012;Risso et al, 2012;Santi et al, 2012;Victoria et al, 2012); cana-de-açúcar (Picoli et al, 2012;Vicente et al, 2012); pastagens (Grego et al, 2012;Lu et al, 2012); fruticultura ; silvicultura (Facco et al, 2012); e sistemas agroflorestais (Bolfe et al, 2012). Os artigos contribuem para o desenvolvimento de métodos inovadores, baseados em análises de respostas espectrais e variações temporais, por meio de métodos robustos de processamento e classificação de imagens que visam ao mapeamento do uso e da cobertura da terra.…”
Section: Pesquisa Desenvolvimento E Inovações Geoespaciais Para a Agunclassified
“…Another method for identifying the level of degradation is to monitor the vegetative growth in grasslands for a certain period of time and to compare the obtained data to a long-term vegetation index data series. Several authors have directed their research efforts towards the development of computational methodologies using GIS and remote sensing data time series to characterize pastures and other ground targets (Verbesselt et al, 2010;Li & Guo, 2012;Victoria et al, 2012;Xu et al, 2013). Applications focused on small or medium-sized areas require high-resolution images that are compatible with limited case studies.…”
Section: Introductionmentioning
confidence: 99%