Search

During the studied time window, between 2003 and 2010, there was an important increase of land use conversion into new soybean areas (first-time-use) in Mato Grosso state (MT) in Brazil. Uncertainties of future scenario of Brazilian agriculture and increase in the frequency of extreme events, such as the occurrence of high temperatures, is highly likely to produce yield loss on summer crops. The MT is the largest producer of soybeans and accounted for 28.2% of the national production in 2013. The objective of this study was to investigated specific characterization of land surface temperature distribution over the soybean crop fields canopies (canopy-LST) due to massive land use conversion into new soybean areas and its impacts on yield. Satellite imagery data from Aqua and Terra/MODIS sensors (Moderate Resolution Imaging Spectroradiometer) were compared to official agricultural statistics covering eight densely cultivated regions in the studied period. Results show that within the period from flowering to grain filling canopy-LST exhibits a non-negligible relation to yield. It is expected an additional loss of 4.9% on soybean yield for each 1oC of canopy-LST above the obtained optimal level of canopy-LST with 28.4oC, associated to the higher yield averages. The difference between overall average of canopy-LST and air temperature was found 4.2 oC.

The agricultural dynamics of soybean expansion have long been recognized as a major driver of excessive land cover change on the southwestern border of the Brazilian Amazon. The hypothesis that the soybean market exerts an influence on land use was investigated by the association between economic indicators and soybean crop dynamics in the state of Mato Grosso (western Brazil). We integrated a historical series of satellite data of soybean cropland expansion and the two main economic variables (selling prices and production costs) for soybean in Mato Grosso. We focused on the relation between profit (the difference between the average soybean price and production costs) and land-use transition to soybean from 2001 to 2013. The spatially explicit analysis showed that the overall accuracy between the resulting first-time use and the most recent soybean crop area in 2013 was 96.75%, with a Kappa index of 0.63. However, dissimilar values found between Omission and Commission indicators suggest that most of the expanded areas prior to 2013 (5.57 million ha) were under a high dynamical range of land uses. Although there is no direct relation between either the deforestation rate or expansion trends (first-time-use rate) and profit, the results strongly suggest (R2=0.81) that profit exerts a direct and non-negligible influence on the evolution of consolidated land use for soybean in Mato Grosso State. RESUMO A dinâmica agrícola relacionada à expansão da soja tem sido reconhecida como um dos principais fatores da excessiva conversão da cobertura do solo no Estado de Mato Grosso, no sudoeste da Amazônia brasileira. A hipótese de que o mercado de soja exerce influência no uso do solo, foi investigada pela associação de indicadores econômicos com a dinâmica da cultura de soja no Mato Grosso. Integramos séries históricas de dados de satélite para expansão da área de cultivo de soja e de suas duas principais variáveis econômicas associadas (preço de venda e custo de produção). Enfocamos a relação entre lucro (a diferença entre as médias do preço da soja e do custo de produção) e a conversão do uso do solo para soja de 2001 a 2013. A análise espacial explícita revelou que a precisão global na comparação entre o mapa resultante de first-time-use de cultivo de soja em 2013 foi de 96,75%, com índice Kappa de 0,63. Entretanto, a divergência obtida entre os indicadores de erro por comissão e omissão, sugerem que a maior parte da expansão da soja ocorrida antes de 2013 (5,57 milhões de ha) esteve sob influência de uma intensa dinâmica de uso do solo. Embora seja claro não haver relação direta entre a taxa de desmatamento ou tendências de expansão (taxa de uso pela primeira vez) e o lucro, os resultados sugerem fortemente (R2=0,81) que o lucro exerce influência direta e não-negligenciável na evolução do uso do solo consolidado com soja no estado de Mato Grosso.

The objective of this work was to evaluate the reliability of the physiological meaning of the enhanced vegetation index (EVI) data for the development of a remote sensing-based procedure to estimate soybean production prior to crop harvest. Time-series data from the moderate resolution imaging spectroradiometer (Modis) were applied to investigate the relationship between local yield fluctuations of soybean and the prevailing physically-driven conditions in the state of Mato Grosso, located in the south of the Brazilian Amazon. The developed methodology was based on the coupled model (CM). The CM provides production estimates for early January, using images from the maximum crop development period. Production estimates were validated at three different spatial scales: state, municipality, and local. At the state and municipality levels, the results obtained from the CM were compared with official agricultural statistics from Instituto Brasileiro de Geografia e Estatística and Companhia Nacional de Abastecimento, from 2001 to 2011. The coefficients of determination ranged from 0.91 to 0.98, with overall result of R2=0.96 (p≤0.01), indicating that the model adheres to official statistics. At the local level, spatially distributed data were compared with production data from 422 crop fields. The coefficient of determination (R2=0.87) confirmed the reliability of the EVI for its applicability on remote sensing-based models for soybean production forecast.

Neste estudo o objetivo foi analisar, em nivel regional, a relacao entre efeito da ocorrencia de temperaturas elevadas associada a variabilidade da produtividade da soja no Estado do Rio Grande do Sul. O estudo cobre as safras entre o periodo de 2000 a 2011. Para a analise da temperatura do dossel, em area agricola, foram utilizados dados da LST (Land Surface Temperature) do sensor MODIS (Moderate-Resolution Imaging Spectroradiometer) a bordo do satelite Aqua. O metodo de krigagem ordinaria foi utilizado para suavizar dados da distribuicao espacial da producao da soja em nivel municipal, provenientes do IBGE, e precipitacao acumulada por safra, no periodo entre outubro e fevereiro, provenientes de 33 estacoes pluviometricas obtidos da FEPAGRO. A media geral da LST no dossel, ocorrida no periodo em todo o Estado, foi 31,9oC com desvio padrao 2,43oC. A media geral da produtividade suavizada foi 2030 kg ha-1 com desvio padrao 320 kg ha-1. Foi observada a ocorrencia da LST no dossel acima da media, em fevereiro, associada com queda severa na produtividade, tendo R2=0,64 e RMSD=19,9%. Tambem foi observado que periodos de queda na produtividade, mas com precipitacao regional acima da media, estao relacionados a LST no dossel acima da media. Os resultados indicaram que mais estudos sobre os efeitos da LST na produtividade podem trazer importantes contribuicoes na compreensao da vulnerabilidade do ciclo de desenvolvimento da cultura da soja assim como dos processos agricolas adaptativos em cenario de mudancas climaticas. 800x600 Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif";} A B S T R A C T In this study we analyze the relationship between the occurrence of high temperatures and the variability of soybean yield. The study covers the crop years from 2003 to 2012 in Rio Grande do Sul State. For the analysis of temperature over the vegetation canopy in agricultural areas, we used a LST (Land Surface Temperature ) time series, product MYD11A2 collection -5 of sensor MODIS ( Moderate -Resolution Imaging Spectroradiometer ) on board the Aqua satellite. Crop area mapping, identification and monitoring of development during phenological stages were performed with application of EVI (Enhanced Vegetation Index) data series product MOD13Q1, collection-5 of MODIS on board the Terra satellite. Ordinary kriging methodology was used for data smoothing of spatial distribution of soybean yield at municipal level, obtained from IBGE; accumulated rainfall, between October and February, came from data of 15 meteorological stations from FEPAGRO (Fundacao Estadual de Pesquisa Agropecuaria). The overall average LST over crop canopy in the studied period was 31.9 oC with standard deviation 2.1 °C. The overall average of the smoothed yield was 2003 kg ha -1 with standard deviation 309 kg ha -1 . The average of cumulative rainfall was 775 mm with a standard deviation of 38 mm. At the state level analysis, results indicate that severe decreases in productivity are coupled events effect of canopy-LST above average during February (DOY 033), associated to below average rainfall by means an inverse nonlinear relationship with R 2 = 0.73 and RMSD = 17,8%. Keywords : Remote sensing; Vulnerability; Agriculture; Soybean; Temperature; Drought

Estimations of crop area were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from moderate resolution imaging spectroradiometer (MODIS) images. Evaluation of the ability of the MODIS crop detection algorithm (MCDA) to estimate soybean crop areas was performed for fields in the Mato Grosso state, Brazil. Using the MCDA approach, soybean crop area estimations can be provided for December (first forecast) using images from the sowing period and for February (second forecast) using images from the sowing period and the maximum crop development period. The area estimates were compared to official agricultural statistics from the Brazilian Institute of Geography and Statistics (IBGE) and from the National Company of Food Supply (CONAB) at different crop levels from 2000/2001 to 2010/2011. At the municipality level, the estimates were highly correlated, withR2=0.97and RMSD = 13,142 ha. The MCDA was validated using field campaign data from the 2006/2007 crop year. The overall map accuracy was 88.25%, and the Kappa Index of Agreement was 0.765. By using pre-defined parameters, MCDA is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the Mato Grosso state.

An accurate estimation of soybean crop areas while the plants are still in the field is highly necessary for reliable calculation of real crop parameters as to yield, production and other data important to decision-making policies related to government planning. An algorithm for soybean classification over the Rio Grande do Sul State, Brazil, was developed as an objective, automated tool. It is based on reflectance from medium spatial resolution images. The classification method was called the RCDA (Reflectance-based Crop Detection Algorithm), which operates through a mathematical combination of multi-temporal optical reflectance data obtained from Landsat-5 TM images. A set of 39 municipalities was analyzed for eight crop years between 1996/1997 and 2009/2010. RCDA estimates were compared to the official estimates of the Brazilian Institute of Geography and Statistics (IBGE) for soybean area at a municipal level. Coefficients R2 were between 0.81 and 0.98, indicating good agreement of the estimates. The RCDA was also compared to a soybean crop map derived from Landsat images for the 2000/2001 crop year, the overall map accuracy was 91.91% and the Kappa Index of Agreement was 0.76. Due to the calculation chain and pre-defined parameters, RCDA is a timesaving procedure and is less subjected to analyst skills for image interpretation. Thus, the RCDA was considered advantageous to provide thematic soybean maps at local and regional scales.

O objetivo deste trabalho foi avaliar a adequação do uso do sensor AVHRR/NOAA (Advanced Very High Resolution Radiometer/National Oceanic and Atmospheric Administration) para mapeamento da temperatura da superfície terrestre (TST) no Estado do Rio Grande do Sul, por meio da comparação entre três algoritmos clássicos. Foram comparados os métodos de Becker & Li, Sobrino et al. e Kerr et al. para estimativa das TST mínimas, utilizando imagens noturnas e logo após o amanhecer. Os dados de emissividade e TST foram obtidos por meio de combinações matemáticas da radiação detectada nas faixas do visível, infravermelho próximo e termal do sensor AVHRR/NOAA. O sensor AVHRR é adequado para o mapeamento de TST para as condições do tipo de cobertura do solo que predominam no Rio Grande do Sul, visto que a TST estimada pelos três métodos testados foi próxima à temperatura do ar medida nos locais selecionados. O método de Sobrino et al. foi o mais adequado. The objective of this work was to evaluate the suitable use of AVHRR/NOAA (Advanced Very High Resolution Radiometer/National Oceanic and Atmospheric Administration) on land surface temperature (LST) mapping in Rio Grande do Sul State by means of the comparison of three classic algorithms. The methods of Becker & Li, Sobrino et al. and Kerr et al. were compared for the minimum LST estimation, using nocturnal and predawn images. Both emissivity and LST data were obtained by means of mathematical combinations of the visible, near-infrared and thermal detected radiation of the AVHRR/NOAA sensor. The AVHRR sensor is suitable for LST mapping for the overall conditions of soil coverage in Rio Grande do Sul, once the estimated LST, by the three tested methods, was close to the measured air temperature at the selected locations. Sobrino et al. was the most adequate method.

A search is made for indicators of the presence of phytoplankton, using satellite images of the Pacific (Central Chile) and Atlantic (South Brazil). AVHRR/NOAA-16 and -17 visible (1 and 2) and thermal (4 and 5) channels were used to perform a detection test, respectively, the Suspended Particulate Matter (SPM) and the Sea Surface Temperature (SST). In Brazilian waters, a positive correlation is found between SST and SPM's reflectance. This is interpreted as due to phytoplankton being more abundant in colder waters, where nutrients availability are higher because CO2 dissolution rates, thus being a favorable environment for phytoplankton contents, which when mixed with SPM, tends to reduce the total water reflectance, since organic matter causes absorption at red wavelengths. A comparison is made with results for colder Pacific, where an opposite trend is found. It is noted that the Pacific shelf, off Chile, is narrower than the Atlantic's off Brazil, leading to circulation processes, which have a different influence on particulate matter contents. It's also concluded that NOAA data is suitable for these studies, despite the fact its spectral resolution is poorer comparing to specialized ocean studies satellites, a disadvantage compensed by its wider spectral and radiometric range and higher imaging frequency