931 resultados para Spatial variability.


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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O presente trabalho vem contribuir com o estudo do clima urbano na cidade de Belém durante a época menos chuvosa, juntamente com uma análise das questões da segregação social deste espaço urbano. Foi realizada uma campanha de coleta de dados meteorológicos durante alguns dias na época menos chuvosa da região para se calcular o índice de conforto térmico nos bairros e compara-los com as tipologias sociais características de cada bairro. Os resultados indicaram que as zonas da cidade menos confortáveis foram a Oeste e a Central, pois são mais urbanizadas e possuem menos vegetação que as demais áreas, enquanto que as zonas mais confortáveis foram a Leste e Noroeste, que possuem mais áreas vegetadas e predominância de edificações baixas. As análises indicaram que não existe um padrão bem definido entre as tipologias sociais dos bairros e suas condições de conforto térmico, pois as características da superfície são mais significativas para as mudanças microclimáticas locais.

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O experimento foi realizado na área experimental do Departamento de Engenharia Rural da Faculdade de Ciências Agronômicas – Unesp/Botucatu, Estado de São Paulo, em duas estufas dispostas em diferentes orientações geográficas, Leste/Oeste e Norte/Sul. A alface (Lactuva sativa L.) cv. Elisa foi cultivada em ambas estufas, sendo semeada em 05/05/99, transplantada em 29/05/99 e colhida em 31/06/99. Utilizou-se tensiômetros para monitorar o potencial de água no solo para realizar o manejo do sistema de irrigação por gotejamento. Microevaporímetros eqüidistantes de 3 m e colocados em 3 alturas, 0.50, 1.00 e 1.50 m, termohigrógrafos e tanques Classe “A” foram instalados nas duas estufas. Através de análise geoestatística, não se observou dependência espacial nem variabilidade espacial da evaporação nas duas estufas. Entretanto, a altura dos evaporímetros apresentou diferenças significativas: a evaporação à altura de 1.50 foi menor que nas outras duas.As médias de temperatura, umidade relativa e déficit de pressão de vapor do arnão diferiram estatisticamente entre as estufas e o ambiente externo. Os valores médios de evaporação de água no tanque Classe A instalado fora das estufas diferiram estatisticamente quando comparados com os instalados no interior das estufas, porém, entre as orientações não se constatou diferença significativa. Pôde-se verificar que não houve diferença significativa das características agronômicas da alface em ambas orientações estudadas. No entanto, houve diferença significativa para essas características entre os canteiros no interior das mesmas, havendo variância espacial para os dados de matéria fresca apenas na estufa N/S.

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Foi estudada a variabilidade espacial da umidade do solo num sistema de irrigação por gotejamento em uma estufa (5,0 x 20,0m) na Fazenda Experimental São Manuel, da Faculdade de Ciências Agronômicas, Universidade Estadual Paulista, Estado de São Paulo, Brasil. Foi estabelecida a malha de amostragem no espaçamento de 1,0 x 0,5m, acrescida de quatro adensamentos de 0,25m. Foram utilizados dados da umidade do solo em 178 pontos. A análise da dependência espacial foi obtida com o auxílio do Programa GS+. Foi construído o variograma experimental e definido o modelo de ajuste, de modo que a curva que melhor se ajustou aos pontos obtidos representasse a magnitude, alcance e intensidade da variabilidade espacial da variável estudada. A umidade do solo apresentou distribuição espacial anisotrópica. Para a direção 0°, pode-se notar uma dependência espacial caracterizada como alta, com o alcance de aproximadamente 3,30m, no sentido do comprimento da estufa. Entretanto, no sentido da largura da estufa, não foi possível ajustar modelos. Utilizando a representação gráfica da superfície, a área estudada apresentou um maior teor de água na parte inicial e menor na parte final das linhas de distribuição de água. A krigagem mostrou-se um bom interpolador para mapeamento da umidade do solo.

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Pós-graduação em Ciências Cartográficas - FCT

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The socioeconomic importance of sugar cane in Brazil is unquestionable because it is the raw material for the production of ethanol and sugar. The accurate spatial intervention in the management of the crop, resulting zones of soil management, increases productivity as well as its agricultural yields. The spatial and Person's correlations between sugarcane attributes and physico-chemical attributes of a Typic Tropustalf were studied in the growing season of 2009, in Suzanápolis, State of São Paulo, Brazil (20°28'10'' S lat.; 50°49'20'' W long.), in order to obtain the one that best correlates with agricultural productivity. Thus, the geostatistical grid with 120 sampling points was installed to soil and data collection in a plot of 14.6 ha with second crop sugarcane. Due to their substantial and excellent linear and spatial correlations with the productivity of the sugarcane, the population of plants and the organic matter content of the soil, by evidencing substantial correlations, linear and spatial, with the productivity of sugarcane, were indicators of management zones strongly attached to such productivity.

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The sugarcane crop plays an important role on Brazilian economy,, especially in the aspect related to alternative energy sources. Yield of ratoon cane (2nd cycle) was evaluated in relation to resistance to penetration, gravimetric moisture and organic matter in a Typic Tropustalf, in the municipality of Suzanápolis (SP), 20º28'10'' S and 50º49'20'' W, in the Brazilian cerrado, in 2009. The main purpose was to select, among the attributes surveyed, the one with the highest linear and spatial correlations that explains the variability of sugar cane yield. A geostatistical grid was installed in order to collect data from the soil as well from the plant, with 120 sampling points in an area of 14.53 ha. Organic matter correlated linearly and negatively with penetration resistance, indicating that the soil management practices that aim its increase in the soil profile can improve soil physical conditions, and consequently, the development and yield of sugarcane. Both gravimetric moisture (UG) and content of soil organic matter (OM) correlated directly, linearly (UG2 and MO1) and spatially (UG1 and MO1) with sugarcane yield, proving to be the best attributes, among the evaluated ones, to estimate and increase the sugarcane yield.

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The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.

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The knowledge on spatial distribution of soil properties by means of geostatistics is important as an indicator for a better soil use and management. This study aimed at evaluating the spatial distribution of soil chemical properties, in a forest and pasture area in Manicoré, Amazonas State, Brazil. Grids with 70.00 m x 70.00 m, with regular spacing of 10.00 m x 10.00 m, totaling 64 points, were established, and then soil samples were collected at the depths of 0.0-0.20 m and 0.40-0.60 m and had their chemical properties determined. Data were analyzed by using descriptive statistics and geostatistics, and the sampling density analysis was based on the coefficient of variation and semivariograms range. The mean and median values were adjusted to the closest values, indicating normal distribution, while the spherical, exponential and gaussian models were adjusted to the soil chemical properties. It was concluded that the geostatistics provided adequate information for understanding the spatial distribution. The forest area showed a higher spatial continuity and the pasture area a lower sampling density. The chemical properties showed differences in the spatial variability, while the range represented better the estimates for sampling density and spacing, in the forest and pasture area.

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Phosphorus is one of the limiting nutrients for sugarcane development in Brazilian soils. The spatial variability of this nutrient is great, defined by the properties that control its adsorption and desorption reactions. Spatial estimates to characterize this variability are based on geostatistical interpolation. However, inherent uncertainties in the procedure of these estimates are related to the variability structure of the property under study and the sample configuration of the area. Thus, the assessment of the uncertainty of estimates associated with the spatial distribution of available P (Plabile) is decisive to optimize the use of phosphate fertilizers. The purpose of this study was to evaluate the performance of sequential Gaussian simulation (sGs) and ordinary kriging (OK) in the modeling of uncertainty in available P estimates. A sampling grid with 626 points was established in a 200-ha experimental sugarcane field in Tabapuã, São Paulo State. The sGs algorithm generated 200 realizations. The sGs realizations reproduced the statistics and the distribution of the sample data. The G statistic (0.81) indicated good agreement between the values of simulated and observed fractions. The sGs realizations preserved the spatial variability of Plabile without the smoothing effect of the OK map. The accuracy in the reproduction of the variogram of the sample data obtained by the sGs realizations was on average 240 times higher than that obtained by OK. The uncertainty map, obtained by OK, showed less variation in the study area than that obtained by sGs. Thus, the evaluation of uncertainties by sGs was more informative and can be used to define and delimit specific management areas more precisely.