Produtividade de soja estimada por modelo agrometeorológico num SIG

Os modelos agrometeorológicos integrados em Sistemas de Informação Geográfica - SIG são uma alternativa para simular e quantificar o efeito da variabilidade espacial e temporal do clima sobre a produtividade agrícola. O objetivo deste trabalho foi adaptar e integrar um modelo agrometeorológico num SIG para estimar a produtividade da soja [Glycine max (L.) Merr.]. Foram geradas estimativas de produtividade para 144 municípios do Estado do Paraná, responsáveis por 90% da produção de soja no Estado, em cinco anos-safra no período de 1996/1997 a 2000/2001. O modelo utiliza parâmetros agronômicos e dados meteorológicos para o cálculo da produtividade máxima, a qual é penalizada quando ocorre estresse hídrico. A análise da comparação entre as estimativas municipais obtidas pelo modelo e aquelas divulgadas pela Secretaria de Estado da Agricultura e do Abastecimento (SEAB) do Paraná foi feita através do teste "t" para pares de observação. No ano safra 1996/1997 o modelo superestimou a produtividade em 10,8% em relação à SEAB, o que pode ser atribuído à ocorrência de oídio, cujo efeito não é considerado no modelo. Nos anos safras de 1997/1998, 1998/1999 e 1999/2000 não foram identificadas diferenças (P >; 0,05) entre as estimativas do modelo e da SEAB. Em 2000/2001 a produtividade foi subestimada pelo modelo em 10,5%, sendo que as causas desta diferença precisam ser melhor investigadas. O modelo integrado no SIG mostrou ser uma ferramenta viável para acompanhar a cultura da soja ao longo da estação de crescimento, e estimar a produtividade em municípios do Estado do Paraná.Agrometeorological models interfaced with the Geographic Information System - GIS are an alternative to simulate and quantify the effect of weather spatial and temporal variability on crop yield. The objective of this work was to adapt and interface an agrometeorological model with a GIS to estimate soybean [Glycine max (L.) Merr.] yield. Yield estimates were generated for 144 municipalities in the State of Paraná, Brazil, responsible for 90% of the soybean production in the State, from 1996/1997 to 2000/2001. The model uses agronomical parameters and meteorological data to calculate maximum yield which will be penalized under drought stress. Comparative analyses between the yield estimated by the model and that reported by the Paraná State Department of Agriculture (SEAB) were performed using the "t" test for paired observations. For the 1996/1997 year the model overestimated yield by 10.8%, which may be attributed to the occurrence of fungal diseases not considered by the model. For 1997/1998, 1998/1999 and 1999/2000 no differences (P >; 0.05) were found between the yield estimated by the model and SEAB's data. For 2000/2001 the model underestimated yield by 10.5% and the cause for this difference needs further investigation. The model interfaced with a GIS is an useful tool to monitor soybean crop during growing season to estimate crop yield

Viabilidade de uso de imagens do Landsat em mapeamento de área cultivada com soja no Estado do Paraná

The aim of this work was to evaluate the feasibility of the use of Landsat imagery to map soybean crop areas in Paraná, Brazil, during crop years from 2000/2001 to 2006/2007. The analysis of the quick look images from the TM and ETM+ sensors was performed to select useful images to map soybean crop. The quick looks were classified according to the presence or absence of clouds and technical problems. It was verified that for none of the seven crop years it would have been possible to map soybean crop for the entire Paraná state, even for the three crop years during which both satellites Landsat 5 and 7 were operating simultaneously. The presence of clouds, detected through the optical sensors, should be considered for systematic mapping of summer crops in Brazil.O objetivo deste trabalho foi avaliar a viabilidade do uso de imagens do Landsat, para o mapeamento da área cultivada com soja, nas safras de 2000/2001 a 2006/2007, no Estado do Paraná. A análise dos "quick looks" das imagens dos sensores TM e ETM+ foi feita para selecionar as imagens úteis para o mapeamento da cultura da soja. Os "quick looks" foram classificados de acordo com a presença ou a ausência de nuvens e de problemas técnicos. Conforme os resultados, em nenhum dos sete anos teria sido possível mapear a área cultivada com soja, em todo o Estado, mesmo nos três anos-safra em que os satélites Landsat 5 e 7 operaram em conjunto. A presença de nuvens, detectada pelos sensores ópticos, deve ser levada em conta no mapeamento sistemático da área cultivada com culturas de verão, no Brasil

Avaliação de modelo agrometeorológico e imagens NOAA/AVHRR no acompanhamento e estimativa de produtividade de soja no Estado do Paraná

O presente trabalho tem por objetivo desenvolver um modelo para acompanhamento e estimativa da produtividade da cultura da soja (Glycine max L. Merril)em um sistema de informações geográficas (SIG), a partir de um modelo agrometeorológico pontual e imagens NOAA-AVHRR. A integração do modelo e da base de dados foi realizada através do aplicativo SPRING e os cálculos foram executados por meio do módulo de programação do SPRING, denominado LEGAL. A área de estudo foi o Estado do Paraná e as estimativas foram geradas, ao nível municipal, para os anos safra de 1996/97, 1997/98 e 1998/99. Mosaicos quinzenais de imagens NOAA-AVHRR, com resolução espacial de 8 x 8 km, transformados em imagens NDVI, foram utilizados como componente espectral no modelo agrometeorológico, visando estimar o índice de área foliar (IAF). O modelo desenvolvido utiliza parâmetros agronômicos e meteorológicos para cálculo da produtividade máxima ou potencial. Esta produtividade é então penalizada quando a demanda hídrica da cultura não é suprida adequadamente, gerando a produtividade real estimada. A análise da comparação desta estimativa com os valores de produtividade divulgados pela Secretaria de Agricultura e Abastecimento do Paraná (SEAB), ao nível municipal, foi feita através do teste "t" para pares de observação, e o resultado para cada ano safra foi: a) em 1996/97 o modelo subestimou a produtividade em relação à estimativa da SEAB em 59kg/ha (t=-2,91; alfa0,05); e em 1998/99 o modelo superestimou a produtividade em 192kg/ha (t=7,59; alfa0.05); and, in 1998/99 the model overestimated yield by 192 kg.ha^-1 (t=7.59; a<0.05). This demonstrates that the model estimated quite satisfactory the soybean yield and requires only minor adjustments. Through the penalization index, generated every 15 days, it was possible to monitor soybean crop grow and development conditions detecting relevant water deficits over the crop growing season in each year. The SPRING software and its LEGAL module performed satisfactory in both model integration and soybean yield calculations. The NOAA/AVHRR images did not performed satisfactory in the LAI estimation and, therefore, data from the literature were alternatively used to estimate this parameter in yield calculation.Number of Pages: 18

Remote Sensing Time Series to Evaluate Direct Land Use Change of Recent Expanded Sugarcane Crop in Brazil

The use of biofuels to mitigate global carbon emissions is highly dependent on direct and indirect land use changes (LUC). The direct LUC (dLUC) can be accurately evaluated using remote sensing images. In this work we evaluated the dLUC of about 4 million hectares of sugarcane expanded from 2005 to 2010 in the South-central region of Brazil. This region has a favorable climate for rain-fed sugarcane, a great potential for agriculture expansion without deforestation, and is currently responsible for almost 90% of Brazilian’s sugarcane production. An available thematic map of sugarcane along with MODIS and Landast images, acquired from 2000 to 2009, were used to evaluate the land use prior to the conversion to sugarcane. A systematic sampling procedure was adopted and the land use identification prior to sugarcane, for each sample, was performed using a web tool developed to visualize both the MODIS time series and the multitemporal Landsat images. Considering 2000 as reference year, it was observed that sugarcane expanded: 69.7% on pasture land; 25.0% on annual crops; 0.6% on forest; while 3.4% was sugarcane land under crop rotation. The results clearly show that the dLUC of recent sugarcane expansion has occurred on more than 99% of either pasture or agriculture land

Relação entre o fator de reflectância hemisférica e o fator de reflectância hemisférica bidirecional de folhas isoladas da Tibouchina granulosa cogn

This paper describes the Leaf hemispheric bidirectional reflectance factors (HBRFs)and the hemispheric reflectance factors (HRFs)of the Tibouchina granular cogn. (Quaresmeira)isolated leaves of were measured using a spectroradiometer that measures in the spectral range from 0.40 to 0.90 mm coupled with a LICOR integrating sphere. The purpose was to identify significant differences between HBRFs and HRFs of 10 isolated leaves from different portions. The results showed that were no significant differences between the hemispherical and bidirectional factors. However, the HBRFs varied between samples as a function os leaf portions wich offerts the shadows in the canopy and the leaf structure.Pages: 1461-146

Studies on the Rapid Expansion of Sugarcane for Ethanol Production in São Paulo State (Brazil) Using Landsat Data

This study’s overarching aim is to establish the areal extent and characteristics of the rapid sugarcane expansion and land use change in São Paulo state (Brazil) as a result of an increase in the demand for ethanol, using Landsat type remotely sensed data. In 2003 flex fuel automobiles started to enter the Brazilian consumer market causing a dramatic expansion of sugarcane areas from 2.57 million ha in 2003 to 4.45 million ha in 2008. Almost all the land use change, for the sugarcane expansion of crop year 2008/09, occurred on pasture and annual crop land, being equally distributed on each. It was also observed that during the 2008 harvest season, the burned sugarcane area was reduced to 50% of the total harvested area in response to a protocol that aims to cease sugarcane straw burning practice by 2014 for mechanized areas. This study indicates that remote sensing images have efficiently evaluated important characteristics of the sugarcane cultivation dynamic providing quantitative results that are relevant to the debate of sustainable ethanol production from sugarcane in Brazil

Avaliação temporal de padrões de fogo, uso e tipo de cobertura da terra

The burnings have been occurred because farmers use this practice on their land, and when forest areas are converted to crop or pasture areas. It usually occurs in the tropical region, during the dry season, because the vegetation has more risk to fire due to dry weather in this period, causing a great environmental impact. This mechanism implies in burning partially or totally the above and below ground biomass presented on the ground, with major implication for carbon emissions. In this study, we investigated and compared the temporal trend of fire activities on areas that have been deforested and subsequently used for intensive agriculture (sugarcane and soybean) and pastures. The study area encompasses four cities located in Mato Grosso State: Arenápolis, Denise, Nova Olímpia, and Santo Afonso. The proposed methodology was to use land use/land cover, deforestation, and hot pixels data. We analyzed the occurrence of fire considering the land cover type. The preliminary results allowed a good understanding of the processes of land use subsequent to the deforestation: Pasture presented more focus of fire at its location, and Agriculture showed the smallest number of hot pixels. This is an indicative that fire is more related with forest degradation process and pasture management activity.Pages: 6278-628