ABSTRACT. Cuiabá is located on the border of the Pantanal and Cerrado, in Mato Grosso State, which is recognized as one of the biggest agricultural producers of Brazil. The use of natural resources in a sustainable manner requires knowledge of the regional meteorological variables. Thus, the objective of this study was to RESUMO. Cuiabá está localizado na fronteira do Pantanal com o Cerrado, no Mato Grosso, queé reconhecido como um dos maiores produtores agrícolas do Brasil.A utilização dos recursos naturais de forma sustentável requer o conhecimento das variáveis meteorológicas em escala regional. Assim, o objetivo deste estudo foi caracterizar o padrão sazonal e interanual das variáveis meteorológicas em Cuiabá. Os dados meteorológicos de 1961 a 2011 foram fornecidos pelo Instituto Nacional de Meteorologia (INMET). Os resultados mostraram variações interanuais e sazonais de precipitação, radiação solar, temperatura e umidade relativa do ar e velocidade e direção do vento, estabelecendo duas principais estações distintas (chuvosa e seca). Em média, 89% da precipitação ocorreu na estação chuvosa. Os valores médios anuais de radiação diária global, temperatura do ar média, mínima e máxima e umidade relativa do ar foram 15,6 MJ m -2 y -1 , 27,9 • C, 23,0 • C, 30,0 • C e 71,6%, respectivamente. A temperatura máxima e a velocidade do vento não tiveram padrão sazonal. A velocidade média do vento diminuiu na direção NW e aumentou na direção S.Palavras-chave: variáveis meteorológicas, climatologia, ENOS.

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The acceleration of the anthropogenic activity has increased the atmospheric carbon concentration, which causes changes in regional climate. The Gross Primary Production (GPP) is an important variable in the global carbon cycle studies, since it defines the atmospheric carbon extraction rate from terrestrial ecosystems. The objective of this study was to estimate the GPP of the Amazon-Cerrado Transitional Forest by the Vegetation Photosynthesis Model (VPM) using local meteorological data and remote sensing data from MODIS and Landsat 5 TM reflectance from 2005 to 2008. The GPP was estimated using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) calculated by MODIS and Landsat 5 TM images. The GPP estimates were compared with measurements in a flux tower by eddy covariance. The GPP measured in the tower was consistent with higher values during the wet season and there was a trend to increase from 2005 to 2008. The GPP estimated by VPM showed the same increasing trend observed in measured GPP and had high correlation and Willmott's coefficient and low error metrics in comparison to measured GPP. These results indicated high potential of the Landsat 5 TM images to estimate the GPP of Amazon-Cerrado Transitional Forest by VPM.

Characterize accurately and accurate evapotranspiration (ET) on a global scale has been one of the major determinant challenges in terrestrial ecosystem studies, climate dynamics and hydrological cycle. The goal in this study was to evaluate methodologies presented in the literature proposing a new methodology and automation in the process of selection of hot and cold pixels to need the sensible heat flux H and ET. The study was conducted in four different locations in the state of Mato Grosso, Brazil. And two areas of forest and two formed by pasture. For the H automation process we used the proposed Bastiaanssen et al. (1998a), Gao et al. (2011), and other vegetation using different levels of the literature suggests. The automation of the selection of hot and cold pixels process was successful, showing correlations above 0.83 for the estimates of H and 0.75 for estimates of ET. The identification of hot and cold pixels using the methodology by similarity of neighboring pixels using the average of pixels showed the highest correlations to the H in the study areas. LAI had the best indicator in the automated identification of hot and cold pixels to estimate the daily evapotranspiration (ET24h).

Resumo A estimativa do índice de área foliar (IAF) em ecossistemas florestais é realizada

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Resumo O Pantanal é considerado a maior planície alagável do mundo, composto de 70% por Cerrado. Nas últimas décadas, devido ao avanço da agropecuária, grande parte deste bioma tem sido convertido em pastagens. O índice de área foliar (IAF) é uma importante medida da cobertura vegetal, pois, controla as trocas de massa e energia de uma superfície vegetada. Dessa forma o objetivo deste trabalho foi avaliar as estimativas de IAF de uma pastagem no norte do Pantanal Mato-Grossense pelo produto do MODIS (MOD15A2) e pelo modelo proposto por Allen et. al. (2002) Palavras-chave: microclima, atenuação da radiação, biomassa, mudança do uso do solo. Abstract The Pantanal is considered the largest floodplain in the world, composed of 70% for Savannah. In recent decades, due to the advancement of agriculture, much of this biome has been converted to pasture. The leaf area index (LAI) is an important measure of vegetation cover, therefore, controls the exchanges of mass and energy of a vegetated surface. Thus the objective of this study was to evaluate the estimates of LAI at a pasture in the northern Pantanal of Mato Grosso by the MODIS product (MOD15A2) and the model proposed by Allen et al. (2002) with LAI measurements obtained through the light interception and precipitation estimated by Tropical Rainfall Measuring Mission (TRMM). The study was conducted in a Brachiaria humidicola Allen et al. (2002) showed no correlation with rainfall, however, the LAI estimated by MODIS product was significant correlated with precipitation. The measured LAI did not correlate with the estimated by MODIS product, but correlated with the estimated by Allen et al. (2002). The LAI values measured in the pasture and estimated by Allen et al. (2002)

ABSTRACT. Cuiabá is located on the border of the Pantanal and Cerrado, in Mato Grosso State, which is recognized as one of the biggest agricultural producers of Brazil. The use... RESUMO. Cuiabá está localizado na fronteira do Pantanal e Cerrado, no Mato Grosso, que é reconhecido como um dos maiores produtores agrícolas do Brasil. A utilização dos...