274 resultados para geoestatística
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Geociências e Meio Ambiente - IGCE
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Pós-graduação em Geociências e Meio Ambiente - IGCE
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O objetivo do trabalho foi determinar o tamanho adequado de amostra para estimar o volume de fustes de espécies florestais de uma população de árvores a serem cortadas no sistema de manejo florestal da empresa Cikel Brasil Verde Madeiras - Pará. Utilizaram-se as metodologias da amostragem sistemática e do estimador geoestatístico da krigagem ordinária com simulação sequencial, respectivamente para a escolha das amostras e estimação dos volumes dos fustes das árvores. Os resultados mostraram que os métodos podem ser utilizados no cálculo dos volumes de fustes de árvores. Entretanto, o método da krigagem apresenta um efeito de suavização, tendo como conseqüência uma subestimação dos volumes calculados. Neste caso, um fator de correção foi aplicado para minimizar o efeito da suavização. A simulação sequencial indicativa apresentou resultados mais precisos em relação à krigagem, uma vez que tal método apresentou algumas vantagens, tal como a não exigência de amostras com distribuições normais e ausência de efeito de suavização, característico dos métodos de interpolação.
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Este artigo analisa a variação da precipitação na bacia hidrográfica Tocantins-Araguaia no período de duas décadas, tomando como base as estações pluviométricas do banco de dados HidroWeb, da Agência Nacional de Águas, nos anos de 1983, 1993 e 2003. As informações foram sistematizadas e tratadas a partir de métodos hidrológicos como método de contorno e interpolação por krigagem ordinária. O tratamento considerou a consistência dos dados das estações e os períodos de estudo. Os resultados demonstraram que o volume total de água precipitada anualmente não se alterou significativamente nos 20 anos estudados, ocorrendo, no entanto, uma significativa variação em sua distribuição espacial. Analisando-se as isoietas e o volume precipitado constatou-se que houve deslocamento da precipitação, no sentido Tocantins Baixo (TOB) aproximadamente de 10% do volume total precipitado. Tal deslocamento pode estar ligado a mudanças globais e/ou pode ser causado por atividades antrópicas ou fenômenos naturais regionais, cuja análise foge ao escopo deste trabalho.
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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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The use of geostatistical techniques allows detection of the existence of dependence and the spatial distribution of soil properties, thus constituting an important tool in the analysis and detailed description of the behavior of soil physical properties. The aim of the present study was to use geostatistics in assessment of physical properties in a Latossolo (Oxisol) dystrophic under native forest and pasture in the Amazon region of Manicore. Grids with of 70 x 70 m were established in native forest and pasture, and points were marked in these grids spaced at every 10 m, for a total of 64 points. These points were then georeferenced and in each one, soil samples (128) were collected at the depths of 0.00-0.20 and 0.40-0.60 m for a survey of their physical properties. These grids are parallel at a distance of 100 m from one another. The following determinations were made: texture, bulk density and particle density, macroporosity, microporosity, total porosity and aggregate stability in water. After tabulating the data, descriptive statistical analysis and geostatistical analysis were performed. The pasture had a slight variation in its physical properties in relation to native forest, with a high coefficient of variation and weak spatial dependence. The scaled semivariograms were able to satisfactorily reproduce the spatial behavior of the properties in the same pattern as the individual semivariograms, and the use of the parameter range of the semivariogram was efficient for determining the optimal sampling density for the environments under study. The geostatistical results indicate that the removal of native forest for establishing pasture altered the natural variability of the physical properties.
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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.
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The objective of this study was to analyze different intensities of soil sampling for accuracy in geostatistical analysis and interpolation maps for precision agriculture in the sugarcane area. Soil samples were collected at two regular grids at a depth of 0.00 to 0.20m for granulometric analysis (area 1) and soil fertility (area 2). We compared soil sampling intensities: 208, 105, 58 and 24 points in Area 1 and 206, 102 and 53 points in Area 2. The data were submitted to descriptive analysis and geostatistics. The variograms constructed with 105 points didn't differ from variograms with 208 points, which doesn't occur for 58 and 24 points. The increase of sampling interval and reducing the number of points promote greater error in kriging. Samples with more than 100 points per area did not result in significant improvements in the error of kriging, or differed in the amount of fertilizer applied to the field.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Classical statistical techniques which necessarily assume that all sampling units are random and independent were always used in the timber industry. Geostatistics considers that certain phenomena are characterized by spatial dependence: values of sampling units closer to each other tend to be more similar than values of sampling units farther away. This study aimed to characterize the spatial variability of the finishing (dyer) in the upper and lower surfaces of four edge glued panels by using geostatistical methods using geoR. Semivariograms were constructed for the analysis of spatial dependence. The spherical mathematical model was the best fit to the semivariograms generated, and was done the interpolation of the data (kriging) in samples where the distribution of dyer presents spatial dependence. In the bottom surfaces of two panels where the spatial dependence was detected geostatistical methods characterized a very large spatial variability due to the heterogeneous application of the finishing