13 resultados para geoestatistics


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Modeling of spatial dependence structure, concerning geoestatistics approach, is an indispensable tool for fixing parameters that define this structure, applied on interpolation of values in places that are not sampled, by kriging techniques. However, the estimation of parameters can be greatly affected by the presence of atypical observations on sampled data. Thus, this trial aimed at using diagnostics techniques of local influence in spatial linear Gaussians models, applied at geoestatistics in order to evaluate sensitivity of maximum likelihood estimators and restrict maximum likelihood to small perturbations in these data. So, studies with simulated and experimental data were performed. Those results, obtained from the study of real data, allowed us to conclude that the presence of atypical values among the sampled data can have a strong influence on thematic maps, changing, therefore, the spatial dependence. The application of diagnostics techniques of local influence should be part of any geoestatistic analysis, ensuring that the information from thematic maps has better quality and can be used with greater security by farmers.

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The soybean is the crop most cultivated in Brazil, with great socioeconomic importance. In the agriculture year 2008/09 in Selviria County, Mato Grosso do Sul State, in the Brazilian Savannah, was analyzed the production components and the soybean yield cultivated in a Typic Acrustox on no-tillage. The main purpose objective was select among the production components number of pods per plant, number of grains per pod, number of grains per plant, mass of a thousand grains, mass of grains per plant and population of plants, which of the best linear and spatial correlation aiming explain the soybean yield variability. The irregular geostatistical grid was installed to collect of data, with 120 sampling points, in an area of 8.34 ha. The values of spatial dependence range to be utilized should be among 38.1 and 114.7 meters. The model of the adjusted semivariograma was predominantly the spherical. of the lineal and spatial point of view, the number of pods per plant and the mass of grains per plant they were correlated in a direct way with the soybean yield, demonstrating be the best components to esteem her.

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Foi pesquisada a variabilidade espacial de alguns atributos físicos e químicos de uma associação de solos cultivada sob videira (Vitis vinifera-L), do município de Vitória Brasil, estado de São Paulo, Brasil. O objetivo foi estudar a dependência espacial de tais atributos, assim como caracterizar as respectivas variabilidades, distribuições de freqüência e números mínimos de subamostras do solo para a cultura da videira. Para isso, coletaram-se dados do solo, dispostos segundo uma malha com 156 pontos amostrais, sendo analisados por meio da geoestatística. As maiores variabilidades foram verificadas para a macroporosidade (MA), P, K, Ca, Mg, SB e CTC, ao passo que as menores foram para a densidade do solo (DS), pH e V. O número mínimo de subamostras, necessário para formar uma amostra composta e representativa, variou de 1 (pH e V) a 241 (Mg), tendo seu valor médio de 64 subamostras. Quanto à dependência espacial, o P e o V apresentaram, respectivamente, forte e fraca dependência, enquanto o restante dos atributos apresentou moderada dependência. Desta forma, o alcance dos atributos físicos variou de 2,56 a 4,32 m, enquanto o dos químicos variou de 1,82 a 5,64 m.

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This work aimed to study the space behavior of the water erosion in a red-yellow latosol. Then a study was developed in an area with colinon coffee cultivation in an Experimental Farm of Bananal do Norte of INCAPER in Cachoeiro de Itapemirim - ES. Soil samples were obtained from 0,0 to 0,20 m depth in an irregular grid with 109 samples. The analyzed variables were granulometric fractions, erodibility (K), natural erosion potential (PNE), soil loss (A) and erosion risk (RE). All the variables showed space dependency with moderate index of space dependency and similar standard of space distribution. The soil loss is related with the space distribution of the granulometric fractions.

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The air temperature is a climatic element of interest for several agricultural related studies. Hence, daily air temperature from two locations in Brazil (Botucatu and Petrolina, with different climate classification), hourly recorded from January 2004 to December 2005, were analysed to verify if 24 h long air temperature variation can be predicted with 6 h interval records. Three data set were selected, with different first time record of air temperature, and analyses performed using geoestatistics to confirm the temporal dependency of records. Then, ordinary krigging was used to model air temperature variation within 1 h interval, and spherical model presented the best approach, with range of 11.6 h for Botucatu and 12.7 for Petrolina. For both locations, the time of air temperature recording was the most importnat factor on accuracy of estimation of air temperature variation. Records at 2, 8, 14 and 20 h and at 4, 10, 16 and 22 h presented the best approaches, but for records at 9, 15 and 21 h, the approach was worst.

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Water infiltration into soil is one of the basic factors for estimating irrigation intensity according to the plants' requirements; this is aimed at avoiding problems of surface run-off and degradation. The purpose of the present investigation was to determine the spatial variation of infiltration and its relationship to some physical properties of soil by means of geostatistical techniques in Typic Plinthaquult soils having average texture and flat relief. A 113 point mesh was designned, having a regular distance of 10 m between points, samples being taken from 0 to 0.20 meters depth. Sand, silt and clay content, bulk density, macroporosity, microporosity and total porosity were determined. Infiltration tests were carried out in the field by means of a 15 cm diameter ring. Descriptive statistics and geostatistics were used for analysing the data. Infiltration, silt and microporosity data did not fit a normal distribution curve. Infiltration had high variability, having an average 36.03 mm h(-1). Total porosity was 56.73%, this being the only property that did not show spatial dependency. The smallest ranges were observed for bulk density, macroporosity and microporosity, having values of less than 40 m. The smallest degrees of spatial dependence were observed for infiltration, silt and clay, evidence also being shown of the influence of silt and clay on infiltration rate. Contour maps were constructed; fitting them to the semivariogram models, together with studying the correlations, led to establishing relationships between the properties.

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The objective of this work was to identify the spatial variability of the natural erosion potential, soil loss and erosion risk in two intensely cultivated areas, in order to assess the erosion occurrence patterns. The soil of the area located at Monte Alto, São Paulo state, was classified as Paleudalf (PVA) with moderately slope, with different managements. The soil of the area located at Jaboticabal, São Paulo state, was classified as Haplortox(LV) with gentle slope and cultivated with sugarcane. A irregular grid was imposed on the experimental areas. Soil samples were obtained from 0-0.2 m depth at each grid point: 88 samples in Monte Alto area (1465 ha) and 128 samples at Jaboticabal area (2597 ha). In order to obtain the values of the studied variables USLE was applied at each grid point. Descriptive statistics were calculated, and geoestatistical analyses were performed for defining semivariograms. Kriging techniques to develop map showing spatial patterns in variability of selected soil attributes were used. All variables showed spatial dependence. The PVA soil showed higher erosion risk due to the slope and atual management compared to the soil LV.

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The obtaining of the correct space distribution for attributes of the soil is relevant in the agricultural planning, in what concerns to the installation and maintenance of the cultures. The objective of that work was to compare statistical interpolation methods (ordinary krigagem) and deterministic methods (inverse square distance) in the estimate of CTC and V% in a distrophic yellow-red Latossolo. The study was accomplished in the State of Experimental Hands on of the Instituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural (INCAPER), in an irregular grading with 109 points. The data were collected in the layer of 0 - 0,20 m in the projection of the cup of the plants, in the superior part of the slope. The performance of the interpolators was obtained and compared using the criterion of the medium mistake. The observations are dependent in space until a maximum reach of 14,1 m, considering the isotropy. IDW presented larger mistake in the estimate of the data; however its difference in relation to KRIG was small for both variables.

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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Os dados de sensoriamento remoto em campo podem fornecer informações detalhadas sobre a variabilidade de parâmetros biofísicos ligados à produtividade em grandes áreas e apresentam potencial para o monitoramento destes parâmetros, ao longo de todo o ciclo de desenvolvimento da cultura. Este trabalho objetivou mapear a variabilidade espacial do índice de vegetação da diferença normalizada (NDVI) e seus componentes, em duas lavouras comerciais de algodão (Gossipium hirsutum L.), utilizando sensor óptico ativo, em nível terrestre. Os dados foram coletados utilizando-se sensor instalado em um pulverizador autopropelido agrícola. Um receptor GPS foi acoplado ao sensor, para a obtenção das coordenadas dos pontos de amostragem. As leituras foram realizadas em faixas espaçadas em 21,0 m, aproveitando-se as passadas do veículo no momento da pulverização de agroquímicos, e os dados submetidos à análise estatística clássica e geoestatística. Mapas de distribuição espacial das variáveis foram elaborados pela interpolação por krigagem. Observou-se maior variabilidade espacial do NDVI e da reflectância espectral da vegetação na região do infravermelho próximo (IVP) (880 nm) e do visível (590 nm) na lavoura com maior estresse fisiológico, devido ao ataque do percevejo castanho [Scaptocoris castanea (Hem.: Cydnidae)], em relação à lavoura sadia.