Jurandir Zullo Junior

Impacto das mudanças climáticas no zoneamento agroclimático do café no Brasil

According to the last report of the Intergovernmental Panel on Climate Change (IPCC), the global temperature is supposed to increase 1°C to 5.8°C and the rainfall 15% in the Tropical area. This paper analyses the effect that these possible scenarios would have in the agroclimatic zoning of the arabic coffee (Coffea arabica L.) main plantation areas in Brazil. The results indicated a reduction of suitable areas greater than 95% in Goias, Minas Gerais and Sao Paulo and about 75% for Parana in the case of a temperature increase of 5.8 o C. These results presume that all the physiological characteristics of the crop will be the same for the varieties analyzed and that the ideal climatic condition for economic development is mean annual temperatures between 18 o C and 23 o C.

Impact assessment study of climate change on agricultural zoning

If mean temperature increases, in accordance with Intergovernmental Panel on Climate Change (IPCC) projections and adaptations and/or genetic modifications are not considered, suitable areas for farming corn (Zea mays) and coffee (Coffea arabica) will decrease in the state of Sao Paulo (Brazil). Further, increases in precipitation will not be enough to ameliorate the impacts associated with increases in mean temperatures. Suitability for grain production will decrease more rapidly in regions with sandy soils than in regions with clay or medium soils, as the temperature increases. The projected increase in mean temperature of up to 5.8°C would decrease the suitability for grain production drastically in spite of soil texture. Besides the reduction of suitable areas for coffee production, the projections suggest that changes will be more enhanced in the southeast of the state, especially in higher elevation regions, where farming practice, soils, and infrastructure are unsuitable for the economic production of coffee. In both cases, no compensatory increase in suitable areas for production is likely under current IPCC scenarios. Copyright

Comparação de dados dos satélites Ikonos-II e Landsat/ETM+ no estudo de áreas cafeeiras

The objective of this work was to assess the impact of the better spatial and radiometric resolutions of the Ikonos-II panchromatic image, for the identification of coffee (Coffea arabica) planting areas, in comparison with a Landsat/ETM+ image. The area of study is situated in the city of Pedregulho, State of Sao Paulo, Brazil, where 50 coffee fields were selected. Information about plants features, like height, age, spacing and variety were collected. Images allowed the identification of coffee areas with different field features, and the calibrated Ikonos-II image showed the best results. Considering the areas with similar field features, images from both satellites were not efficient in the coffee identification. The atmospheric and radiometric corrections applied on the Ikonos-II image did not improve the analyses results. More than half of the identified areas in the Ikonos-II image could be found in the Landsat/ETM+ image (68%). The significant correlation between Landsat/ETM+ band 4 and Ikonos-II panchromatic channel shows a link between both satellite images.

Estimation of biophysical parameters of coffee fields based on high-resolution satellite images.

Remote sensing data are each time more available and can be used to monitor the vegetal development of main agricultural crops, such as the Arabic coffee in Brazil, since that the relationship between spectral and agronomical data be well known. Therefore, this work had the main objective to assess the use of Quickbird satellite images to estimate biophysical parameters of coffee crop. Test area was composed by 25 coffee fields located between the cities of Ribeirao Corrente, Franca and Cristais Paulista (SP), Brazil, and the biophysical parameters used were row and between plants spacing, plant height, LAI, canopy diameter, percentage of vegetation cover, roughness and biomass. Spectral data were the reflectance of four bands of QUICKBIRD and values of four vegetations indexes (NDVI, GVI, SAVI and RVI) based on the same satellite. All these data were analyzed using linear and nonlinear regression methods to generate estimation models of biophysical parameters. The use of regression models based on nonlinear equations was more appropriate to estimate parameters such as the LAI and the percentage of biomass, important to indicate the productivity of coffee crop.

In-flight absolute calibration of the CBERS-2 CCD sensor data

Since the first images of the sensors on board of CBERS-2 (China-Brazil Earth Resources Satellite) satellite were made available by the National Institute for Space Research (INPE), users have asked information about the conversion of image digital numbers to physical data (radiance or reflectance). This paper describes the main steps that were carried out to calculate the in-flight absolute calibration coefficients for CBERS-2 CCD level 2 (radiometric and geometric correction) images considering the reflectance-based method. Remarks about the preliminary evaluation of these coefficients application are also presented.

Análise da transição entre dias secos e chuvosos por meio da cadeia de Markov de terceira ordem

O objetivo deste trabalho foi verificar se as ocorrencias de dias secos e chuvosos sao condicionalmente dependentes da sequencia dos tres dias secos e chuvosos anteriores, numa zona pluviometricamente homogenea, por meio da cadeia nao-homogenea de Markov de terceira ordem. Os resultados mostraram que as probabilidades diarias de transicao podem ser adequadamente estimadas, com base em dados agregados bimestralmente, seguidas de interpolacao por meio de funcoes sinusoidais. Alem disso, evidenciou-se que, naquela zona, as ocorrencias diarias de chuva sao condicionalmente dependentes da sequencia de dias secos e chuvosos nos tres dias anteriores. A cadeia nao-homogenea de Markov de terceira ordem e um importante instrumento para a analise da dependencia entre as sequencias de dias secos e chuvosos em determinadas regioes.

Ajuste dos simuladores de dados meteorológicos do modelo EPIC para diferentes locais do Estado de São Paulo

EPIC (Erosion Productivity Impact Calculator) model has been developed to simulate the effect of agricultural management strategies of water resources and soil productivity. In this study, the performance of meteorological data simulators were evaluated for six (Campinas, Jau, Manduri, Mococa, Pindorama and Ubatuba) localities in the State of Sao Paulo, Brazil, which include the Markov chain probabilities for the sequences of wet and dry days; the maximum air temperature model adjusted for wet days; and the solar radiation model also adjusted for wet days. From tests and adjustments of the models using the historical data for each locality, the best performance for the model of probabilities for dry days sequence has been found, taking into account the last wet day - P(W|D) in relation to the model of probabilities of two consecutive wet days sequence - P(W|W). The maximum air temperature and solar radiation models have presented good performance in tests after the adjustment for each locality. For all models, the best results have been obtained from the local adjustments, when compared to the original model conceived for EPIC. Model results for Ubatuba data were distinct from the other sites.

Influence of Precipitation in the Response of Spectral-phenology Model of Estimation of Sugar Cane Productivity

Introdução O Brasil é o principal produtor de cana-deaçúcar do mundo. Seus produtos são largamente utilizados na produção de açúcar, álcool combustível e, mais recentemente, biodiesel. A safra agrícola passou de 57,8 milhões de toneladas em 1990/91 para 509 milhões de toneladas estimadas para a safra 2012/2013, em todo país, representando um crescimento de 3,19% em relação ao total processado na última safra (2011/2012), que foi de 493,26 milhões de toneladas (Unica, 2012). Apesar da evolução e importância econômica e social dessa cadeia para o agronegócio do Brasil, existe ainda uma grande dificuldade em estimar com a precisão e a antecipação necessárias a safra das suas principais culturas o que justifica o estudo e a elaboração de novas metodologias, entre elas, as que englobem o sensoriamento remoto para essa finalidade. Revista Brasileira de Geografia Física V. 08 N. 03 (2015) 831-839.