Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

Araújo, Gleyce Kelly Dantas; Rocha, Jansle Vieira; Lamparelli, Rubens Augusto Camargo; Rocha, Agmon Moreira

doi:10.1590/s0100-69162011000400014

Cited by 17 publications

(12 citation statements)

References 8 publications

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“…As 23 Em razão da grande variabilidade de datas de semeadura nas diferentes regiões do estado (Araújo et al, 2011), utilizaram-se diversas imagens de EVI para gerar a imagem de mínimo EVI e a imagem de máximo EVI. Este procedimento foi operacionalizado por um sistema de extração de dados de imagens em linguagem de programação "interactive data language" (IDL) (Esquerdo et al, 2011 valores mínimos e máximos de EVI das culturas para cada uma das diferentes regiões do estado.…”

Section: Methodsunclassified

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Estimativa de áreas com culturas de verão no Paraná, por meio de imagens multitemporais EVI/Modis

Johann

Rocha

Duft

et al. 2012

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi estimar e mapear as áreas com as culturas de soja e milho, no Paraná, com uso de imagens multitemporais EVI/Modis. Foram avaliados os anos-safra de 2004/2005 a 2007/2008. Em razão da alta dinâmica temporal e da heterogeneidade de datas de semeadura das culturas no estado, foram utilizadas cenas que contemplavam as fases de pré-plantio e de desenvolvimento inicial das culturas, para gerar a imagem de mínimo EVI (IMIE), e cenas que consideravam o pico vegetativo das culturas, para gerar a imagem de máximo EVI (IMAE). Estas imagens foram utilizadas para gerar a composição colorida RGB (R, IMAE; GB, IMIE), o que permitiu a confecção de máscara das áreas com soja e milho. As estimativas das áreas de máscara por município foram comparadas com dados oficiais de produção agrícola municipal, tendo-se observado bons ajustes (R²>0,84, d>0,95, c>0,85) entre os dados. Para a avaliação da exatidão espacial das máscaras, imagens Landsat-5/TM e AWiFS/IRS foram usadas como referência para construção da matriz de erros. Os resultados obtidos são indicativos de que a metodologia proposta é altamente eficiente e pode ser utilizada para mapeamento dessas culturas.Termos para indexação: classificação de imagens, distribuição espacial de culturas, índice de vegetação, mapeamento, previsão de safras, sensoriamento remoto. Estimation of summer crop areas in the state of Paraná, Brazil, using multitemporal EVI/Modis imagesAbstract -The objective of this work was to estimate and map crop areas with soybean and corn in the state of Paraná, Brazil, using EVI/Modis images. The crop seasons from 2004/2005 to 2007/2008 were evaluated. Due to the high temporal dynamics and difference in sowing dates of the cultures within the state, scenes containing the pre-planting and initial crop development phases were used to obtain the minimum EVI image (IMIE), and scenes at the peak of the crop cycle were used to obtain the maximum EVI image (IMAE). These images were used to generate the RGB color composition (R, IMAE; GB, IMIE), which allowed for the creation of masks of the areas planted with soybean and corn. The estimation of masked areas by municipality was compared with the municipal agricultural production official data, and good fits (R²>0. 84, d>0.95, c>0.85) were observed between data. For spatial accuracy assessment, Landsat-5/TM and AWiFS/IRS images were used as references to build the error matrix. The obtained results indicate that the proposed methodology is highly efficient and may be used as a model for cropland mapping.

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Section: Methodsunclassified

“…Araújo et al (2011) observaram que as datas de semeadura variam entre o primeiro decêndio de outubro (região Oeste do Paraná) e o terceiro decêndio de dezembro (região Centro-Sul do Paraná). Isso é importante para que se possa definir a ocorrência do pico vegetativo das culturas; informação utilizada no mapeamento.…”

Section: Introductionunclassified

Estimativa de áreas com culturas de verão no Paraná, por meio de imagens multitemporais EVI/Modis

Johann

Rocha

Duft

et al. 2012

Pesq. agropec. bras.

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“…For these crop specific masks, we followed the methodology described by Araújo et al (2011), where multi-temporal color composites were created in RGB channels. The color composites were based on the soybean crop cycle in which the Red channel corresponds to the vegetative peak, and the Green and Blue channels correspond to the beginning of the crop cycle, thus, only the soybean crop was highlighted in the composite.…”

Section: Regression Modelmentioning

confidence: 99%

Correlation maps to assess soybean yield from EVI data in Paraná State, Brazil

Figueiredo

Brunsell

Higa

et al. 2016

Sci. agric. (Piracicaba, Braz.)

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Vegetation indices are widely used to monitor crop development and generally used as input data in models to forecast yield. The first step of this study consisted of using monthly . We compared the ability of forecasting crop yield based on correlation maps and crop specific masks. We ran a preliminary regression model to test its ability on yield estimation for four municipalities during the soybean growing season. A regression model was developed for both methodologies to forecast soybean crop yield using leave-one-out cross validation.The Root Mean Squared Error (RMSE) values in the implementation of the model ranged from 0.037 t ha −1 to 0.19 t ha −1 using correlation maps, while for crop specific masks, it varied from 0.21 t ha −1 to 0.35 t ha −1 . The model was able to explain 96 % to 98 % of the variance in estimated yield from correlation maps, while it was able to explain only 2 % to 67 % for crop specific mask approach. The results showed that the correlation maps could be used to predict crop yield more effectively than crop specific masks. In addition, this method can provide an indication of soybean yield prior to harvesting.

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“…In the state, methodologies based on the behavior of spectral-temporal crops have also been proposed for estimating soybean cultivated areas (SANTOS, 2010) and irrigated rice (KLERING, 2007). Multitemporal compositions of NDVI images from the SPOT Vegetation satellite (from French, Systeme Pour l'Observation de la Terre), subjected to supervised classification, were considered adequate for mapping crops in the state of Paraná (ARAÚJO et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

2013

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This study aimed to propose methods to identify croplands cultivated with winter cereals in the northern region of Rio Grande do Sul State, Brazil. Thus, temporal profiles of Normalized Difference Vegetation Index (NDVI) from MODIS sensor, from April to December of the 2000 to 2008, were analyzed. Firstly, crop masks were elaborated by subtracting the minimum NDVI image (April to May) from the maximum NDVI image (June to October). Then, an unsupervised classification of NDVI images was carried out (Isodata), considering the crop mask areas. According to the results, crop masks allowed the identification of pixels with greatest green biomass variation. This variation might be associated or not with winter cereals areas established to grain production. The unsupervised classification generated classes in which NDVI temporal profiles were associated with water bodies, pastures, winter cereals for grain production and for soil cover. Temporal NDVI profiles of the class winter cereals for grain production were in agree with crop patterns in the region (developmental stage, management standard and sowing dates). Therefore, unsupervised classification based on crop masks allows distinguishing and monitoring winter cereal crops, which were similar in terms of morphology and phenology.

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Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

Cited by 17 publications

References 8 publications

Estimativa de áreas com culturas de verão no Paraná, por meio de imagens multitemporais EVI/Modis

Estimativa de áreas com culturas de verão no Paraná, por meio de imagens multitemporais EVI/Modis

Correlation maps to assess soybean yield from EVI data in Paraná State, Brazil

Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

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