59 resultados para Variograms


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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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O presente trabalho tem por objetivo avaliar a distribuição espacial, por geoestatística, da produção de água gerada pelo modelo hidrológico matemático SWAT 2009 (Soil and Water Assessment Tool, versão 2009), da parte inicial da bacia hidrográfica do Rio Pardo – SP. Foi utilizado um Sistema de Informação Geográfica (SIG) associado a uma interface com o modelo SWAT para a confecção do banco de dados. Para isto, as informações de entrada necessárias para avaliar a produção de lâmina de água (mm), que infiltrou e armazenou em cada sub-bacia gerada pelo SWAT, referem-se a dados tabulares climáticos e de parâmetros físicos e químicos de solo e a planos de informações como: o Modelo Numérico do Terreno (MNT), Mapa de Uso do Solo e Mapa de Solos. A amostragem geoestatística foi representada por uma malha irregular georreferenciada com 43 pontos localizados na parte central de cada sub-bacia representando a quantidade de água produzida. A análise geoestatística foi realizada pela construção dos variogramas e posteriormente a confecção dos mapas interpolados por krigagem. Do resultado obtido observou-se que a produção de água apresentou dependência espacial e que esta ocorreu de forma homogênea, tanto para os maiores como para os menores valores de produção de água encontrados na bacia.

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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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Soil CO2 emission (F-CO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere. F-CO2 varies in time and space depending on environmental conditions, including the management of the agricultural area. The aim of this study was to investigate the spatial variability structure of F-CO2 and soil attributes in a mechanically harvested sugarcane area (green harvest) using fractal dimension (D-F) derived from isotropic variograms at different scales (fractograms). F-CO2 showed an overall average of 1.51 mu mol CO2 m(-2) s(-1) and correlated significantly (P < 0.05) with soil physical attributes, such as soil bulk density, air-filled pore space, macroporosity and microporosity. Topologically significant DF values were obtained from the characterization of F-CO2 at medium and large scales (above 20 m), with values of 2.92 and 2.90, respectively. The variations in D-F with scales indicate that the spatial variability structure of F-CO2 was similar to that observed for soil temperature and total pore volume and was the inverse of that observed for other soil attributes, such as soil moisture, soil bulk density, microporosity, air-filled pore space, silt and clay content, pH, available phosphorus and the sum of bases. Thus, the spatial variability structure of F-CO2 presented a significant relationship with the spatial variability structure for most soil attributes, indicating the possibility of using fractograms as a tool to better describe the spatial dependence of variables along the scale. (C) 2014 Elsevier B.V. All rights reserved.

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Pós-graduação em Agronomia (Ciência do Solo) - FCAV

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Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA

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Climatic factors directly influence growth and productivity of plants inside greenhouses, where temperature can be considered one of the major parameter in this context. Thus, the aim of this research was to develop a low cost device for thermal sensing and data acquisition, and use it in data collection and analysis of spatial variability of temperature inside a greenhouse with tropical climate. The developed equipment for thermal measurements showed a high degree of accuracy and fast responses in measurements, proving its efficiency. The data analysis interpretations were made from the elaborations of variograms and of tridimensional maps generated by a geostatistical software. The processed data analysis presented that a greenhouse without thermal control has spatial variations of air temperature, both in the sampled horizontals layers as in the three analyzed vertical columns, presenting variations of up to 3.6 ºC in certain times.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The objective of this research was to estimate the productivity (PRODUT) in sc/ha of coffee conilon through the technique of cokriging, using as covariate the production of humid coffee (PROD) in kg and compare the results with estimates obtained by kriging ordinary. The study was conducted in a commercial area of conilon coffee, Coffea canephora Pierre var. conilon, located in São Mateus Municipality, Espirito Santo State. For the field work was sampled the humid coffee production in a sampling grid irregular of 18.5 ha, 87 sampling points in the total. We also determined the production of dry coffee beans and coffee benefited 12% moisture, to obtain the PRODUT variable. After exploratory data analysis, which showed the correlation between variables in the order of 0.899, was performed variogram analysis. Were adjusted theoretical variograms to PROD and PRODUT and cross variogram between two variables. Finally we estimated the value of productivity, both by ordinary kriging as per cokriging. The validation of the estimation by cokriging not shows, however, significant gains in relation to validation by ordinary kriging.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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As imagens de alta resolução espacial impulsionaram os estudos de Sensoriamento Remoto em ambientes urbanos, já que elas permitem uma melhor distinção dos elementos que compõem esse ambiente tão heterogêneo. Técnicas de Geoestatística são cada vez mais utilizadas em estudos de Sensoriamento Remoto e o variograma é uma importante ferramenta de análise geoestatística, pois permitem entender o comportamento espacial de uma variável regionalizada, neste caso, os níveis de cinza de uma imagem de satélite. O presente trabalho pretende avaliar a proposta metodológica que consiste em identificar padrões residenciais urbanos de três classes de uso e ocupação do solo por meio da análise dos valores apresentados pelos parâmetros, alcance, patamar e efeito pepita de um variograma. A hipótese é que os valores correspondentes a esses parâmetros representem o comportamento espectral padrão de cada classe e, portando, indicam que há um padrão na organização espacial de cada uma das classes. Para a presente pesquisa foram utilizadas imagem IKONOS 2002, e a classificação de uso e ocupação do solo da sub-bacia do córrego Bananal na bacia do Rio Cabuçu de Baixo em São Paulo SP. Amostras das imagens de cada classe foram extraídas e os valores de nível de cinza em cada pixel foram utilizados para calcular os variogramas. Após análise dos resultados obtidos, apenas o parâmetro alcance foi levado em consideração, pois é através desse parâmetro que se observa o grau de homogeneidade de cada amostra. Os valores de alcance obtidos nos cálculos dos variogramas identificaram com melhor precisão a classe Conjuntos Residenciais que é uma classe com padrões e características singulares, já a identificação das classes Ocupação Densa Regular e Ocupação Densa Irregular não obteve uma precisão boa, sendo que essas classes são similares em diversos aspectos.

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Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone health. The objective of this work was to determine if the structural attributes of savanna riparian zones in northern Australia can be detected from commercially available remotely sensed image data. Two QuickBird images and coincident field data covering sections of the Daly River and the South Alligator River - Barramundie Creek in the Northern Territory were used. Semi-variograms were calculated to determine the characteristic spatial scales of riparian zone features, both vegetative and landform. Interpretation of semi-variograms showed that structural dimensions of riparian environments could be detected and estimated from the QuickBird image data. The results also show that selecting the correct spatial resolution and spectral bands is essential to maximize the accuracy of mapping spatial characteristics of savanna riparian features. The distribution of foliage projective cover of riparian vegetation affected spectral reflectance variations in individual spectral bands differently. Pan-sharpened image data enabled small-scale information extraction (< 6 m) on riparian zone structural parameters. The semi-variogram analysis results provide the basis for an inversion approach using high spatial resolution satellite image data to map indicators of savanna riparian zone health.

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Approaches to quantify the organic carbon accumulation on a global scale generally do not consider the small-scale variability of sedimentary and oceanographic boundary conditions along continental margins. In this study, we present a new approach to regionalize the total organic carbon (TOC) content in surface sediments (<5 cm sediment depth). It is based on a compilation of more than 5500 single measurements from various sources. Global TOC distribution was determined by the application of a combined qualitative and quantitative-geostatistical method. Overall, 33 benthic TOC-based provinces were defined and used to process the global distribution pattern of the TOC content in surface sediments in a 1°x1° grid resolution. Regional dependencies of data points within each single province are expressed by modeled semi-variograms. Measured and estimated TOC values show good correlation, emphasizing the reasonable applicability of the method. The accumulation of organic carbon in marine surface sediments is a key parameter in the control of mineralization processes and the material exchange between the sediment and the ocean water. Our approach will help to improve global budgets of nutrient and carbon cycles.