368 resultados para KRIGING
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This study aim to evaluate the spatial variability of soil physical attributes in of Alfissol forest in Manicoré region, AM. The mapping of an agroforestry growing area of 70×70m was made using a regular grid sampling of 10 × 10m. In each grid, soil samples were collected at 0.0-0.2 and 0,40-0,60 m depth, with a total of 128 sample points. Physical analyses were made (texture, soil bulk and particles density, macro and microporosity, total porosity and aggregates stability in water). With the exception of DMG, DMP and class aggregates <1.00 mm had all the physical attributes spatial dependence structure ranging from moderate to weak. Values were above the range established in the mesh (12.00 to 45.56 m), enabling to make a basis for future studies in forest area. The physical attributes presented in kriging maps different spatial behavior, however there are relationships between these attributes shown by geostatistics proving that this is effective tool for studies in forest area.
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Rustic forages as the signal-grass are predominant in areas of Cerrado in extensive livestock systems that favor soil degradation. However, with time, not even these forages can have a good development in those areas. The objective of this study was to analyze the variability of plant and soil attributes; to define the linear and spatial correlations between signal-grass yield and the chemical attributes of the studied soil, and to evaluate, among the chemical attributes of the soil, which one that best explain the variability in this forage yield. The experiment was conducted in an area that had been under pasture for more than 30 years, belonging to UNESP - Ilha Solteira Campus, located in Selvíria - MS. A geostatistical grid was installed in an oxisol, for soil and plant data collection, with 121 sampling stations, consisted of eleven transections with 160 m width in the direction of the Cartesian axes. The dry mass yield of signal-grass was low, presenting high variation. The attributes MSr, N, PB, MO1, MO2, pHa1, pHa2, pHk1 and pHk2 did not vary at random. They presented data variability from low to high and followed clearly defined spatial patterns, ranging between 17.7-162.9 m. There was significant linear correlation at 1% between MSr and N leaf, and between MSr and PB. The cross semivariograms MSr=f(N) and MSr=f(PB) confirmed that the dry matter can be estimated from data of nitrogen leaf and crude protein content of this forage.
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The objective of this work was to evaluate the magnetic susceptibility efficiency for estimating the support capacity of areas for vinasse application. Two hundred forty-one soil samples were collected from a 380-ha area, on which soil chemical properties, clay content, and magnetic susceptibility were determined. Vinasse requirement was calculated for each sample. Data were subjected to descriptive statistical analysis, and regression models were developed between magnetic susceptibility and the other evaluated attributes. The analysis of data spatial dependence was performed using geostatistics. Kriging maps and cross variograms were built in order to investigate the spatial correlation between soil magnetic susceptibility and studied attributes. Based on the map of vinasse requirement, on the soil classes, and on the kriging map, calculations were done for average vinasse dose and average soil support capacity, weighted by the area. Magnetic susceptibility has significant linear spatial correlation with recommended vinasse doses and soil support capacity for the application of this effluent, and it can be used as a pedotransfer function for indirect quantification of soil support capacity.
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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)
Classificação fuzzy de vertentes por krigagem e TPS com agregação de regiões via diagrama de Voronoi
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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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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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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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Pós-graduação em Agronomia (Ciência do Solo) - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)